Fig. 1 - Aix Marseille UniversitÃ©

U NIVERSITE D’AIX-MARSEILLE I - U NIVERSITE DE P ROVENCE 

UFR DE P SYCHOLOGIE, S CIENCES DE L’EDUCATION 

THÈSE 

en vue de l'obtention du grade de 

DOCTEUR DE L'UNIVERSITÉ D'AIX-MARSEILLE I 

Formation doctorale : Psychologie 

Présentée et soutenue publiquement par 

K ATHERINE M IDGLEY 

le 13 février 2009 

L E LEXIQUE BILINGUE 

ETUDES ELECTROPHYSIOLOGIQUES 

DES INTERACTIONS INTER- LANGUES 

sous la direction de J ONATHAN G RAINGER 

membres du jury : 

Jonathan Grainger, Directeur de Recherche, CNRS 

Sonja Kotz, Professeur, Institut Max Planck, rapporteur 

Jean-Marc Lavaur, Professeur, Université Paul Valéry 

Janet van Hell, Professeur, Université de Nimègue, rapporteur 

Johannes Ziegler, Directeur de Recherche, CNRS

à mes bilingues

Remerciements 

Il y a un nombre de personnes sans qui ce travail ne serait pas ce qu'il est. 

There are many who have helped shape this work. But first I must thank the 

Je remercie en premier lieu les participants qui se sont livrés avec joie et bonne 

participants who lent their brains to my questioning. Without them science 

humeur à mes expérimentations. Sans eux la science n’existerait pas. 

cannot exist. To all who have helped me along the way, I thank you. 

Et à tous ceux qui m’ont assisté d’une façon ou d’autre - je vous remercie. 

You know who you are.

Sommaire 

1 | Introduction 9 

Les Modèles 11 

Potentiels évoqués 14 

Etudes bilingues en potentiels évoqués 18 

Difficultés en études bilingues 22 

Les études présentées 24 

2 | Les effets de langue chez des apprenants en langue seconde et des 33 

bilingues confirmés grâce à la technique des potentiels évoqués 

Résumé pagination du journal - 1 35 

Introduction 2 36 

1° Expérience 4 38 

Méthodes 4 38 

Résultats 7 41 

Discussion 8 42 









Discussion générale 15 49 

Références 18 52 

3 | Une étude électrophysiologique des effets de voisinage 55 

orthographique inter-langues 

Résumé pagination du journal - 123 57 

Introduction 123 57


Discussion générale 130 64 


Références 135 69 

4 | Les effets de cognats sur la compréhension des mots chez les 71 

apprenants en langue seconde : une étude en potentiels évoqués 

Résumé 74 

Introduction 75 

Méthodes 81 

Résultats 86 

Discussion 92 

Références 97 

5 | L'amorçage masqué de répétition et par équivalent de traduction 101 

chez des apprenants en langue seconde : un regard sur le décours 

temporel de l'activation de la forme et du sens 

Résumé 104 

Introduction 105 

1° Expérience 111 

Méthodes 111 

Résultats 117 

Discussion 122 

2° Expérience 123 

Méthodes 124 

Résultats 124 

Discussion 130 

Discussion générale 131 

Références 136 

6 | Discussion générale 139 

| Bibliographie 151

Introduction 

Chapitre 1 

Introduction 

P | 9

Introduction 

A true universal account of language processing will require a 

detailed understanding of both monolingual comprehension 

and bilingual comprehension and the representations and 

processes involved. 

This statement, loosely quoted from de Groot and Kroll’s introduction of Tutorials 

in Bilingualism (1997), is partly the result of at least two important observations. One - 

bilingualism is prevalent. Grosjean (1982) estimates that more than half the world’s 

population has some experience in a language other than a native language. Two - many 

of the existing accounts of lexical processing that have been elaborated to date describe 

monolingual processing in great detail with rare contingencies for describing bilingual 

processing. However, we can point to two models that directly tackle the question of the 

bilingual lexicon, its organization and processes. 

The Models 

One of the earliest and most cited models describing the specifics of the bilingual 

lexicon is the Revised Hierarchical Model of Kroll and Stewart (1994). The model 

assumes a separation of lexical and conceptual representations of the lexicon with links as 

the provision for mapping form to meaning. The RHM posits a single conceptual level 

that can be accessed via links from lexical items from both a bilingual’s first language 

(L1) and second language (L2). In this model the conceptual links are stronger between 

well established L1 lexical entries and conceptual representations than they are between 

P | 11

Introduction 

lexical entries of a newly acquired L2 and conceptual representations. (See figure 1.) The 

RHM also describes an interconnectivity between the lexical representations of a 

bilingual’s two languages with direct lexical links that are stronger from L2 lexical 

representations to L1 lexical representations than they are from L1 lexical representation 

to L2 lexical representations. 

Figure 1. The revised Hierarchical Model (RHM) 

This model provides an architecture around which it is possible to make hypotheses 

about the interactions of a bilingual’s two languages. This model also leaves room to 

describe the changes that occur over time as a bilingual’s, or a learner’s experience with 

both L1 and L2 evolves. As a learner becomes more proficient in his L2 conceptual links 

between the L2 lexical representations and concepts will strengthen while links between 

L2 lexical representations and L1 lexical representations will weaken. 

Strategies on the part of the learner, such as the express study of vocabulary and 

grammar as is the case with classroom learning, lead to explicit knowledge. This explicit 

learning is often the method for late learners of an L2. The strong lexical links from L2 to 

L1 reflect a type of explicit learning where L2 items rely on their L1 translations to 

P | 12

Introduction 

access meaning. This asymmetry is supported by translation studies reporting better 

performance from L2 to L1 than vice-versa and by studies showing better performance in 

translation as compared to picture naming in L2 (Kroll & Curley, 1988; Chen & Leung, 

1989; de Groot, 1992). 

While the RHM proposes separate stores for L1 and L2 lexical items, providing for 

the possibility of interaction between the two stores, another bilingual lexicon model, the 

Bilingual Interactive Activation Model or BIA model (Grainger & Dijkstra, 1992; van 

Heuven, Dijkstra, & Grainger, 1998) posits a completely integrated and highly interactive 

bilingual lexicon as does its successor the BIA+ model (Dijkstra & van Heuven, 2002 - See 

figure 2.) The BIA model is an implemented connectionist model in the line of 

McClelland and Rumelhart’s Interactive Activation (IA) model (1981). This model adds 

on to the monolingual IA model. It adds an integrated lexicon of two languages and an 

extra representational layer containing two language nodes. These language nodes 

connect to all the items in both lexica. The model posits non-selective bottom-up 

processing in which words from both languages are activated along with languagespecific 

top-down processing in which the language nodes selectively inhibit activity in 

words of the non-appropriate language. At the word level all words inhibit each other. 

Activated word nodes from the same language send activation to the corresponding 

language node. The activated language node sends inhibitory feedback to all word nodes 

in the other language. Language nodes collect activation from words in the language that 

they represent and inhibit active words of the other language. This model addresses 

questions of language selectivity as it is possible within this model’s framework to obtain 

results that show both language selectivity and language non-selectivity as does the 

bilingual lexicon literature. 

P | 13

Introduction 

Figure 2. The Bilingual Interactive Activation Model (BIA) 

Throughout the chapters of this work we will refer to these two models. The RHM 

is a descriptive model that captures the asymmetries of a bilingual’s two lexicons and can 

also be used to describe the changes over time of a second language learner. The BIA 

model is an instantiated computational model that assumes certain proficiency. Many 

phenomena related to bilingual word recognition can be simulated with the BIA model. 

Event-Related Potentials - ERPs 

The ERP technique involves measuring the brain's electrical activity at the scalp 

(electroencephalogram or EEG) and time-locking this activity to specific stimulus events. 

The individual EEG waveforms to the stimulus events are then averaged across the same 

or experimentally similar items to yield a waveform characterizing the measurable part of 

the brain's electrical response to the stimulus category of interest. The important thing to 

keep in mind is that it is the averaging process that extracts the voltage signature of a 

particular stimulus condition from the background noise. The waveforms resulting from 

P | 14

Introduction 

the averaging, the ERPs, are a series of peaks and valleys that are identified as ERP 

components. Researchers have linked the various components in the ERP waveform to a 

number of cognitive processes (Coles & Rugg, 1995; Lau, Phillips & Poeppel, 2008 for 

reviews). 

One ERP component that is of particular interest for the presented studies is the 

N400. The N400 is a negative-going wave that usually starts around 250-300 ms and 

peaks at approximately 400 ms after the onset of a stimulus. Numerous studies have 

found the N400 to be involved in some aspect of semantic processing. Kutas and Hillyard 

(1980, 1984) were the first to report on this component. They found it in a sentential 

context to be larger in amplitude in response to sentence final words that are semantically 

anomalous (e.g., "He takes his coffee with cream and dog.) and that it is greatly reduced 

or even absent to high probability congruent sentence endings (e.g., "He takes coffee with 

cream and sugar."). Based on findings such as these and others it has been argued that the 

N400 reflects the process of semantic integration (Brown & Hagoort, 1993; Holcomb, 

1993). Larger N400s are taken as being indicative of a more effortful or involved 

integration process. 

Subsequent work has shown that the N400 is also elicited to words outside of a 

sentence context. For example, in one early study Bentin, McCarthy & Wood (1985) 

demonstrated N400s to word pairs in a semantic priming task. Target words preceded by 

semantically related prime words (e.g., doctor-NURSE) produced smaller N400s than 

target words preceded by unrelated words (e.g., truck-NURSE). Other studies using 

words in lists with no sentence or semantic context have also reported effects on the 

N400. For example, Münte, Wieringa, Weyerts, Szentkuti, Matzke and Johannes (2001) 

showed that the N400 is sensitive to word frequency with low frequency words having a 

larger N400 amplitude than high frequency words. The general conclusion from this and 

P | 15

Introduction 

other studies is that virtually any word processed for meaning will produce an N400 

response (Holcomb, 1993). 

An important example of a study using single word presentation was one by 

Holcomb, O’Rourke and Grainger, (2002). In this study the authors demonstrated that 

N400 amplitude is sensitive to the size of a word’s orthographic neighborhood. The N400 

was larger to items that were similar to many other words (e.g., words like “time”) than to 

items that resembled only a few or no other word (e.g., “yacht”). They interpreted this 

result as supporting a view of the N400 whereby it reflects activity at the interface of 

form and meaning during word processing. 

More recently research using masked priming paradigms has elaborated on the 

timing of visual word recognition. Holcomb and Grainger (2006) describe the modulation 

of the N400 and earlier components, including the N250, that reflect the sequential 

overlapping steps in the processing of printed words. The N250 component is also of 

interest for the work presented here. Holcomb and Grainger compared targets that were 

full repetitions of, partial repetitions of, or unrelated to their masked primes. They found 

strong modulation of the N400 and N250 for full repetitions as compared to unrelated 

targets (see Figure 3). The amplitude of these components in the case of partial repetitions 

compared to unrelated items was between that of full repetitions and unrelated primes. 

This led Holcomb and Grainger to propose that the N250 reflected the mapping of 

sublexical form representations (e.g., letters and letter combinations) onto lexical 

representations. 

P | 16

Introduction 

Figure 3. From Holcomb and Grainger 2006, fig. 3b. ERPs time locked to target onset in the three 

repetition conditions at CP1 site. Negative voltages are plotted upward. 

Throughout this work we will present research conducted using ERPs. 

Electrophysiological measures were preferred here because they more directly reflect the 

processing of items, being an on-line measure of brain activity rather than, as in the case 

with behavioral measures such as reaction times, just one data point after processing has 

been completed. Moreover, ERPs are multidimensional in that not only are they a 

measure of “voltage” but they also they contain precise time-course information and scalp 

distribution information. This allows us to draw conclusions not only about the time 

course of word processing but also concerning possible differences in the nature of this 

processing. For example, one effect observed using behavioral methods could be shown 

to have an effect on two different ERP components, which by inference would implicate 

two different perceptual or cognitive processes. Similarly, differences in time-course of 

effects could point to different loci for these effects. Furthermore since much research 

designed to probe the bilingual lexicon has been conducted using behavioral measures it 

P | 17

Introduction 

is our position that the added multidimensional sensitivity of this electrophysiological 

data can only enrich our collective knowledge of the subject. 

ERP studies of bilingual visual word processing 

Yet ERPs have been used to study issues of bilingual language comprehension. A 

recent review by Moreno, Rodríguez-Fornells & Laine (2008) listed over 30 publications 

where ERPs were used to characterize some aspect of bilingual language processing, and 

this was by no means an exhaustive list (we found 45 studies published since 1996). 

Of particular relevance to the experiments in this dissertation is the much smaller 

set of studies that have used ERPs to examine visual word processing in second language 

learners. In one of the first such studies Kotz (2001) set out to examine semantic priming 

in early fluent Spanish-English bilinguals. ERPs were recorded while participants made 

lexical decisions on target items in either Spanish or English. The results demonstrated 

that both associative (e.g., girl-BOY or chica-CHICO) and categorical (junior-BOY or 

joven-CHICO) priming produced the typical reduction in N400 amplitude in both L1 and 

in L2. This pattern is consistent with the view that, at least in proficient bilinguals, there 

is not an asymmetry in lexical-semantic connections in L1 and L2. A more recent study 

by this same group (Kotz & Elston-Guttler, 2004) used the same ERP priming method but 

with native German late learners of English. Participants were assigned to two 

proficiency groups. Unlike the early proficient participants in Kotz (2001) neither group 

of late learners showed a robust categorical priming effect on the N400 in their L2, 

although both groups showed effects of associative priming. This pattern of results was 

taken to indicate that categorical relationships require an early exposure to a second 

language, while associative relationships can be acquired later. 

P | 18

Introduction 

In a study similar to that of Kotz (2001), Phillips, Segalozitw, O’Brien & Yamasaki, 

(2004) investigated individual differences in second language (L2) proficiency by looking 

at the efficiency of semantic priming. Twenty-nine L1 English speakers varying in L2 

(French) proficiency read lists of words in English and French blocked by language. 

Critical target words were either primed by a semantic associate in the preceding trial 

(e.g. adult-CHILD) or were unprimed (e.g. rabbit-CHILD). High proficiency participants 

showed an N400 priming effect in both L1 and L2 (i.e., smaller N400s for targets 

following related primes than unrelated primes), but low proficiency participants showed 

only a priming effect in L1. Moreover, in the high proficiency group the N400 effect was 

delayed by 50 ms in L2 compared to L1. 

Two ERP studies have been conducted looking at interlingual-homographs in 

Dutch-English bilinguals (de Bruijn, Dijkstra, Chwilla & Schriefers, 2001; Kerkhofs, 

Dijkstra, Chwilla & de Bruijn, 2006). Interlingual homographs are words that are spelled 

the same in both languages (i.e., they have the same orthographic form) but have different 

meanings in the two languages. In the first study, de Bruijn et al. (2001) had bilinguals 

perform a generalized lexical decision task on triplets of items, responding with “yes” if 

all three items were correct Dutch and/or English words, and with “no” if one or more of 

the items was not a word in either language. The critical manipulation was that sometimes 

the second item in a triplet was an interlingual homograph whose English meaning was 

semantically related to the third item of the triplet (e.g., HOUSE - ANGEL - HEAVEN, 

where ANGEL means “sting” in Dutch). In such cases, the first item was either an 

exclusively English (HOUSE) or an exclusively Dutch (ZAAK) word. The ERP results 

showed clear N400 priming effects on the third item and these were not affected by the 

language of the first item in the triplets. In other words the N400 to ANGEL-HEAVEN 

was attenuated compared to an unrelated pair of words even when the ANGEL was 

P | 19

Introduction 

preceded by a Dutch word which presumably puts the reader in a Dutch mode of 

processing for the subsequent word ANGEL (sting), which is not related to the word 

HEAVEN. The authors claimed this finding was evidence in support of a strong bottomup 

role with respect to bilingual word recognition. 

A second study (Kerkhofs et al., 2006) also used a semantic priming paradigm and 

interlingual homographs. This study examined the effects of semantic and lexical– 

orthographic context in Dutch–English bilinguals who performed an English lexical 

decision task in which homograph target words like STEM (meaning “voice” in Dutch) 

were preceded by primes like ROOT (a related word in English) or FOOL (and unrelated 

word in English). N400 effects were found for homograph targets preceded by related 

(ROOT-STEM) compared to unrelated primes (FOOL-STEM) a result consistent with the 

findings of de Bruijn et al. (2001). The amplitude of the N400 effect was also modulated 

by the word frequency of the targets in both their Dutch and English reading, although in 

the opposite direction (i.e., smaller N400s for high frequency English and larger N400s 

for high frequency Dutch readings). These data would also appear to argue for a strong 

bottom-up role with respect to bilingual word recognition. 

A seemingly contradictory finding comes from Rodríguez-Fornells, Rotte, Heinze, 

Nosselt & Münte, (2002) who recorded ERPs and fMRI from bilingual Spanish/Catalan 

and monolingual Spanish participants. Participants were instructed to press a button when 

presented with words in one language, while ignoring words and pseudowords in the 

other language. The ERPs of bilingual participants to words of the non-target language 

were not sensitive to word frequency in that language suggesting that participants were 

able to reject these items at an early stage before semantic analysis. However, one 

difference between this study and the Dutch studies is that the Spanish/Catalan speakers 

were highly proficient in both languages and acquired both languages at an early age. The 

P | 20

Introduction 

Dutch/English bilinguals were presumably less proficient in L2 and learned it later. The 

ability to reject items from the other language then might reflect differences in the age of 

acquisition or proficiency. 

A 2004 study by McLaughlin employed a novel approach for using ERPs in the 

study of second language learning. In their study ERPs were recorded in a lexical 

decision semantic priming paradigm in L1 English speakers (similar to the Kotz 2001 

study). However, they only included L2 (French) stimuli and tracked changes in the ERPs 

as participants progressed through their first university French course. In the first session 

participants who had had only 14 hours of instruction in French showed significant 

differences between word and pseudoword N400 responses. The results were similar to 

monolingual studies which have consistently shown larger N400s for pseudowords than 

real words (e.g., Holcomb & Neville, 1990). A control group of monolingual English 

speakers (with no French experience) showed no difference between real French words 

and French-like pseudowords. Moreover, these effects of word-pseudoword N400s 

continued to increase as participants received more instruction in French from 14 to 63 to 

138 hours. Moreover, with more instruction semantic priming effects on the N400 began 

to emerge. 

A recent study by Thierry and Wu (2007) illustrates another way ERPs have been 

used to augment behavioral measures of bilingual processing. Similar to the Dutch studies 

using interlingual homographs Thierry and Wu sought to determine if the native language 

of bilingual individuals is active during second-language comprehension. Chinese– 

English bilinguals were required to decide whether English (L2) words presented in pairs 

were related in meaning or not (i.e., semantic priming). However, rather than present L1 

words that participants could read along with the L2 items (a procedure that arguably 

alerts participants to the bilingual nature of the task), Thierry and Wu unbeknownst to 

P | 21

Introduction 

their participants, included L2 words which concealed (masked) a Chinese word that was 

a translation of the L2 item. Interestingly, there was no evidence of the masked L1 items 

affecting behavioral performance, but it did significantly modulate the N400 in expected 

direction (smaller N400s for translations compared to unrelated words), establishing that 

English words were automatically and unconsciously translated into Chinese. Critically, 

the same modulation was found in Chinese monolinguals reading the same words in 

Chinese. These findings demonstrate that native-language activation is an unconscious 

correlate of second-language comprehension. 

These ERP studies make important contributions to the literature on bilingual visual 

word processing. However, even though these specific pieces have been added it is clear 

that many aspects of bilingual word processing still remain unexplored with 

electrophysiological methods. For example, although there have been two studies using 

interlingual homophones to probe bilingual word processing no studies using ERPs have 

been conducted using cognates. No studies examining the effects of orthographic 

neighborhood and its effects in a bilingual context have been reported. More surprisingly, 

there are no reported studies that directly compare processing between an L1 and an L2. 

It is our position that electrophysiological methods can bring a wealth of information to 

what is known about bilingual visual word processing. This dissertation presents four 

articles, three of which are published or accepted for publication, that we hope will add 

significantly to the field of bilingual visual word recognition. 

Thorny issues in bilingual studies 

Bilingualism may be the norm for many of the world’s populations but its forms 

certainly cannot be generalized. The language experience of bilinguals and second 

language learners varies enormously. State agendas regarding the obligation, the amount 

P | 22

Introduction 

and the starting age of second language study in schools vary wildly from country to 

country. Populations where balanced bilingualism is rampant can be found (e.g. the 

Basque country, Catalonia, San Diego County) as can populations where a majority 

language is not the dominant L1 of a great number of speakers (e.g. New York City). The 

emphasis on teaching English as a second language has been on the rise in many 

countries across the globe. These quick observations illustrate the fact that there are 

varying levels of bilingualism, various bilingual situations and varying attitudes towards 

bilingualism and second language learning that could very well affect its study. 

Furthermore we can imagine that there are important differences in the lexicons of 

bilinguals that share very similar languages like Spanish and French when compared to 

bilinguals that come from very different language groups like Finnish and French and that 

a difference in script between a bilingual’s two languages like between Hebrew and 

French would result in its own specificity. These factors tend to complicate the 

generalization of studies that may use comparisons between any two language 

combinations difficult. 

Another thorny issue is the question of proficiency and how to measure it in order to 

compare results across studies. Furthermore in the context of studying learners it is clear 

that a learner’s competence in L2 changes over time. What isn’t clear is how to select a 

homogenous group of L2 learners and how to compare them to other populations of L2 

learners. 

The bottom line in bilingual studies, given all the possible variation due to different 

language pairs, proficiency, homogeneity of population, is that precaution must always be 

exercised when comparing results of studies that have been conducted in different 

populations. 

P | 23

Introduction 

We sought solutions to these issues for the research presented in this dissertation. 

We consistently studied learners and bilinguals from the same language combination, i.e., 

French and English. Our L2 learner participants were students at Tufts University in the 

Boston area who were engaged in studying French and students from the University of 

Provence in the Aix-en-Provence area who were studying English. One solution was to 

keep our populations as homogeneous as possible by selecting participants from 

university learners at the same level of study. However, we did note differences between 

the group of American students and the group of French students. These differences were 

presumably due to the difference of commitment between the two groups. The French 

university students were studying only English while the Tufts students had French in 

addition to many other subjects. Moreover, we conducted our studies in two ERP 

laboratories, one at Tufts University and one in Marseille at the LPC (Laboratoire de 

Psychologie Cognitive) that were designed to be as identical as possible allowing us to 

compare our results. 

The presented studies 

The studies that are the starting point for this dissertation do not address the 

complex question of language interactivity but are a simple interrogation of the 

processing differences between an L1 and an L2. In chapter two we present research that 

looks at the differences in processing using electrophysiological methods and observing 

language learners and proficient bilinguals. Across three experiments we compared ERPs 

to words passively read for meaning in bilingual participants of different proficiency 

levels and from different L1 language populations who were all adult learners of their L2. 

The first two experiments in chapter two investigate mechanisms underlying word 

recognition in second language learners. Are the mechanisms involved in word 

P | 24

Introduction 

recognition in L1 and L2 basically the same, that is, are L2 words integrated into a 

common set of lexical representations much like newly acquired words in L1? Or is there 

a different mechanism involved in L2 word recognition in adult learners? Are L2 words 

somehow associated with L1 equivalents as the RHM proposes and as explicit adult 

learning may induce? 

An integrated lexicon view of how languages are represented in the bilingual mind 

would appear to predict that L2 words should be processed much in the same way as L1 

words. According to this account, words in L2 would be influenced by the same factors 

that are known to influence L1 processing. By a pure frequency account of word 

processing, words in a second language learner’s L2 should behave like low-frequency 

words in L1 (Van Petten & Kutas, 1990; Münte et al., 2001). Much prior behavioral 

research shows that performance in L2 is slower and less accurate than performance in 

L1. This could be accounted for by the relative frequency characteristics of the words in 

each language with L2 items having a lower subjective frequency. Age-of-acquisition 

(AoA) is a factor that has been seen to influence word processing in research with 

monolinguals (Morrison & Ellis, 1995, 2000). In the case of adult learners of an L2 AoA 

could be a factor driving differences in performance to L1 and L2 words. In this case we 

would expect to see ERP language effects that are similar to AoA effects in 

monolinguals. Alternatively L2 words might be less interconnected to other L2 words, 

having smaller orthographic neighborhoods or fewer semantic associations than L1 words 

and these differences could be another factor that accounts for differences in 

performance. Our language effects in this case would mimic known monolingual 

neighborhood effects (Holcomb et al., 2002). 

On the other hand, any observed language effects could be the result of mechanisms 

that are specific to the developing bilingual lexicon such as the RHM would predict, i.e., 

P | 25

Introduction 

lexical level links between L2 and L1 items that favor an L1 based processing of L2 

words. Effects due to this type of mechanism may have a previously unobserved ERP 

signature. 

In the third experiment in chapter three the same language processing comparisons 

are made in a population of proficient bilinguals. The comparison of results between 

learners and proficient bilinguals permits us to observe the evolution of language effects 

over time and structure questions about how L2 processing mechanisms may change as a 

learner becomes bilingual. We call on the RHM and the BIA model to describe the 

language effects of our different populations. Throughout this work we are not interested 

in adjudicating between these two models. We choose to accept their different strengths 

and to reconcile them with the observations that the BIA model better reflects lexical 

processing in relatively proficient bilinguals, while the RHM is a better model for 

describing lexical processing in evolving bilinguals. 

Having addressed the question of processing specificities of a bilingual’s two 

languages in chapter two we move on to a significant debate in the literature on bilingual 

language comprehension in chapter three. This debate opposes proponents of languageselective 

processing to those who posit non-selective access to a set of representations 

that is shared by both languages. 

According to one version of the language-selective hypothesis a switching 

mechanism guides the linguistic input to the appropriate set of language-specific lexical 

representations (Macnamara, 1967; Macnamara & Kushnir, 1972). When a bilingual is 

operating in a monolingual context, according to this hypothesis, the language of the 

incoming information is completely predictable so there should be no cross-language 

interference and the input will be treated by the appropriate set of language 

representations. In contrast, in the non-selective access hypothesis word representations 

P | 26

Introduction 

from both languages are activated by orthographic or phonological similarities with the 

input resulting in competition between form-related words both within and across 

languages (van Heuven et al., 1998). 

Previous experiments demonstrating cross-language interference have provided 

evidence that bilinguals cannot block interference from the irrelevant language. There 

exists the possibility, however, that the mere presence of words in both languages will 

prevent bilinguals from processing in a pure “monolingual” mode (Grosjean, 1988). In 

order to provide more convincing evidence in favor of non-selective access, crosslanguage 

interference must be demonstrated in conditions where there is no explicit 

activation of the both languages simultaneously. The research presented in chapter three 

is based on a study by van Heuven et al. (1998) that avoided this mixing of a bilingual’s 

two languages. Van Heuven et al. did not explicitly manipulate the presence or absence of 

stimuli that belong to both languages such as inter-lingual homophones or cognates. 

Rather, they manipulated the presence of potential cross-language interference in the 

form of phonologically or orthographically similar words from the other language. 

They, as did we, manipulated the number of orthographic neighbors of items in the 

non-task relevant (non-presented) language in order to observe any cross-language 

interference. We observed the effects of cross-language neighborhood size on the N250 

and the N400 components in two experiments with proficient French-English bilinguals 

and English monolinguals and presented the results of a simulation using the BIA+ 

computational model. The non-selective hypothesis proposes that the initial feed-forward 

sweep of information from the linguistic input can make contact with lexical 

representations from both. This is a central hypothesis of the Bilingual Interactive- 

Activation model (Grainger & Dijkstra, 1992; van Heuven et al, 1998). We discuss the 

results of the bilingual study and the simulation within the framework of the BIA+ model. 

P | 27

Introduction 

The interactivity of a bilingual’s word representations is touched upon in chapter 

three and we continue to explore interactivity in the next chapter. Chapter four presents a 

study that exploits an oft used device for bilingual research, the cognate. Cognates are 

favored in bilingual research because they are a special case of interactivity, where form 

and meaning coincide across languages. Cognates are words like “table” that in French 

and English share orthography, much phonology and complete semantic overlap. Because 

of their shared form with L1 items, cognates, during L2 acquisition, could be a learner’s 

first foothold into the new lexicon. Presumably in the early stages of acquisition this 

would result in different patterns of processing for cognates and non-cognates while 

processing in L2. In the case of L1 processing, if cognates showed different patterns of 

processing when compared to non-cognates this would be evidence of L1 changing as a 

function of learning an L2 and also point to an integrated, interactive lexicon. 

In many behavioral studies cognate items have been shown to elicit different RT 

patterns than non-cognate items; they are recognized more rapidly than non-cognates, 

they have been shown to be translated more quickly than non-cognates, and stronger 

priming has been found for cognates than for non-cognates (Dijkstra, Grainger & van 

Heuven, 1999; Lemhöfer & Dijkstra, 2004; Lemhöfer, Dijkstra & Michel, 2004; de 

Groot, 1992; Sánchez-Casas, Davis, & García-Albea, 1992; van Hell & de Groot,1998; de 

Groot, Delmaar & Lupker, 2000; van Hell & Dijkstra, 2002; Cristoffanini, Kirsner, & 

Milech, 1986; Lalor & Kirsner, 2001; de Groot & Nas, 1991; Gollan, Forster, & Frost, 

1997; Voga & Grainger, 2007). The majority of previous behavioral studies that observed 

a cognate advantage did so in paradigms that tested processing in L2. What about cognate 

processing in L1? Studies in this direction have given mixed results (Caramazza & 

Brones, 1979; Gerard & Scarborough, 1989; van Hell & de Groot,1998; de Groot et al., 

2000; van Hell & Dijkstra, 2002) making it appear that word recognition in L2 benefits 

P | 28

Introduction 

from cognate status, whereas word recognition in L1 may be somewhat immune to such 

influences. However effects of cognate status on word recognition in L1 have been 

documented. Van Hell and Dijkstra (2002) showed clear effects of cognate status during 

L1 processing and this while testing 2 groups of bilinguals of different proficiencies. 

They observed that only more fluent bilinguals showed clear effects of an L3 on L1 

processing while the less proficient bilinguals showed only a trend for these effects. They 

concluded that a certain level of proficiency is necessary in the bilinguals’ non-target 

language relative to their target language in order to observe effects on processing in the 

target language. In other words a bilingual must have enough fluency in L2 for L2 word 

status to influence L1 processing. 

We used electrophysiological measures once again to improve our chances of 

observing effects in our population of L2 learners. We sought evidence for mechanisms 

that would be the basis of the observed behavioral advantage in processing cognate words 

compared with non-cognates and this during processing in both languages. We again 

observed the N400 component that reflects processing of a word and can inform us of the 

relative difficulty of settling on a unique form-meaning interpretation of a word. 

Chapters two, three and four explore the bilingual lexicon in proficient bilinguals 

and second language learners primarily seeking insights about the similarities and 

differences of processing in L1 and L2, language selectivity and the level of integration 

and interactivity of the bilingual lexicon. Yet on a broader perspective, bilinguals and 

second-language learners provide an ideal testing ground for general theories of how 

form and meaning representations interact during language comprehension in general. 

The study presented in chapter five examines masked within-language repetition priming 

in L1 and L2 and masked translation repetition priming in order to examine the relative 

P | 29

Introduction 

contributions of form and meaning based representations in bilingual word processing. 

However, on a larger scale the results may speak to word recognition in general. 

The question of when semantic information becomes available during visual word 

recognition and the nature of the form-level processing that is necessary for that to occur 

during L1 processing and during L2 processing is addressed in this chapter. 

Non-cognate translation equivalents (e.g., the English word “tree” and its French 

translation “arbre”) arguably provide the closest possible semantic relation between two 

distinct word forms. They therefore provide an ideal testing ground for the interplay 

between form-level and semantic-level processes during visual word recognition. 

Studies investigating masked non-cognate translation priming effects have produced 

mixed results. Effects of masked translation priming have been consistently found in the 

direction of L1 priming L2 (De Groot & Nas, 1991; Gollan et al, 1997; Sanchez-Casas et 

al., 1992). However observing similar priming in the L2 to L1 direction has not been 

conclusive. Many studies failed to observe masked translation priming in this direction 

(Altarriba, 1992; Fox, 1996; Keatley & de Gelder, 1992; Keatley, Spinks, & de Gelder, 

1994; Kroll & Sholl, 1992). Robust masked translation priming has been reported for 

languages of different scripts in both directions (Finkbeiner, Forster, Nicol, & Nakamura, 

2004; Gollan et al., 1997; Voga & Grainger, 2007) but also found in a same script context 

by Grainger and Frenck-Mestre (1998) in proficient English-French bilinguals in the L2- 

L1 direction. 

In recent research, the masked priming paradigm has been used with ERP 

recordings to map out the time-course of component processes in visual word recognition 

(e.g., Grainger, Kiyonaga & Holcomb, 2006; Holcomb & Grainger, 2006; Kiyonaga, 

Grainger, Midgley & Holcomb et al., 2007). Holcomb and Grainger (2006) described a 

P | 30

Introduction 

cascade of ERP components elicited in masked priming paradigms. In chapter four we are 

interested in two of these components the N250 and the N400. The N250 is a negativegoing 

component which peaks near 250 ms. Holcomb and Grainger propose that the 

N250 reflects processes in visual word recognition where sublexical form representations 

(letters and letter combinations) are mapped onto the lexical system. The N400 has been 

observed in a host of word processing studies and described as reflecting some aspect of 

semantic processing (e.g., Kutas & Hillyard, 1980, 1984; Kounios & Holcomb, 1992, 

1994). In masked priming paradigms both the N250 and the N400 have been found to be 

modulated by the degree of form overlap across prime and target stimuli, with unrelated 

primes generating more negative waveforms than primes that are the same word as 

targets, or orthographically similar words. 

The study presented in chapter four compares within-language repetition priming 

and translation priming in order to obtain an improved picture of the time-course of form 

and meaning activation both within and between the lexical and semantic systems of 

second language learners. The N250 and N400 ERP components will be used to infer 

form-level and semantic-level influences on processing. Even if these two components 

reflect to some extent a combination of form and semantic influences, we expect formlevel 

influences to be greater on the N250, and semantic level influences to be greater on 

the N400. 

This then allows us to test the predictions of the RHM (Kroll & Stewart, 1994) and 

BIA model (Grainger & Dijkstra, 1992). In the RHM there are stronger links from L2 

lexical representations to L1 lexical representations than from L1 lexical representations 

to L2 lexical representations, and weaker links between L2 lexical representations and 

concepts than between L1 lexical representations and concepts. L2 primes should 

therefore affect form-level processing of the upcoming translation in L1, modulating the 

P | 31

Introduction 

N250 component, and in consequence the N400. L1 primes, on the other hand, should 

mostly affect semantic level processing of upcoming L2 translates, and therefore only 

modulate the N400 component. According to the BIA model, translation priming is 

always semantically mediated (i.e., there are no excitatory connections between lexical 

form representations of translation equivalents), hence most of the effects should be 

evident in the N400. Some priming effects are nevertheless expected on the N250 

component via feedback from semantics to lexical representations (Voga & Grainger, 

2007), and these should be most evident with L1 primes and L2 targets, simply because it 

is assumed that L1 words are processed more rapidly and efficiently than L2 words. If 

this is indeed the case, we should also observe smaller and later effects in L2-L2 

repetition priming than L1-L1 repetition priming. 

The four articles in this dissertation, while not a complete picture of bilingual word 

recognition, present studies using electrophysiological measures that inform the existing 

body of research. The following chapters address important questions about similarities 

and differences of processing in L1 and L2, language selectivity and the level of 

integration and interactivity of the bilingual lexicon and provide insight into the timecourse 

of bilingual lexical processing and the more general question of how form and 

meaning representations interact during language comprehension. 

P | 32

Effets de langage 

Chapitre 2 

Les effets de langue chez des 

apprenants en langue seconde et des bilingues 

confirmés grâce à la technique des potentiels évoqués* 

Dans cette étude nous avons examiné les effets de langue chez des apprenants en langue 

seconde avec la méthode des potentiels évoqués. Dans trois expériences nos sujets ont été 

confrontés à des listes constituées de mots appartenant à leur langue première (L1) et de 

mots appartenant à leur langue seconde (L2). Dans la première expérience, les 

participants dont la première langue était l’anglais et qui suivaient à l’Université des 

cours de français, ont lu deux listes de mots: l’une entièrement composée de mots anglais, 

l’autre de mots français. Nous avons observé un important effet de langue sur l’amplitude 

de la composante N400, effet qui commençait à se manifester dès 150 ms après la 

présentation du stimulus. Un pattern similaire a été mis en évidence au cours de 

l’expérience suivante dans laquelle les apprenants avaient pour L1 le français et pour L2 

l’anglais. La similitude des effets dans ces deux premières expériences nous portent à 

croire que les effets observés sont dus à des dominances linguistiques et non à la langue 

elle-même. Dans la troisième expérience, les participants étaient des bilingues 

compétents. Ils ont produit un pattern différent concernant les effets de langue, ces 

derniers semblent-ils modulés par le niveau de compétence linguistique du sujet. Ces 

résultats renforcent l’hypothèse selon laquelle des mécanismes spécifiques seraient 

impliqués dans la reconnaissance des mots au cours des phases précoces d’acquisition de 

la L2 chez des apprenants tardifs en comparaison à la reconnaissance des mots en L1. 

Mots-clefs : traitement des mots visuel, bilinguisme, N400 

________________________ 

* Article in press, Journal of Neurolinguistics, August 2008 

P | 33

ARTICLE IN PRESS 

+ MODEL 

Journal of Neurolinguistics xx (2008) 1e20 

www.elsevier.com/locate/jneuroling 

Language effects in second language learners and 

proficient bilinguals investigated with event-related 

potentials * 

Katherine J. Midgley a,b, *, Phillip J. Holcomb a , Jonathan Grainger c 

a Department of Psychology, Tufts University, Medford, MA, USA 

b Université de Provence - Aix-Marseille I, Marseille, France 

c CNRS, Marseille, France 

Received 30 March 2008; received in revised form 6 August 2008; accepted 11 August 2008 

Abstract 

The present study examines language effects in second language learners. In three experiments 

participants monitored a stream of words for occasional probes from one semantic category and ERPs 

were recorded to non-probe critical items. In Experiment 1 L1 English participants who were university 

learners of French saw two lists of words blocked by language, one in French and one in English. We 

observed a large effect of language that mostly affected amplitudes of the N400 component, but starting as 

early as 150 ms post-stimulus onset. A similar pattern was found in Experiment 2 with L1 French and L2 

English, showing that the effect is due to language dominance and not language per se. Experiment 3 

found that proficient French/English bilinguals exhibited a different pattern of language effects showing 

that these effects are modulated by proficiency. These results lend further support to the hypothesis that 

word recognition during the early phases of L2 acquisition in late learners of L2 involves a specific set of 

mechanisms compared with recognition of L1 words. 

Ó 2008 Elsevier Ltd. All rights reserved. 

Keywords: Visual word processing; Bilingualism; N400 

* This research was supported by grant numbers HD043251 & HD25889. 

* Corresponding author. Department of Psychology, Tufts University, 490 Boston Avenue, Medford, MA 02155, USA. 

Tel.: þ1 617 627 3521; fax: þ1 617 627 3181. 

E-mail address: kj.midgley@tufts.edu (K.J. Midgley). 

0911-6044/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. 

doi:10.1016/j.jneuroling.2008.08.001 

Please cite this article in press as: Katherine J. Midgley et al., Language effects in second language learners and 

proficient bilinguals investigated with event-related potentials, Journal of Neurolinguistics (2008), doi:10.1016/ 

j.jneuroling.2008.08.001


+ MODEL 

2 K.J. Midgley et al. / Journal of Neurolinguistics xx (2008) 1e20 

What are the basic mechanisms underlying word recognition in a second language (L2) in 

late learners of a foreign language, and to what extent do they overlap with the mechanisms 

involved in word recognition in the first language (L1)? One possibility is that the mechanisms 

are basically the same, and L2 words are integrated into a common set of lexical representations 

much like newly acquired words in L1. This would appear to be an unlikely possibility for late 

learners of a second language, at least in the early phases of L2 acquisition, for several reasons. 

First, anecdotally, many L2 learners report using translation into L1 as a general heuristic for 

processing L2 words. Second, given the relatively large number of cognates (words that share 

form and meaning in the two languages) in languages such as English and French, it would be 

more economical to establish L2eL1 formeform associations rather than creating new 

formemeaning associations. This is the position adopted by the revised hierarchical model 

(RHM) of word recognition in bilinguals proposed by Kroll and Stewart (1994) (Fig. 1). 

Nevertheless, the alternative hypothesis, that L2 words are basically processed in the same 

way as L1 words, would fit with an account of lexical representation in bilinguals according to 

which words from both languages are stored together. Indeed, there is an abundance of 

behavioral evidence in favor of a language non-selective, integrated lexicon view of written 

word comprehension in bilinguals, at least when the two languages share the same alphabet 

(e.g., Beauvillain & Grainger, 1987; Brysbaert, Van Dyck, & Van de Poel, 1999; De Groot, 

Delmaar, & Lupker, 2000; Dijkstra, Grainger, & van Heuven, 1999; Dijkstra, van Heuven, & 

Grainger, 1998; Dijkstra, Timmermans, & Schriefers, 2000; Dyer, 1973; Guttentag, Haith, 

Goodman, & Hauch, 1984; Lemhöfer et al., 2008; Nas, 1983). According to this view, bottomup 

processing of a printed word proceeds independently of the language to which that word 

belongs, up to the level of whole-word representations stored in a word-form lexicon that is 

common to both languages, and possibly beyond. Perhaps the strongest evidence in favor of this 

non-selective approach to bilingual lexical access was provided by van Heuven, Dijkstra, and 

Grainger (1998) who showed that word recognition in one language was affected by the target 

word’s orthographic neighbors in the other language. The major conclusion from this and 

Fig. 1. The revised hierarchical model (Kroll & Stewart, 1994). 





+ MODEL 

K.J. Midgley et al. / Journal of Neurolinguistics xx (2008) 1e20 

3 

related behavioral research is that bilinguals cannot completely stop interference from the nontarget 

language (see Midgley, Holcomb, van Heuven, & Grainger (in press), for further 

evidence from ERPs). These results counter the predictions of the input-switch mechanism first 

proposed by Macnamara and Kushnir (1972), according to which the words of the bilingual’s 

two languages are kept apart (in separate stores) and the incoming sensory input is directed to 

the appropriate set of words as a function of context. 

The non-selective access/integrated lexicon view of how languages are represented in the 

bilingual mind would appear to predict that L2 words should be processed much in the same 

way as L1 words. Therefore, according to this account, words in a second language learner’s L2 

should behave like low-frequency words in the L1. This therefore contrasts with the predictions 

of the RHM (Kroll & Stewart, 1994) that assigns very different mechanisms for processing 

words in L2 compared with L1. Of course, behavioral results show that performance in L2 is 

slower and less accurate than performance in L1, but this could be attributed to the frequency 

characteristics of the words in each language. Exposure to L2 words is generally much lower 

than exposure to words in L1, especially for beginning bilinguals. Therefore L2 words will have 

lower subjective frequencies than L1 words, and these differences in subjective frequency could 

be driving the behavioral effects. Furthermore, L2 words are learned after the majority of L1 

words have already been learned, so age-of-acquisition (AoA) could be another factor driving 

observed differences in performance to L1 and L2 words. Finally, L2 words might be less 

interconnected to other L2 words (e.g., have smaller orthographic neighborhoods) than L1 

words and these differences might also account for differences in performance. 

Therefore, one key question that emerges from the above review of the behavioral literature 

on word recognition in bilinguals is whether L2 words show any processing specificities 

compared with L1 words that are quantitatively or qualitatively different than those attributable 

to subjective frequency, AoA or neighborhood density. In order to address this issue, the present 

study compared ERPs to words in L1 and L2 in lists that are blocked by language, hence 

avoiding issues of predictability and language-switching (see Chauncey, Grainger, & Holcomb, 

2008, for a recent ERP study of language-switching). A number of previous studies have 

presented words in participants’ L1 and L2 and compared various ERP effects such as priming 

or anomaly detection between languages (e.g., De Bruijn, Dijkstra, Chwilla, & Schriefers, 

2001; Hahne & Friederici, 2001; Kerkhofs, Dijkstra, Chwilla, & de Bruijn, 2006; Kotz, 2001; 

Kotz & Elston-Guttler, 2004; Moreno & Kutas, 2005; Phillips, Klein, Mercier, & de Boysson, 

2006; Phillips, Segalowitz, O’Brien, & Yamasaki, 2004; Weber-Fox & Neville, 1996). 

Surprisingly though, none of these studies has systematically compared ERPs to words in L1 

and L2. ERPs would appear to be ideally suited for discerning word level differences between 

languages, both because of their excellent temporal resolution as well as their ability to 

differentiate multiple sensory and cognitive influences in a single experiment. 

There are also comparatively few ERP studies that have examined second language learners 

in the process of formal classroom instruction. One notable exception is a study by 

McLaughlin, Osterhout, and Kim (2004). These authors showed that the N400 component to 

visually presented items in L2 (French) differentiated between words and pseudowords after 

only a very brief period of L2 learning (14 h) though semantic priming effects were not 

observed at this point in L2 learning. This result suggests that ERPs are sensitive to lexical 

representations laid down in the very initial phases of L2 learning. McLaughlin et al. did not 

report direct comparisons between L2 and L1, but a study by Alvarez, Grainger, and Holcomb 

(2003) did directly compare ERPs recorded to Spanish (L2) and English (L1) words in native 

English speakers enrolled in intermediate university Spanish classes. The finding of most 




interest here was that starting as early as 150 ms and continuing on as late as 700 ms there were 

differences in the time course of ERP effects between L1 and L2. However, because their 

design included a repetition factor and all of their reported effects of language interacted with 

this factor, it is not clear whether there were pure differences between languages when 

participants read words in each language for the first time (i.e., prior to a repetition). Examination 

of their Figs. 2 and 3 does, however, suggest that L1 words produced somewhat larger 

N400s than L2 words. 

In the current study we examined differences in the ERPs generated by L1 and L2 words for 

American students of French (Experiment 1), French students of English (Experiment 2) and 

proficient FrencheEnglish bilinguals (Experiment 3). Table 1 summarizes the different level of 

expertise in L1 and L2 of these three groups of participants. 

1. Experiment 1 e learners of French 


+ MODEL 


In this experiment ERP language effects for L1 and L2 items were measured during 

a passive reading for meaning task. Participants were native speakers of American English 

selected from beginning and intermediate French courses at university and none had had 

a significant immersion experience. To better match these participants to the native French 

participants learning English in Experiment 2, an additional criterion for selection was 

a relatively early (by US educational standards) and ongoing exposure to French. 

1.1. Methods 

1.1.1. Participants 

Twenty-two participants from Tufts University (17 female, mean age ¼ 19.8, SD ¼ 1.7) who 

were enrolled in French courses were paid for their participation. All were right handed (Edinburgh 

Handedness Inventory e Oldfield, 1971) and had normal or corrected-to-normal visual acuity with 

no history of neurological insult or language disability. English was reported to be the first language 

learned by all participants (L1) and French their primary second language (L2). Participants began 

their study of French on average at the age of 12.1 years (range 5e18 years, SD ¼ 2.5). 

Fig. 2. A critical trial in the L1 block. 





+ MODEL 


5 

Fig. 3. Electrode montage and electrode analysis sites (connected by lines). 

Participants’ auto-evaluation of English and French language skills were surveyed by 

questionnaire. On a seven-point Likert scale (1 ¼ unable; 7 ¼ expert) participants reported their 

abilities to read, speak and comprehend English and French as well as how frequently they read 

in both languages (1 ¼ rarely; 7 ¼ very frequently). The overall average of self-reported 

language skills in English was 7.0 (SD ¼ 0.0) and in French was 4.2 (SD ¼ 0.9). Our participants 

reported their average frequency of reading in English as 6.4 (SD ¼ 0.9) and in French as 

3.6 (SD ¼ 1.1). See Table 1 for a comparison of participants across the 3 experiments. 

1.1.2. Stimuli 

The critical stimuli for this experiment were 80 four to seven letter non-cognate morphemically 

simple English words and their translations into French. The English items had a mean 

Table 1 

Average self-evaluation on a seven-point scale of overall language skills and reading frequency of the three groups of 

participants in Experiments 1e3 

Experiment 1 Experiment 2 Experiment 3 

L1 e E L2 e F L1 e F L2 e E L1 e F L2 e E 

Language skills 7.0 (0.0) 4.2 (0.9) 6.8 (0.4) 3.9 (1.1) 6.9 (0.3) 5.7 (1.0) 

Reading 6.4 (0.9) 3.6 (1.1) 6.4 (1.2) 2.7 (1.3) 6.3 (1.1) 5.8 (1.5) 





+ MODEL 


log frequency (CELEX, 1993) of 1.73 (SD ¼ 0.63, range 0.00e3.09). The French items had 

a mean log frequency (New, Pallier, Ferrand, & Matos, 2001) of 1.63 (SD ¼ 0.53, range 0.24e 

2.65). The log frequencies of the items in the two languages were not found to be statistically 

different (t(79) ¼ 1.16, p ¼ 0.25). The log frequencies of the translation equivalents correlated 

highly (r ¼ 0.71, p < 0.01). The average length of the English items was 4.7 letters (SD ¼ 0.97) 

while the average length of the French items was 5.5 (SD ¼ 1.09). 

Forty animal names were selected as probe items and an additional 200 non-critical words 

were used as fillers for each language block. These non-critical items and the probe items were, 

like the critical items, four to seven letters in length (mean length: 5.5 letters for English items 

(SD ¼ 1.00), 5.8 letters for French items (SD ¼ 0.99)). These items had slightly lower log 

frequencies than the critical items (average log frequency for English items: 1.23 (SD ¼ 0.52), 

French: 1.17 (SD ¼ 0.50)). 

The 80 English items were divided into two lists of 40 items and each participant saw one of 

the two lists. The same was done with the French items such that there was no repetition of 

translation equivalents. That is if a participant saw ‘‘tree’’ in the English block they would not 

see ‘‘arbre’’ in the French block. Both an English block and a French block were presented to 

each participant in a counterbalanced fashion across participants. The two blocks were thus 

comprised of 40 animal probes, 40 critical items and 200 fillers. All items in a block were in 

one language and there was no repetition of translation equivalents across blocks. 

1.1.3. Procedure 

Animal names served as probe items in a go/no-go semantic categorization task in which 

participants were instructed to rapidly press a single button whenever they detected an animal 

name. Participants were told to read all other words passively without responding (i.e., critical 

stimuli did not require an overt response). Stimulus lists were a pseudorandom mixture of 

critical trials, fillers and probe trails. A practice session was administered before the main 

experiment to familiarize the participant with the task. 

The visual stimuli were presented on a 19 00 monitor located directly in front of the participant 

at a distance of approximately 150 cm. Stimuli were displayed at high contrast as white 

letters on a black background in the Verdana font (letter matrix 20 pixels wide 40 pixels tall). 

Each trial began with a fixation cross followed by a blank screen and then an item. The item 

was on screen for 300 ms, followed by 1000 ms of blank screen and then a 2500 ms blink 

symbol (see Fig. 2). The participants were instructed to blink only during this blink symbol. 

This symbol was followed by 500 ms of blank screen after which the next trial began with 

a fixation cross. 

1.1.4. EEG recording procedure 

Participants were seated in a comfortable chair in a sound attenuated darkened room. The 

electroencephalogram (EEG) was recorded from 29 active tin electrodes held in place on the 

scalp by an elastic cap (Electrode-Cap International e see Fig. 3). In addition to the 2 scalp 

sites, additional electrodes were attached to below the left eye (LE, to monitor for vertical eye 

movement/blinks), to the right of the right eye (VE, to monitor for horizontal eye movements), 

over the left mastoid bone (A1, reference) and over the right mastoid bone (recorded actively to 

monitor for differential mastoid activity). All EEG electrode impedances were maintained 

below 5 kU (impedance for eye electrodes was less than 10 kU and for the references electrodes 

less than 2 kU). The EEG was amplified by an SA Bioamplifier with a bandpass of 0.01 and 

40 Hz and the EEG was continuously sampled at a rate of 200 Hz throughout the experiment. 





+ MODEL 


7 

1.1.5. Data analysis 

Averaged ERPs were formed off-line from trials free of ocular and muscular artifact (9% of 

trials rejected for artifact) and were lowpass filtered at 15 Hz. The approach to data analysis 

involved the selection of a subset of the 29 scalp sites (see Fig. 3). Average waveforms were 

formed for the two levels of LANGUAGE (L1 vs. L2), three levels of POSTERIOReANTERIOR 

(posterior, central and anterior) and three levels of LATERALITY (right, midline and left). The 

main analysis approach involved measuring mean amplitudes in three temporal epochs; 

150e300 ms, 300e500 ms, 600e800 ms capturing activity prior, during and after the typical 

N400. Separate repeated measures analyses of variance (ANOVAs) were used to analyze the 

data in each of these three epochs. 1 The Geisser and Greenhouse (1959) correction was applied 

to all repeated measures with more than one degree of freedom in the numerator. 

1.2. Results 

1.2.1. Visual inspection of ERPs 

The ERPs time locked to critical target items are plotted in Fig. 4. Plotted in Fig. 5 are the 

voltage maps resulting from subtracting L2 from L1 ERPs (these plots reveal the scalp 

distribution of differences between languages). As can be seen in Fig. 4, early in the waveforms 

there is a small negativity (sharpest at anterior sites) peaking around 100 ms (N1), this is 

followed by a prominent positivity peaking near 200 ms (P2). The P2 is visible at all sites, but is 

larger at more anterior electrodes. Up to this point the ERPs for the two languages are quite 

similar. However, starting just after the peak of the P2 there are clear differences in the ERPs 

for the two languages. These can be seen most clearly in the voltage maps in Fig. 5. At posterior 

sites there are differences on the negativity that starts at about 250 ms and which peaks at about 

400 ms (N400). Here the difference appears to be due to a prolonged attenuation of the N400 

for L2 compared to L1 items starting as early as 200 ms and lasting through 500 ms. Also 

evident is a reduction and/or delay in the negativity which peaks at about 300 ms at anterior 

sites in L1 and at about 450 ms in L2 and a subsequent larger anterior sustained negativity for 

L2 compared to L1 words. 

1.2.2. Analyses of ERP data 

1.2.2.1. 150e300 ms epoch. In this epoch there was a main effect of LANGUAGE (F(1,21) ¼ 8.56, 

p ¼ 0.008) with L1 items being more negative-going than L2 items. 

1.2.2.2. 300e500 ms epoch. In the traditional N400 epoch there were again differences between 

the languages, however, these effects differed as a function of scalp site (LANGUAGE POSTERIORe 

ANTERIOR, F(2,42) ¼ 15.75, p ¼ 0.0002; LANGUAGE LATERALITY, F(2,42) ¼ 5.76, p ¼ 0.009). 

Examination of Fig. 4 suggests that the LANGUAGE POSTERIOReANTERIOR interaction reflects that 

at anterior sites L2 items are slightly only more negative-going than L1 items, but at posterior 

sites L1 items are substantially more negative-going than L2 items. The LANGUAGE LATERALITY 

interaction indicates that L1 was quite a bit more negative than L2 at midline and right hemisphere 

sites compared to left hemisphere sites. 

1 We performed a first pass analysis including the factor of order to test for differential effects of which target 

language block occurred first for all three epochs and for all three Experiments. There were no interactions involving the 

order and language (all Fs < 2). In all of the analyses reported we collapsed across this factor. 





+ MODEL 


Fig. 4. ERP language effects from nine sites (see Fig. 3 for electrode locations) for native English speakers reading 

critical words in their L1 (English) and L2 (French) in Experiment 1. 

1.2.2.3. 600e800 ms epoch. In the final epoch there were again language effects that differed 

as a function of scalp site (LANGUAGE POSTERIOReANTERIOR, F(2,42) ¼ 11.64, p ¼ 0.001). Fig. 4 

suggests that this interaction reflects that L2 was more negative-going than L1 at anterior sites 

while at posterior sites L1 was still slightly more negative-going than L2. 

1.2.3. Behavioral data 

Participants detected on average 98.2% (SD ¼ 2.7%) of probes in the L1 block. In the L2 block 

the participants detected 78.9% of probes (SD ¼ 10.5%). Participants produced false alarms on an 

average of 0.5 items (SD ¼ 1.1) in L1 (0.2%) and on 7.6 items (SD ¼ 7.8) in L2 (3.8%). 

1.3. Discussion 

Experiment 1 tested learners of French still at a relatively early point in acquiring their 

second language. ERPs were time locked to passively read words in L1 (English) and L2 

(French). Both languages elicited a similar pattern of early ERP components. However, in the 

time frame of the N400 component there were clear effects of language dominance. At 

posterior electrode sites L1 items were associated with larger N400-like negativities starting as 

early as 200 ms and continuing on through 500 ms. At anterior sites L1 items started off more 

negative-going than L2 items (between 200 and 400 ms), but after 400 ms L2 items became 

more negative than L1 items. This latter effect suggests that the anterior negativity produced by 

words in both languages is delayed by some 150 ms in L2. 





+ MODEL 


9 

Fig. 5. Voltage maps computed by subtracting ERPs recorded to L2 words (French) from ERPs recorded from L1 words 

(English) in Experiment 1. Note that computing the subtraction in this direction (L1eL2) results in the larger early 

posterior negativity from L1 ERPs (see Fig. 4) producing a larger effect at posterior sites (blue areas at 300 and 400 ms) 

and the larger late anterior negativity from L2 ERPs (see Fig. 4) producing an effect at anterior sites (red areas at 600, 

700 and 800 ms). 

2. Experiment 2 

In Experiment 1, L2 speakers of French showed smaller posterior negativities and delayed/ 

prolonged anterior negativities to words read in their L2 compared to their L1. It seems likely 

that these effects are due to these participants less competent language status in L2, although it 

is possible that they are due entirely or in part to inherent differences between French and 

English words. Neville et al. have demonstrated that there are both similarities and differences 

in ERP effects for users of different languages (English and ASL) and that some of these effects 

can be attributed to language competence but that some effects reflect basic differences in the 

languages themselves (Neville et al., 1997; Neville, Mills, & Lawson, 1992). In order to test if 

the language effects seen in Experiment 1 are due to specific characteristics of English and 

French or reflect the different level of participants’ competence in English and French, in 

Experiment 2 we tested native speakers of French that are learners of English in a similar 

paradigm with different items. 

2.1. Methods 


Eighteen participants (14 female, mean age ¼ 22.1, SD ¼ 4.7) were recruited from the 

University of Provence and paid for their participation. All were right handed (Edinburgh 

Handedness Inventory e Oldfield, 1971) and had normal or corrected-to-normal visual acuity 

with no history of neurological insult or language disability. French was reported to be the first 

language learned by all participants (L1) and English their primary second language (L2). 




+ MODEL 


Participants began their study of English in their sixth year of primary school at approximately 

the age of 12 years, as is customary in the French school system. 

Participants’ auto-evaluation of English and French language skills were surveyed by 




language skills in French was 6.8 (SD ¼ 0.4) and in English was 3.9 (SD ¼ 1.1). Our participants 

reported their average frequency of reading in French as 6.4 (SD ¼ 1.2) and in English as 



The critical stimuli for this experiment were 74 four and five letter English words and 74 

four and five letter French words. The English items had a mean log frequency (CELEX, 1993) 

of 1.08 (SD ¼ 0.489, range 0.301e2.158). The French items had a mean log frequency (New 

et al., 2001) of 1.16 (SD ¼ 0.611, range 0.000e2.615). These log frequencies were not found to 

be statistically different (t(73) ¼ 0.654, p ¼ 0.51). The average length of the English items was 

4.34 letters (SD ¼ 0.48) while the average length of the French items was 4.43 (SD ¼ 0.50). 

The critical stimuli were morphemically simple items. Stimulus lists were formed by mixing 

the above critical items with probe words which were all members of the semantic category of 

‘‘body parts’’ (20% of trials). These probe items were, like the critical items, four and five 

letters in length (mean length: 4.5 letters (SD ¼ 0.51) for both English and French items). These 

items had slightly higher log frequencies than the critical items (average log frequency for 

English items: 1.53 (SD ¼ 0.80), French: 1.69 (SD ¼ 0.61)). 


The procedure was the same as Experiment 1. Two blocks were presented in counterbalanced 

order. In the L1 block only French items were presented and in the L2 block only 

English items were presented. 

The laboratory in France was designed to be as similar as possible to the laboratory at Tufts 

University. The same EEG recording system is used and the same software is used in Experiments 

1e3 as well as the same experimenters. 

The visual stimuli were presented on a 15 00 monitor located directly in front of the participant 

at a distance of approximately 150 cm. Stimuli were displayed at high contrast as white 

letters on a black background in the Verdana font (letter matrix 30 pixels wide 60 pixels tall). 

All else was as in Experiment 1. See Fig. 2 for a typical L2 trial. 


Data analysis was identical to Experiment 1. Trials containing ocular and muscular artifact 

were excluded from analysis (13% of trials rejected due to artifact). 

2.2. Results 




voltage maps resulting from subtracting L2 from L1. As can be seen, and similar to Experiment 1, 

early in the waveforms there is a small negativity (sharpest at anterior sites) peaking around 

100 ms (N1). This is followed by a prominent positivity peaking near 200 ms (P2). The P2 is 





+ MODEL 


11 

Fig. 6. ERP language effects from nine sites (see Fig. 2 for electrode locations) for native French speakers reading 

critical words in their L1 (French) and L2 (English) in Experiment 2. 

visible at all sites, but is larger at more anterior electrodes. Again, as in Experiment 1, up to the 

peak of the P2 the ERPs for the two languages are quite similar. However, starting near the peak of 

the P2 there are clear differences in the ERPs for the two languages. Most evident across the scalp, 

but most notable at posterior sites there are differences on the negativity starting as early as 

200 ms and peaking at about 450 ms (N400). This difference appears to be due to a prolonged 

attenuation of the N400 for L2 compared to L1 items (see the large central/posterior blue area in 

Fig. 7 between 200 and 600 ms). Another difference is a reduction in the anterior negativity in L2 

compared to L1 especially after 400 ms (the red area in Fig. 7 between 500 and 800 ms). 


2.2.2.1. 150e300 ms epoch. In this epoch there was a main effect of LANGUAGE (F(1,21) ¼ 7.42, 

p ¼ 0.014) with L1 items being more negative-going than L2 items. 

2.2.2.2. 300e500 ms epoch. In this epoch there were differences between the languages 

(F(1,17) ¼ 17.83, p ¼ 0.001) as well as an interaction between LANGUAGE POSTERIOReANTE- 

RIOR LATERALITY (F(4,68) ¼ 5.45, p ¼ 0.002). Fig. 6 suggests that this interaction reflects that 

the difference between languages (L1 more negative than L2) tended to be larger at more 

posterior and midline sites. 





+ MODEL 


Fig. 7. Voltage maps computed by subtracting ERPs recorded to L2 words (English) from ERPs recorded from L1 words 

(French) in Experiment 2. Note that as in Fig. 4 there is a large early central/posterior effect resulting from L1 ERPs 

being more negative-going (blue areas at 200, 300, 400 and 500 ms) and a large late anterior effect resulting from L2 

ERPs being more negative at anterior sites (red areas at 500, 600, 700 and 800 ms). 


as a function of scalp site (LANGUAGE POSTERIOReANTERIOR LATERALITY (F(4,68) ¼ 8.60, 

p ¼ 0.0002)). Fig. 6 suggests that at anterior sites, especially along the midline and over the 

right hemisphere, L2 was more negative-going than L1, while at posterior sites, especially 

along the midline, L1 was still more negative than L2. 


Participants detected on average 87.0% (SD ¼ 10.9%) of probes in the L1 block. In the L2 

block the participants detected 52.9% of probes (SD ¼ 21.7%). Participants produced false 

alarms on an average of 1.4 items (SD ¼ 1.1) in L1 (1.9%) and on 1.0 items (SD ¼ 1.0) in L2 

(1.4%). 


Experiment 2 tested French learners of English still at a relatively early point in acquiring 

their second language. As in Experiment 1, ERPs were time locked to passively read words but 

now French is the participants’ L1 and English their L2. Again, both languages elicited 

a similar pattern of early ERP components. Just after the peak of the P2, at the beginning of the 

time frame of the N400 component there were again effects of language dominance. At central 

and posterior electrode sites L1 items were associated with larger N400-like negativities 

starting as early as 200 ms and continuing on through 700 ms. At anterior sites L1 items started 

off more negative-going than L2 items (between 200 and 500 ms) but after 500 ms L2 items 

became more negative than L1 items especially at midline and right hemisphere sites. This 





+ MODEL 


13 

latter effect is consistent with the possibility that the anterior negativity produced by words in 

both languages is delayed by some 150 ms in L2. The overall pattern of effects in Experiments 

1 and 2 was quite similar suggesting that the observed differences in L1 and L2 are not due to 

specific attributes of either language, but rather are more general effects of language competence 

in L1 and L2. This hypothesis is further tested in Experiment 3 with more balanced 

FrencheEnglish bilinguals. 

3. Experiment 3 

In order to provide a further test of the hypothesis that the language effects obtained in 

Experiments 1 and 2 are due to different levels of proficiency in each language, Experiment 3 

tests a group of proficient FrencheEnglish bilinguals in the same paradigm as Experiment 2. 

3.1. Methods 


Twenty participants (13 female, mean age ¼ 23.0, SD ¼ 4.7) were recruited as proficient 

bilinguals and paid for their participation. All were right handed (Edinburgh Handedness 

Inventory e Oldfield, 1971) and had normal or corrected-to-normal visual acuity with no 

history of neurological insult or language disability. French was reported to be the first language 

learned by all participants (L1) and English their primary second language (L2). Participants 

began their study of English in their sixth year of primary school at approximately the age of 12 

years, as is customary in the French school system. 

Participants’ auto-evaluation of French and English language skills were surveyed by 




language skills in French was 6.9 (SD ¼ 0.3) and in English was 5.7 (SD ¼ 1.0). Our participants 

reported their average frequency of reading in French as 6.3 (SD ¼ 1.1) and in English as 


3.1.2. Stimuli and procedure 

The stimuli and procedure for this experiment were the same as in Experiment 2. 


Data analysis was identical to Experiment 1. Trials containing ocular and muscular artifact 

were excluded from analysis (7% of trials rejected). 

3.2. Results 



voltage maps resulting from subtracting L2 (English) from L1 (French) ERPs. As can be seen, 

and similar to Experiments 1 and 2, early in the waveforms there is a small negativity (sharpest 

at anterior sites) peaking around 100 ms (N1). This is followed by a prominent positivity 

peaking near 200 ms (P2). In Experiments 1 and 2 there were prominent differences between 

languages that appeared to begin just after the P2 (Figs. 4 and 6). These effects are not so 





+ MODEL 


Fig. 8. ERP language effects from nine sites (see Fig. 3 for electrode locations) for native French speakers reading 

critical words in their L1 (French) and L2 (English) in Experiment 3. 

apparent in Experiment 3 (Fig. 8). Still evident, however, is the delay in the anterior negativity 

which peaks after 350 ms at the frontal sites in L1 and just after 450 ms in L2. Moreover, this 

negativity appears to now be larger in L2 than L1. Another difference between the ERPs in 

Experiment 3 and those in Experiments 1 and 2 is that in Experiment 3 there are no longer large 

differences on the negativity that peaks between 400 and 500 ms (N400) at posterior sites. Here 

the peak of the negativity is roughly equivalent for the two languages. It is only in the epoch 

following the N400 where there are small differences between languages (L2 more negative 

than L1). 


3.2.2.1. 150e300 ms epoch. Consistent with the visual observation of Fig. 8 there were no 

significant effects of LANGUAGE in this epoch. 

3.2.2.2. 300e500 ms epoch. In this epoch there were differences between the languages as 

a function of scalp site (LANGUAGE POSTERIOReANTERIOR (F(2,38) ¼ 5.21, p ¼ 0.022)). Examination 

of Fig. 8 suggests that this interaction was sensitive to the difference between languages 

from the front to the back of the head. 


as a function of scalp site (LANGUAGE LATERALITY (F(2,38) ¼ 4.20, p ¼ 0.031)). Fig. 8 suggests 

that differences between the languages were greater over midline and right hemisphere sites. 





+ MODEL 


15 

Fig. 9. Voltage maps computed by subtracting ERPs recorded to L2 words (English) from ERPs recorded from L1 words 

(French) in Experiment 3. Note that the early posterior is much smaller than in Figs. 5 and 7 reflecting the fact that L1 

ERPs are only slightly more negative-going than L2 ERPs (pale blue area at 400 ms), but that there is still a large late 

anterior effect resulting from L2 ERPs being more negative at anterior sites (red areas at 500, 600, 700 and 800 ms). 


Participants detected on average 92.8% (SD ¼ 5.7%) of probes in the L1 block. In the L2 block 

the participants detected 93.0% of probes (SD ¼ 10.7%). Participants produced false alarms on an 

average of 1.8 items (SD ¼ 1.1) in L1 (2.4%) and on 2.2 items (SD ¼ 3.9) in L2 (2.9%). 


This experiment examined proficient bilinguals in both their L1 (French) and L2 (English). 

As in Experiments 1 and 2, ERPs were time locked to passively read words in both languages. 

Both languages elicited a similar pattern of early ERP components and this similarity in early 

effects extended through 300 ms. It was not until the middle portion of the N400 (around 

350 ms) that the somewhat larger posterior N400 for L1 items could be seen in this Experiment. 

At anterior sites the negativity which peaked around 350 ms for L1 was clearly delayed in L2, 

peaking around 50e100 ms later. Also the late negativity that follows the N400 especially at 

anterior sites was larger in L2 than in L1. However, the latency shift in anterior N400 was 

certainly smaller than seen in the less proficient participants of Experiments 1 and 2. 

4. General discussion 

Across three experiments we compared ERPs to words passively read for meaning in bilingual 

participants who were comparatively late learners of their L2 (after age 12). In Experiment 1, 

participants were native speakers of English (L1 English) and were in the process of learning 





+ MODEL 


French (L2). In Experiment 2 participants were native speakers of French (L1 French) and were in 

the process of learning English (L2). In Experiment 3 participants were again native speakers of 

French (L1 French) but were also competent speakers of English (L2). 

In all three experiments words in L1 and L2 produced a series of early ERP components (N1 

and P2) prior to 200 ms that were quite similar in morphology (shape) scalp distribution and 

amplitude (see Figs. 4, 6 and 8). This is not surprising because these early exogenous ERP 

components are believed to reflect sensory and perceptual characteristics of the eliciting 

stimulus (Luck, 2005) and in the current study we carefully matched these characteristics 

across the words used in the two languages (e.g., no French words with accents were used). 

The most prominent feature of ERPs to passively read content words after 200 ms is the 

N400 (Osterhout & Holcomb, 1995). The N400 in single word paradigms is believed to be 

sensitive to word processing as early as the word-form/meaning interface (e.g., Holcomb, 

O’Rourke, & Grainger, 2002) and therefore is likely to be the first ERP component that would 

carry any language effects in a passive reading paradigm. As expected words presented in L1 

were associated with a large broadly distributed N400, and this was true for both English and 

French L1 speakers. Turning first to the two less competent L2 groups (Experiment 1 and 2), 

perhaps most notable is the observation that both experiments produced a very similar pattern 

of L1eL2 ERP effects. Because the language of L1 and L2 were reversed across the experiments, 

this suggests that language-specific differences were not at the root of the effects 

observed. In both experiments the L2 N400 was attenuated relative to L1 especially at centroposterior 

sites. However, at anterior sites while the N400 started out smaller in L2 than L1, this 

difference appeared to be due in part to the anterior N400 being somewhat delayed in L2 

compared to L1. In fact, looking at the epoch just after the traditional N400 at anterior sites, L2 

words are more negative-going than L1 words and this difference continued all the way to the 

end of the recording epoch. Moreno et al (2005) also found delayed N400s as well as 

a posterior N400 negativity in competent L2 speakers in a sentence reading task. They found 

that this late negativity was also associated with language dominance, with ERPs to the less 

dominant language having the larger late negativity. 

Experiment 3 examined the impact of L2 proficiency level on these language differences by 

testing participants with roughly comparable proficiency in their L1 and L2 (in Experiments 1 

and 2 participants were significantly less competent in L2), but who had began learning their L2 

at a similarly late age. In this experiment the difference between L1 and L2 in centro-posterior 

N400 amplitude that was seen previously in Experiments 1 and 2 was virtually non-existent. 

The L2 words in Experiment 3 generated a centro-posterior N400 of similar size to words in L1. 

This pattern of similar N400 amplitude for L1 and L2 has been reported in previous studies of 

competent L2 speakers in other language paradigms (e.g., Moreno et al., 2005; Neville et al., 

1992) and is consistent with the hypothesis that the posterior N400 effect reflects competence in 

L2, less competent users producing smaller N400s. The anterior N400 latency shift seen clearly 

in Experiments 1 and 2 was still evident in Experiment 3, but the latency difference was much 

smaller. This would suggest that the anterior N400 latency shift reflects competence in L2, but 

contrary to the posterior N400 effect continues to reflect differences in L1 and L2 processing 

even in relatively proficient bilinguals. 

These large differences in the ERPs generated by words in L1 and L2 and their modulation 

by proficiency in L2 are in line with the hypothesis that word recognition in L2 involves distinct 

mechanisms compared with the first language, at least in the relatively early phases of L2 

acquisition in late learners of L2. One specific model, the RHM (Kroll & Stewart, 1994), 

predicted such differences in L1 and L2 word recognition over and above possible differences 





+ MODEL 


17 

due to subjective frequency, AoA, and other correlated factors. In the RHM, it is the process of 

translation from an L2 word-form to its equivalent in L1 that is the key distinguishing characteristic 

of L2 vocabulary acquisition in beginning bilinguals. That is, word recognition in L2 

is achieved mainly by translation of the L2 word-form into its equivalent word-form in L1, 

which then leads to the appropriate semantic activation. The delayed anterior N400 latency to 

L2 words might well reflect this specific process of L2 word recognition, that is inevitably 

delayed compared with L1 word recognition for which the translation route is non-dominant 

(see Fig. 1). The fact that an albeit smaller latency shift was still observed in the proficient 

bilinguals of Experiment 3 suggests that the translation route is still operational in these 

participants, but to as lesser degree. 

Do these results therefore force us to reject an integrated lexicon account of bilingual lexical 

representation, such as implemented in the bilingual interactive-activation model (BIA-model, 

Grainger & Dijkstra, 1992; van Heuven et al., 1998)? One way of saving the BIA-model is to 

assume that it better reflects processing in relatively proficient bilinguals, while the RHM is a better 

model of lexical processing in beginning bilinguals. The idea would be that during L2 acquisition, 

the L2eL1 translation route of the RHM would be gradually replaced by L2 lexical representations 

that become part of an integrated network along with L1 representations. This could be achieved by 

gradually weakening the L2eL1 connections between translation equivalents, and gradually 

strengthening the connections between L2 word-forms and semantics. Thus as proficiency 

develops in L2, lexical processing in L2 becomes more and more akin to lexical processing in L1. 

But why is the posterior N400 smaller for L2 items in less competent speakers? Indeed, one 

might have expected a greater N400 amplitude to L2 words compared with L1 words, given 

that N400 amplitude is often associated with processing effort or cost. One possibility is that in 

less competent speakers exposure to L2 words is generally much lower than exposure to words 

in L1. Therefore L2 words will have lower subjective frequencies than L1 words. Differences in 

subjective frequency could be the source of the smaller posterior N400 for L2 items. However, 

the effects of word frequency on the N400 have typically been reported to be just the opposite 

of those obtained here (i.e., larger N400s for less frequent words e Van Petten & Kutas, 1990), 

so a mechanism like subjective word frequency is an unlikely source. 

Another possible explanation for these effects is that they reflect differential activity in 

a mechanism similar to the age-of-acquisition effect for words in L1. That is, that words 

acquired younger in life are afforded some special privilege (Zevin & Seidenberg, 2004). 

Plotted in Fig. 10 are ERPs recorded to words in the same passive reading paradigm of the 

current study in adult monolingual speakers of English. These waves have been segregated 

according to whether they were learned before or after the age of eight years. As can be seen, 

the very small effects seen at anterior sites for the two word categories are in the opposite 

direction to those predicted by the late negative effects seen for words in L2 in Figs. 4, 6 and 8. 

So AoA appears to be an unlikely source of the posterior N400 language effect. 

Finally, another possibility is that L2 words, especially in a less competent speaker may be 

less interconnected to other L2 words e that is, on average, they would tend to have smaller 

orthographic neighborhoods. At least one previous study has shown that words from dense 

orthographic neighborhoods have larger N400s than words from sparse neighborhoods 

(Holcomb et al., 2002). Therefore, the larger posterior N400 amplitude to L1 words might be 

a reflection of the greater number of other words that are co-activated during target word 

recognition. A similar argument could be made at the level of semantic representations, with 

the semantic representations of L1 words being more richly interconnected within the semantic 

network than L2 words. Such an analysis would fit with one account of the effects of 





+ MODEL 


Fig. 10. ERPs in the same passive reading task and at the same 9 scalp sites as the current study. ERPs are based on 250 

words divided at the median on age-of-acquisition ratings. 

concreteness on N400 amplitude (concrete words generate larger N400 amplitudes than abstract 

words, e.g., Kounios & Holcomb, 1994) according to which this would be due to the greater 

semantic interconnectivity for concrete words. 

5. Conclusions 

The present study provides evidence that the processing of L1 and L2 words in late L2 

learners diverge in two distinct ways as reflected in the ERP waveforms generated by these 

words during silent reading for meaning. An anterior part of the N400 component showed 

a distinct latency shift with L2 amplitudes peaking later than L1 amplitudes, and although the 

latency shift was still present in proficient bilinguals, it was smaller in magnitude. This 

latency shift might well reflect differences in processing difficulty associated with words in L1 

and L2. The posterior part of the N400 revealed larger amplitudes to L1 compared with L2 

words in our low-proficiency participants, and very little difference in the proficient 

bilinguals. It is suggested that these amplitude differences might reflect a lower level of 

interconnectivity of L2 lexical and semantic representations in beginning bilinguals, that 

disappears with increasing competence in L2 and greater integration of L2 words in 

a common lexical-semantic network. 

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+ MODEL 


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Voisinage orthographique inter-langues 

Chapitre 3 

Une investigation électrophysiologique 

des effets de voisinage orthographique inter-langues* 

Au cours d'une expérience où des sujets bilingues français-anglais lisaient des listes de 

mots anglais et français, des potentiels évoqués ont été enregistrés. Les mots se 

distinguaient en termes de nombre de voisins orthographiques qu'ils possèdent dans 

l'autre langue ; peu ou beaucoup. C'est le nombre de voisins français pour des mots cibles 

anglais et vice-versa qui est manipulé. Les résultats ont montré des effets de taille de 

voisinage inter-langue sur la composante ERP N400. Celle-ci survenait plus précocement 

et se distribuait plus largement pour des mots cibles anglais (L2) que pour des mots cibles 

français (L1). Dans une expérience contrôle destinée à démontrer que ces effets n'étaient 

dus à aucun facteur parasite, des participants monolingues anglais ne lisaient que la liste 

des mots cibles anglais variant par le nombre de voisins français (langue inconnue d'eux). 

Ces sujets ont produit un pattern d'effets totalement différent de celui des bilingues. Ces 

résultats témoignent de la perméabilité inter-langue impliquée dans la reconnaissance des 

mots dans un contexte bilingue, phénomène dont la prédiction et la simulation sont 

correctement prises en charge par le modèle BIA+ (Modèle d'Activation Interactive 

Bilingue, version plus). 

Mots-clefs : potentiels évoqués, bilinguisme, voisinage orthographique, N400 

________________________ 

* Article in Brain Research vol. 1246, pp. 123-135, December 2008 

P | 55

BRAIN RESEARCH 1246 (2008) 123– 135 

available at www.sciencedirect.com 

www.elsevier.com/locate/brainres 

Research Report 

An electrophysiological investigation of cross-language effects 

of orthographic neighborhood 

Katherine J. Midgley a,b, ⁎, Phillip J. Holcomb a , Walter J.B. vanHeuven c , Jonathan Grainger b 

a Tufts University, Medford, MA, USA 

b CNRS and University of Provence, Marseille, France 

c University of Nottingham, Nottingham, UK 

ARTICLE INFO 

Article history: 

Accepted 17 September 2008 

Available online 9 October 2008 

Keywords: 

ERP 

Bilingualism 

Orthographic neighborhood 

N400 

ABSTRACT 

In Experiment 1 ERPs were recorded while French–English bilinguals read pure language lists 

of French and English words that differed in terms of the number of orthographic neighbors 

(many or few) they had in the other language. That is the number of French neighbors for 

English target words was varied and the number of English neighbors for French target words 

was varied. These participants showed effects of cross-language neighborhood size in the 

N400 ERP component that arose earlier and were more widely distributed for English (L2) 

target words than French (L1) targets. In a control experiment that served to demonstrate 

that these effects were not due to any other uncontrolled for item effects, monolingual L1 

English participants read only the list of English targets that varied in the number of French 

(an unknown L) neighbors. These participants showed a very different pattern of effects of 

cross-language neighbors. These results provide further crucial evidence showing crosslanguage 

permeability in bilingual word recognition, a phenomena that was predicted and 

correctly simulated by the bilingual interactive-activation model (BIA+). 

© 2008 Elsevier B.V. All rights reserved. 

1. Introduction 

A long-standing debate in the literature on bilingual language 

comprehension concerns the relative permeability of the 

representations dedicated to processing each language. Traditionally, 

this debate has opposed proponents of early languageselective 

processing with proponents of a non-selective access 

to a set of representations shared by both languages. The 

language-selective hypothesis is typically associated with the 

notion of a switching mechanism that guides the linguistic 

input to the appropriate set of language-specific lexical representations 

(Macnamara, 1967). According to this hypothesis, 

there should be no cross-language interference when the 

language of the incoming information is completely predictable 

(i.e., in a monolingual context). When this is the case, information 

extracted from the stimulus is sent directly to the 

appropriate set of language-specific representations. 

The non-selective access hypothesis proposes, on the other 

hand, that the initial feed-forward sweep of information from 

the linguistic input can make contact with lexical representations 

from both languages as a function of their orthographic 

or phonological overlap with the input. This is the central 

hypothesis of the Bilingual Interactive-Activation model 

(Grainger & Dijkstra, 1992; van Heuven et al., 1998), and its 

successor the BIA+ model (Dijkstra & van Heuven, 2002). As a 

consequence, word representations from both languages are 

activated and they compete with each other due to lateral 

inhibition at the word level. Therefore the model predicts not 

⁎ Corresponding author. Tufts University, 490 Boston Avenue, Medford, MA 02155, USA. Fax: +1 617 627 3181. 

E-mail address: kj.midgley@tufts.edu (K.J. Midgley). 

0006-8993/$ – see front matter © 2008 Elsevier B.V. All rights reserved. 

doi:10.1016/j.brainres.2008.09.078

124 BRAIN RESEARCH 1246 (2008) 123– 135 

only within-language interference but also cross-language 

interference effects. 

Evidence in favor of language-selective access to languagespecific 

representations, was first provided by language 

switching experiments (Macnamara & Kushnir, 1972; Soares 

& Grosjean, 1984; Beavillain & Grainger, 1987; Thomas & 

Allport, 2000; Alvarez et al., 2003). All of these studies have 

shown that switching languages incurs a processing cost 

compared to a situation where there is no language switch. 

Thus, for example, in Grainger's and Beauvillain's (1987) study, 

lexical decision responses to words in one language were 

slower when the word on the preceding trial was from the 

other language compared with a word from the same 

language. Although switch costs have traditionally been 

taken as evidence for language-selective access, Grainger 

and Dijkstra (1992) provided an interpretation within the 

framework of a non-selective access model. Language switch 

costs are therefore not necessarily diagnostic of languageselective 

access. 

Evidence in favor of non-selective access to a common set 

of representations was provided by experiments demonstrating 

cross-language interference using bilingual versions of the 

Stroop task (Dyer, 1973), the flanker task (Guttentag et al., 

1984), experiments showing evidence for co-activation of nontarget 

language representations during the processing of 

cross-language homographs (Beauvillain & Grainger, 1987; 

De Groot et al., 2000; Dijkstra et al., 1999, 2000; Jared & Szucs, 

2002; van Heuven et al., 2008) and cross-language homophones 

(Brysbaert et al., 1999; Nas, 1983; Dijkstra et al., 1999), 

and experiments showing differential processing of cognate 

words compared with non-cognate words (e.g., de Groot & 

Nas, 1991; van Hell & de Groot, 1998; van Hell & Dijskstra, 

2002). These cross-language influences have generally been 

interpreted as showing that bilinguals cannot block interference 

from the irrelevant language. However, proponents of 

selective access have argued that the mere presence of words 

in the irrelevant language (as is the case in Stroop and Flanker 

interference experiments) is enough to prevent processing in a 

pure “monolingual” mode (e.g., Grosjean, 1988). The same 

critique can be leveled against research examining processing 

of cross-language homographs, homophones, and identical 

cognates, since these stimuli are also words in the other 

language. In order to provide more convincing evidence in 

favor of non-selective access, cross-language interference 

must be demonstrated in conditions where there is no explicit 

activation of the irrelevant language. 

These conditions were respected in two studies, one 

investigating spoken word recognition (Marian & Spivey, 

2003), and the other investigating visual word recognition 

(van Heuven et al., 1998). Critically, and contrary to all prior 

research, these studies did not explicitly manipulate the 

presence or absence of other language stimuli. Rather, they 

manipulated the presence of potential cross-language interference 

in the form of phonologically or orthographically 

similar words from the other language. To do so, Marian and 

Spivey (2003) applied the visual world paradigm (see Tanenhaus 

et al., 2000, for a description of this technique). In one 

version of this paradigm, participants are requested to pick up 

one of four objects placed in front of them. The instructions 

are delivered auditorily (e.g., “pick up the candle”) and eye 

movements are recorded. The standard finding is that a 

significant proportion of eye movements are made to objects 

whose name is phonologically similar to the target (e.g., 

“candy”), suggesting at least partial access to the distracter's 

lexical representation during target word processing. In 

Marian and Spivey's (2003) study, the phonological similarity 

of targets and distracters was manipulated within and 

between languages in bilingual participants. As well as the 

standard within-language effect, they also found a significant 

percentage of eye movements to distracter objects in the 

cross-language condition, but only for targets in L2. Thus, in 

the absence of any overt presentation of L1 words, comprehension 

of words in L2 would appear to be influenced by 

implicit activation of phonologically similar L1 words. 

Most relevant for the present study is van Heuven et al.'s 

(1998) investigation of cross-language neighborhood effects in 

bilinguals (applying Coltheart et al., 1977, definition of an 

orthographic neighbor). Prior work has shown that withinlanguage 

manipulations of this variable significantly affects 

performance in standard word recognition tasks (e.g., 

Andrews, 1989; Carreiras et al., 1997; Grainger, 1990; Grainger 

et al., 1989). Van Heuven et al. (1998) found a significant effect 

of number of orthographic neighbors both within languages 

and across languages in bilingual participants (see also 

Grainger & Dijkstra, 1992). Most important, the crosslanguage 

neighborhood effects disappeared in an experiment 

testing monolingual participants with the same materials. 

Therefore, as predicted by the BIA model, the cross-language 

neighborhood effect found in bilingual participants suggests 

that the processing of a given word (among a list of words 

from one language only) generates activation in orthographically 

similar words not only within that language but also in 

the other language. 

There is, however, some variability in the effects of 

orthographic neighborhood reported in monolingual studies 

using behavioral measures, with some studies showing 

facilitatory effects (i.e., faster responses and/or lower error 

rates to words with large numbers of neighbors compared 

with words with few neighbors), and others showing inhibitory 

effects (see Andrews, 1997; Grainger & Jacobs, 1996, for 

review and discussion of possible mechanisms). These 

discrepancies in prior behavioral research were the primary 

motivation for Holcomb et al. (2002) study. These authors 

investigated the effects of orthographic neighborhood density 

in English using event-related potentials (ERPs). In one 

experiment, participants had to read words presented in 

isolation and press a response button whenever they saw an 

animal name (randomly appearing in 19.5% of trials). The 

amplitude of the N400 ERP component, a negative going 

waveform that peaks around 400 ms post-target onset, was 

found to vary significantly with the neighborhood density of 

target words. Words with large numbers of orthographic 

neighbors generated greater N400 amplitudes (i.e., more 

negative-going waveforms in the 300–500 ms time window). 

Most critically, and unlike prior behavioral findings, these 

effects of orthographic neighbor on ERP amplitudes did not 

depend on the task that participants had to perform (semantic 

categorization or lexical decision). 

One ERP study has examined neighborhood effects in 

bilingual participants. Rüschemeyer et al. (2008) examined


125 

the effects of phonological neighborhood during L2 processing. 

They found ERP effects in the same direction as Holcomb 

et al. (i.e., items from larger neighborhoods elicit greater N400 

amplitudes). 

Holcomb and Grainger (2007) have proposed a tentative 

mapping of ERP components onto underlying processes 

involved in visual word recognition, couched with the framework 

of a generic interactive-activation model. Based primarily 

from evidence obtained with the masked priming 

paradigm, these authors suggested that much of the mapping 

of form onto meaning arises as early as 200 ms post-target 

onset (the beginning of the N250 component found in masked 

priming) and culminating in the N400. This processing would 

initially involve the mapping of prelexical form representations 

onto whole-word representations, with the N400 reflecting 

the mapping of whole-word form representations onto 

semantics. In the interactive-activation framework adopted 

by Holcomb and Grainger (2007), competition between wholeword 

form representations is thought to be the primary cause 

of inhibitory effects of orthographic and phonological neighbors. 

Thus the greater negativity to words with many 

orthographic neighbors reported by Holcomb et al. (2002), 

would reflect inhibition operating across lexical representations 

leading to increased difficulty in settling on a unique 

form-meaning association. The bilingual version of interactive-activation 

(the BIA model and its successor the BIA+ 

model) predicts similar effects of cross-language neighbors 

due to lexical competition operating within an integrated 

lexicon of word forms from both languages. 

1.1. Experiment 1 

The present study provides a further investigation of crosslanguage 

neighborhood effects using ERP recordings. We 

combine the basic manipulation of cross-language neighborhood 

in the van Heuven et al. (1998) study with the procedure 

used in the Holcomb et al. (2002) study. In Experiment 1 

bilingual participants saw pure lists of French and English 

words that varied in terms of the number of orthographic 

neighbors in the other language (many or few). Given the 

number of items per condition required for an ERP study we 

did not manipulate within-language neighborhood, although 

this was equated (see Holcomb et al., 2002, for a withinlanguage 

ERP investigation of neighborhood effects). The 

participants tested in Experiment 1 were L1 French and had 

a relatively high level of proficiency in their L2 (English). They 

were tested in an L1 context, that is, in France although these 

participants reported using their L2 on a daily basis for work 

or study. On the basis of the non-selective access hypothesis 

and prior ERP effects of neighborhood density found in 

monolinguals, it was predicted that the N400 would be 

sensitive to the number of neighbors in the non-presented 

language, with larger amplitudes for items with many otherlanguage 

neighbors compared with items with few otherlanguage 

neighbors. 


Although within language neighborhood size was carefully 

controlled in Experiment 1, our words with many and few 

neighbors could differ by chance on some other withinlanguage 

dimension. In order to be absolutely sure that it is 

non-target language activation that is driving the crosslanguage 

neighborhood effects, it is important to show that 

these effects are not a result of some other uncontrolled for 

property of the words. Monolingual L1 English participants 

with no or little exposure to French as an L2 should show no 

effect of French orthographic neighborhood size during the 

processing of L1 (English) target words. If, on the other hand, it 

is an uncontrolled L1 variable that is driving the effect, then 

the results should resemble the pattern found in the bilingual 

participants tested with English words in Experiment 1. This 

prediction was tested in Experiment 2. 

1.3. Simulation study 

Finally, a simulation study was run on the BIA+ model 

(Dijkstra & van Heuven, 2002). The model was tested with 

exactly the same stimuli as used in Experiments 1 and 2 in 

order to evaluate its ability to account for the precise pattern of 

cross-language neighborhood effects found in the present 

experiments. 

2. Results 

2.1. Experiment 1 results 


The ERP grand mean waveforms for English targets for 12 scalp 

sites are plotted in Fig. 1A while the grand mean waveforms 

for French targets are plotted in Fig. 2A. Figs. 1B (L2) and 2B (L1) 

contain voltage maps computed by subtracting ERPs for items 

with few cross-language neighbors from ERPs for items with 

many cross-language neighbors. We included these to better 

visualize the scalp distribution of neighborhood size effects at 

three points in time. The first includes voltages at the center of 

the early analysis window (275 ms), while the second and third 

are centered at early (350 ms) and later (450 ms) in the N400 

window. As can be seen in these figures, for all ERPs anterior to 

the occipital sites the first visible component was a negativegoing 

deflection between 90 and 150 ms after stimulus onset 

(N1). This was followed by a positive deflection occurring at 

approximately 200 ms (P2). A negativity followed the P2 

peaking around 400 ms (N400). At occipital sites the first 

observable component is the P1, which peaked near 100 ms 

and was followed by the N1 at 190 ms and a broad P2 between 

250 and 300 ms. The P2 was followed by the N400 between 400 

and 600 ms. 


2.1.2.1. 175–275 ms epoch. As can be seen in Fig. 1 

differences due to cross-neighborhood-size began to emerge 

in this epoch. The omnibus ANOVA on the mean amplitude 

values revealed a marginal main effect of cross-neighborhood-size 

(F(1,19)=3.78, p=.067), and a significant language by 

cross-neighborhood-size interaction (F(1,19)=4.41, p=.049), 

the latter indicating a difference in the cross-neighborhoodsize 

effect for the two languages.


Fig. 1 – (A) Results of bilinguals reading English (L2) targets with either many orthographic neighbors in French (L1) or few 

orthographic neighbors in French. (B) Scalp voltage maps at three time points between English words with few French 

neighbors and many French neighbors (units are in microvolts).


127 

Fig. 2 – (A) Results of bilinguals reading French (L1) targets with either many orthographic neighbors in English (L2) or few 

orthographic neighbors in English. (B) Scalp voltage maps at three time points between French words with few English 

neighbors and many English neighbors.


Follow-up analyses examining the effects of crossneighborhood-size 

separately for the two target languages 

revealed that English (L2) words with many French orthographic 

neighbors were more negative-going than English 

words with few orthographic neighbors in French (main 

effect of cross-neighborhood-size: F(1,19)=8.08, p=.01). Moreover, 

this cross-neighborhood-size effect tended to be larger 

over the left hemisphere and midline electrode sites than 

over right hemisphere sites (cross-neighborhood-size×laterality 

interaction: F(2,38)=4.49, p=.033 — see Fig. 1B, left). 

There was however, no evidence that French (L1) words 

were affected by the number of English neighbors in this 

epoch (all Fsb1.0 involving cross-neighborhood-size — see 

Fig. 2). 

2.1.2.2. 300–500 ms epoch. As can be seen in Figs. 1 and 2 

differences due to cross-neighborhood-size continued into 

this epoch. The omnibus ANOVA produced marginal effects 

for cross-neighborhood-size (F(1,19)=3.24, p =.089) and a 

cross-neighborhood-size×language interaction (F(1,19)=4.13, 

p=.056) and importantly a significant cross-neighborhoodsize×language×electrode 

site interaction (F(3,57)=3.85, 

p=.037). This latter interaction indicated differences in the 

scalp distribution of the cross-neighborhood-size effect for the 

two languages. 

Follow-up analyses examining the effects of cross-neighborhood-size 

separately for the two target languages demonstrated 

that English words (L2) with many French (L1) 

orthographic neighbors were again more negative-going 

than English words with few French neighbors (main effect 

of cross-neighborhood-size: F(1,19)=8.63, p=.008). However, 

unlike the earlier epoch where the cross-neighborhood-size 

effect was larger over left and midline sites, in this epoch the 

effect was more widespread across the head and was 

bilaterally more symmetrical (see Fig. 1B middle and right). 

Also different from the earlier epoch where there was no 

evidence of significant cross-neighborhood-size effects for 

French words, in this window French words with many 

English orthographic neighbors did produce evidence of 

more negative-going ERPs than French words with few English 

neighbors (although the main effect of cross-neighborhoodsize 

was not significant, pN.778). This was revealed in a 

significant cross-neighborhood-size ×electrode site interaction 

(F(3,57)=4.5, p=.029). As can be seen in Figs. 2A and B, 

these effects were not widespread across the scalp and were 

significant only at the three most posterior sites (occipital 

cross-neighborhood-size F(1,19)=5.74, p=.027). 

2.1.3. Experiment 1 behavioral results 

Participants averaged 17 (SD=0.94) out of 18 hits in their L1 

(95%) and 14 (SD=1.77) out of 18 hits in their L2 (79%) for probe 

words. This difference was significant (t(19)=7.78, p=.001). 

Participants produced false alarms on an average of 1.8 items 

(SD=1.01) in L1 (2.4%) and on 1.9 items (SD=2.87) in L2 (2.5%). 

This difference between languages was not significant (pN.9). 

In a post translation task participants were asked to translate 

all 74 L2 target words that they had seen in the experiment. 

The mean number of correct translations was 53 (SD=9.2) or 

71%. The mean number of correct translations of probe items 

was 15 (SD=1.88) or 81%. 

2.2. Discussion of Experiment 1 

The results of Experiment 1 show effects of cross-language 

orthographic neighborhood density in the ERP waveforms 

generated during the processing of words in L1 and L2. These 

cross-language neighborhood effects had an earlier onset and 

were more widely distributed when the targets were in L2. 

This is important evidence in favor of initial non-selective 

access processes in bilingual word recognition, as assumed in 

the BIA+ model (Dijkstra & van Heuven, 2002). Participants in 

this study read words in one language only (and knew that 

they would only receive words in one language in a given list), 

yet the orthographic characteristics of the words in the nonpresented 

language influenced the way our participants 

reacted to these stimuli. These results can be explained by a 

combination of non-selective access (a string of letters 

activates compatible whole-word orthographic representations 

in both of a bilingual's languages) and lateral inhibition 

across word representations in an integrated lexicon. A given 

stimulus word generates activation in all whole-word orthographic 

representations that are partly compatible with the 

stimulus, and these co-activated word representations inhibit 

processing of the target word itself. The increased difficulty in 

target word processing is reflected in the greater ERP 

negativities between 200 and 500 ms, a result similar to that 

previously reported for neighborhood density in a monolingual 

context (Holcomb et al., 2002), and compatible with the 

time-course of component processes in visual word recognition 

proposed by Holcomb and Grainger (2006, 2007). 

2.3. Experiment 2 results 


2.3.1.1. 175–275 ms epoch. As can be seen in Fig. 3 there 

does not appear to be much of a cross-neighborhood-size 

effect in this epoch (cross-neighborhood-size main effect: 

F(1,19)=2.85, p=.108; cross-neighborhood-size×electrode site 

pN0.2) and this small marginal main effect is actually in the 

opposite direction compared to the results for English targets 

in Experiment 1. 

2.3.1.2. 300–500 ms epoch. As can be seen in Fig. 3, there is 

only a small effect of cross-neighborhood-size in this epoch (F 

(1,19)=3.00, p=.100; cross-neighborhood-size×electrode site 

pN0.2) and importantly this marginal main effect is in the 

opposite direction compared to the results for English targets 

in Experiment 1 as in the previous epoch. 

2.3.2. Experiment 2 behavioral results 

Participants averaged 84% (SD=9.5%) hit rate for probe words. 

2.3.3. Combined analysis of Experiments 1 and 2 

A between participants analysis was carried out, comparing 

the English list of the L1 French participants in Experiment 1 

with the English list of the monolingual participants in 

Experiment 2 to insure that our effects, showing the influence 

of cross-language neighborhood on word recognition, are not 

due to any properties of the English items that we may not 

have effectively controlled. While there was no main effect of


129 

Fig. 3 – (A) Results of the monolinguals reading English targets with either many orthographic neighbors in French or few 

orthographic neighbors in French. (B) Scalp voltage maps showing the difference at three time points between English words 

with few French neighbors and many French neighbors.


cross-neighborhood-size in either epoch (both pN.260), there 

was a significant interaction of cross-neighborhood-size by 

experiment in both epochs (early: F(1,38)=10.69, p=.002; late: 

F(1, 38)=11.26, p=.002). 

2.4. Discussion of Experiment 2 

The results of Experiment 2 demonstrate that the pattern of 

effects seen in these monolinguals is not similar to those of 

bilinguals when processing a list of English words in which 

cross-language orthographic neighborhood size varies. This 

implies that the effects of cross-language neighborhood size 

that was found in the bilinguals in Experiment 1 are not due to 

some confound or uncontrolled property of the English list. If 

that had been the case, we should have seen very similar 

effects of this variable in Experiment 2. 

Our results clearly indicate that when bilinguals read lists 

of words in one of their languages, the brain's reaction to these 

word stimuli is influenced by the orthographic characteristics 

of the words in the other (non-presented) language. The BIA+ 

model (Dijkstra & van Heuven, 2002) accounts for such crosslanguage 

influences in terms of non-selective activation of 

word representations in both of the bilingual's languages. In a 

simulation study we put the BIA+ model to test with the 

stimuli used in the present experiments. 

2.5. Simulation study results 

The mean number of cycles to reach the identification threshold 

for the different experimental conditions in Experiments 1 

and 2 is presented in Table 1. We conducted separate analyses 

for Experiment 1 (bilinguals) and Experiment 2 (English 

monolinguals). The data of the bilinguals revealed a significant 

effect of Language (F(1,144)=23.42, pb.001), Cross-Neighborhood-Size 

(F(1,144)=4.41, pb.05), and importantly a significant 

interaction between these factors (F(1,144)=5.21, pb.05). This 

interaction is due to a significant inhibition effect (0.7 cycles) of 

cross-language neighborhood size for English words (F(1,72)= 

8.51, pb.01) and not for French words (F(1,72)b1). As expected, 

Table 1 – Simulated response times of French–English 

bilinguals and English monolinguals in the BIA+ model 

for the different experimental conditions tested in 

Experiments 1 (bilingual participants) and 2 (monolingual 

participants) 

Neighborhood Bilinguals Monolinguals 

size 

English targets 

French targets 

High French 21.1 20.1 

Low French 20.4 20.0 

difference 0.7 0.1 

High English 20.0 

Low English 20.1 

difference −0.1 

Average number of cycles to reach the word identification threshold 

for English words with many French neighbors (High French) or 

few French neighbors (Low French) and French words with many 

English neighbors (High English) or few English neighbors (Low 

English). 

the data of the English monolinguals did not show any effect of 

cross-language neighborhood size (F(1,72)b1). 

2.6. Simulation study discussion 

The results of the simulation study show that the BIA+ model 

correctly predicts an influence of cross-language orthographic 

neighborhood size. The effect of cross-language neighbors 

was significant in the simulation of bilinguals recognizing L2 

words. As expected, no effect of cross-language neighborhood 

size was found in the simulation of English monolinguals. The 

BIA+ model therefore simulates the pattern of cross-language 

neighborhood effects for French–English bilinguals and English 

monolinguals that, overall, mimics the effects found in 

our ERP experiments. The simulation study revealed a 

significant interaction between cross-language neighborhood 

size and language, thus correctly accounting for the stronger 

effects that were found in L2 than in L1 in Experiment 1. 

3. General discussion 

In the present study French–English bilinguals were shown 

pure-language lists of words that varied in terms of the 

number of orthographic neighbors they had in the other 

language (the number of cross-language neighbors). French 

native speakers who were relatively proficient in English were 

found to be sensitive to the cross-language neighborhood 

density of words in both their L1 (French) and their L2 

(English). Words with many cross-language neighbors generated 

a more negative-going ERP waveform in the region of the 

N400 than words with few cross-language neighbors. This 

cross-language neighborhood effect appeared earlier (in the 

175–275 ms epoch) and was more widely distributed across the 

scalp when the target words were in English (L2) and the 

neighbors in L1. Effects of cross-language neighborhood on 

French (L1) words only appeared in the 300–500 ms epoch and 

were limited to the most posterior electrode sites. The strong 

effects of L1 (French) neighbors on processing L2 (English) 

words cannot be attributed to any properties of the English 

items apart from their French neighborhood size because 

English monolingual participants did not show the same 

pattern of ERPs to these stimuli. 

These results provide considerable support for the nonselective 

access hypothesis embodied in the BIA+-model 

(Dijkstra & van Heuven, 2002), and contradict the notion of 

early language-specific selection in bilingual language comprehension. 

Our participants saw lists of words in one 

language only and were therefore in appropriate conditions 

for using language-specific selection processes. The results 

clearly indicate that such selection processes were not 

effective in blocking the activation of word representations 

in the irrelevant language. We found evidence for early 

activation of non-target language representations that influenced 

the processing of target words. The more negativegoing 

waveforms found for words with large numbers of crosslanguage 

neighbors is interpreted as reflecting a greater 

difficulty in settling on a single form-meaning interpretation 

of the stimulus (Holcomb et al., 2002). Words with more crosslanguage 

neighbors suffer from the co-activation of the lexical


131 

representations of these neighbors, as reflected in the 

typically longer RTs found to these stimuli in behavioral 

studies (Grainger & Dijkstra, 1992; van Heuven et al., 1998). 

The results of Experiment 1 show that L2 neighbors have a 

later and less widely distributed effect on L1 target processing 

than L1 neighbors have on L2 target processing. This is 

perfectly in line with one major principle implemented in all 

connectionist models of language processing — that frequency 

of exposure determines connection strength. Because 

none of our participants in Experiment 1 were early balanced 

bilinguals we can assume that exposure to L2 words is overall 

much lower than exposure to L1 words. This exposure 

difference is thus reflected in word frequency differences 

between L1 and L2. Therefore, L2 word representations will on 

average be more weakly activated by a stimulus than L1 word 

representations, and this imbalance will be exaggerated in a 

competitive network where the dominant representation 

inhibits all others. This therefore accounts for why the effects 

of L2 neighbors are weaker, less widely distributed (since more 

time is required for propagation), and appear later than the 

effects of L1 neighbors. Simulations run on the BIA+ model 

show effectively that cross-language neighborhood effects are 

stronger when targets are in L2 compared with targets in L1 

(see Table 1). 

Experiment 2 of the present study tested monolingual 

English participants with the same list of English words 

presented to the French–English bilinguals of Experiment 1. 

Since these monolingual participants did not show that same 

pattern of effects of cross-language neighborhood (i.e., of 

French language neighbors) as the bilinguals, this allows us to 

reject uncontrolled for within-language variables as the 

source of the cross-language neighborhood effect found in 

Experiment 1. Therefore, the present study adds to the 

behavioral literature on effects of cross-language orthographic 

and phonological similarity (Marian & Spivey, 2003; van 

Heuven et al., 1998) showing that the process of word 

comprehension in bilingual participants presented with 

words in one of their languages is influenced by the similarity 

of these words to words in the non-presented language. 

The present study provides important information concerning 

the time-course of cross-language neighborhood 

effects. The results of Experiment 1 show relatively early 

influences of L1 orthographic neighbors on the processing of 

L2 words, emerging as early as 200 ms post-target onset (see 

Fig. 1). Such early influences were not found in the withinlanguage 

neighborhood manipulation of Holcomb et al. (2002). 

This can be explained by differences in the relative frequency 

of target words and their orthographic neighbors in the 

Holcomb et al. and the present study. Orthographic neighbors 

will tend to have higher subjective frequencies when these 

neighbors are L1 words and the target a word in L2 (compared 

to L1 neighbors of L1 words), and the more frequent the 

orthographic neighbors are relative to the target word, the 

more rapidly they can influence target word processing. 

Furthermore, as processing develops and word recognition is 

in its final stages (i.e., a stable form-meaning association is 

established), activation of the target word itself will dominate 

processing and neighborhood effects disappear. 

Furthermore, the precise timing of the effects found in the 

present study is in line with the time-course analysis of visual 

word recognition proposed by Holcomb and Grainger (2006, 

2007). According to their analysis, form-level (orthographic 

and phonological) processing of printed words initiates 

around 200 ms post-target onset with the mapping of 

prelexical representations onto whole-word forms, and culminates 

at around 400 ms (the peak of the N400) with the 

mapping of lexical form onto meaning. Within the generic 

interactive-activation model adopted by Holcomb and Grainger, 

effects of orthographic neighborhood are generated by 

competition arising between co-activated whole-word representations. 

This lexical-level competition already affects the 

early mapping of prelexical form representations onto wholeword 

form representations and further influences processing 

upstream, increasing the difficulty of mapping whole-word 

forms onto semantics. Given that orthographic neighborhood 

correlates highly with phonological neighborhood (e.g., Grainger 

et al., 2005), it is likely that part of the effects of 

orthographic neighborhood are being driven by competition 

between phonologically similar words. However, this possibility 

is greatly reduced in a cross-language neighborhood 

manipulation as used in the present study, given the lower 

levels of phonological overlap between orthographically 

similar words from different languages. 

In conclusion, the present study provides further evidence 

for cross-language permeability in bilingual word 

recognition, in particularly stringent testing conditions. 

First, following the behavioral study of van Heuven et al. 

(1998) participants saw words of one language only in a 

given list, and cross-language interference was evaluated by 

a manipulation of the number of orthographic neighbors in 

the non-presented language. Second, our participants had 

to silently read words for meaning and respond (on noncritical 

trials) whenever a body part appeared, a procedure 

that minimizes contamination by decision-related processes. 

The ERPs generated by target words on critical trials 

were found to be sensitive to the number of orthographic 

neighbors of that word in the other language of our bilingual 

participants. This constitutes perhaps the strongest evidence 

to date in favor of initial parallel access to representations 

in both languages when bilinguals are reading in one 

language. 

4. Experimental procedures 



Twenty-two participants were recruited and compensated for 

their time. The data from two participants was not used due to 

excessive noise in their ERP data. Of the remaining 20, thirteen 

were women (mean age=23 years, SD=4.7), all were right 

handed (Edinburgh Handedness Inventory — Oldfield, 1971) 

and had normal or corrected-to-normal visual acuity with no 

history of neurological insult or language disability. 

French was reported to be the first language learned by all 

participants (L1) and English their primary second language 

(L2). All participants began their study of English in their sixth 

year of primary school at approximately the age of 12 years, 

as is customary in the French school system. Participants'


daily use of English, auto-evaluation of English and French 

language skills and a history of study and of immersion in 

English were surveyed by questionnaire. Participants reported 

daily use of English to be on average 42% (SD=26.8%) of their 

total language use. On a seven point scale (1=unable; 

7=expert) participants reported their abilities to read, speak 

and comprehend English and French as well as how 

frequently they read in both languages (1=rarely; 7=very 

frequently). The overall average of self-reported languages 

skills in French was 6.9 (SD=0.32) and in English was 5.7 

(SD=0.95). Our participants reported their average frequency 

of reading in French as 6.3 (SD=1.05) and in English as 5.8 

(SD=1.47). 


For the selection of stimuli a French lexicon was extracted 

from the Lexique database (New et al., 2004), and an English 

lexicon from the CELEX database (Baayen et al., 1995). These 

lexicons contained only 4 and 5-letter, monosyllabic and bisyllabic 

words with at least 1 occurrence per million, and were 

used to calculate the number of orthographic neighbors of 

words within and across languages. The final set of stimuli for 

the study were 74 English and 74 French words between four 

and five letters in length with half of the items in each 

language having many orthographic neighbors in the other 

language and other half having few neighbors in the other 

language (an orthographic neighbor is defined as a word of the 

same length having all but one letter in common respecting 

letter position (Coltheart et al., 1977). 

The English items from large French neighborhoods had a 

mean number of French neighbors of 5.9 (range=4–13, 

SD=2.2). For the English items with few French neighbors 

the mean number of French neighbors was 1.1 (range=0–3, 

SD=1.1). These means were significantly different (t(72)=4.58, 

p=0.036). The means of within language neighbors for these 

two groups of English words were 6.5 (SD=3.4) for items with 

many French neighbors and 6.9 (SD=3.6) for items with few 

French neighbors. These means were not significantly different 

(t(72)=1.29, p=0.26). The mean frequency per million, of 

English words with many French neighbors was 12.9 (SD=13.9) 

while for items with few French neighbors the mean 

frequency was 12.8 (SD=13.0). These means were not significantly 

different (t(72)=0.04, p=0.97). The mean number of 

letters for English items was not significantly different for the 

two conditions (see Table 2 for mean lengths, t(72)=0.73, 

p=0.47). 

Table 2 – Stimulus characteristics for the two languages 

and the two conditions 

English 

targets 

French 

targets 

Mean 

number of 

cross 

language 

neighbors 

Mean 

number of 

within 

language 

neighbors 

Mean 

frequency 

count per 

million 

Mean 

length 

Many 5.9 (2.2) 6.5 (3.4) 12.9 (13.9) 4.4 (0.5) 

Few 1.1 (1.1) 6.9 (3.6) 12.8 (13.0) 4.3 (0.5) 

Many 7.8 (3.6) 6.6 (3.1) 15.2 (15.0) 4.4 (0.5) 

Few 0.7 (1.0) 4.7 (3.3) 14.2 (11.9) 4.5 (0.5) 

The French items from large English neighborhoods had a 

mean number of English neighbors of 7.8 (=5–19, SD=3.6). For 

the French items with few English neighbors the mean 

number of English neighbors was 0.7 (range=0–5, SD=1.0). 

These means were significantly different (t(72)= 25.62, 

pb0.001). The means of within language neighbors for these 

two groups of French words were 6.6 (SD=3.1) for items with 

many English neighbors and 4.7 (SD=3.3) for items with few 

English neighbors. These means were not significantly 

different (t(72)=0.50, p=0.48). The mean frequency per million, 

of French words with many English neighbors was 15.2 

(SD=15.0) while for items with few English neighbors the 

mean frequency was 14.2 (SD=11.9). These means were not 

significantly different (t(72)=0.30, p=0.76). The mean number 

of letters for French items was not significantly 

different for the two conditions (, t(72) =1.41, p =0.16). 

Mean lengths can be seen in Table 2. 

Two lists were formed, one with the 74 English words in a 

pseudorandom order and one with the 74 French words in a 

pseudorandom order. Intermixed in each list was a second 

group of 18 probe words which were all members of the 

semantic category of “body parts” (probes were English words 

in the English list and French words in the French list). The 

order of the list, blocked by language was counter-balanced 

across participants. 


The word stimuli in each list were presented as white letters 

centered vertically and horizontally on a black background on 

a 15 in. color monitor (Toshiba Tekbright). Presentation of all 

visual stimuli and digitizing of the EEG was synchronized 

with the vertical retrace interval (60 Hz refresh rate) of the 

stimulus PCs video card (ATI Radeon) to assure precise time 

marking of ERP data. The participants were seated so that 

their eyes were at a distance of approximately 1.5 m from the 

screen. The maximum height and width of the stimuli were 

such that no saccades would be required during reading of 

the single word stimuli (i.e., the width of the word filled less 

than 2 degrees of the participant's visual field). Participant 

responses were made using a button box held in the lap 

throughout the experiment. A go/no-go semantic categorization 

task was used in which participants were instructed to 

read all words but to press a button whenever they saw a 

word referring to a body part. Eighteen trials in each language 

block were body part words (19.5% of all trials). As can be seen 

in Fig. 4, each trial began with the onset of a fixation cross 

which remained on screen for 200 ms and was followed by 

300 ms of blank screen. A target word then appeared for a 

duration of 300 ms was followed by 1000 ms of blank screen. 

Each trial ended with a screen indicating that it was 

permissible to move or blink the eyes [( - - )]. This screen 

had a duration of 2500 ms. The next trial began after 500 ms 

of blank screen with the fixation cross. 

4.1.4. EEG recording 

Participants were seated in a comfortable chair in a sound 

attenuating room and were fitted with an elastic cap equipped 

with 29 tin electrodes (Electro-cap International — see Fig. 5 

for the location of electrodes). Two additional electrodes were 

used to monitor for eye-related artifact (blinks and vertical or


133 

Fig. 4 – Schematic of two trials in the English block, one with a target word (grape) and another with a probe word requiring a 

button pressing response (foot). 

horizontal eye movement); one below the left eye (VE) and one 

horizontally next to the right eye (HE). All electrodes were 

referenced to an electrode placed over the left mastoid (A1). A 

final electrode was placed over the right mastoid (A2 — used to 

determine if there was any asymmetry between the mastoids; 

none was observed). The 32 channels of electrophysiological 

data were amplified using an SA Instruments Bio-amplifier 

system with 6db cutoffs set at .01 and 40 Hz. The output of the 

bio-amplifier was continuously digitized at 200 Hz throughout 

the experiment. 

After electrode placement instructions for the experimental 

task were given in French then a short practice list (in the 

Fig. 5 – Electrode Montage and analysis sites (in grey).


language of the first block) was presented to assure good 

performance during experimental runs and to accustom the 

participant to the coming language. A practice list was also 

run before the second block in the language of the second 

block. The order of language blocks was counterbalanced 

across participants. There were three pauses within each 

block; the length of these pauses was determined by the 

participant. Each language block typically required 15 min. At 

the end of the ERP experiment participants were asked to give 

a translation of the 92 English words that they had seen during 

the experiment (74 critical items and 18 body parts). These 

post-translations were graded for accuracy and reported as 

behavioral results. 


ERPs were averaged separately for English target words that 

had many or few orthographic neighbors in French, and 

French target words that had many or few orthographic 

neighbors in English. Only trials contaminated by eye movement 

activity were rejected prior to averaging (7.1% of trials). 

Because we did not assume that translation performance is 

equivalent to L2 word representation all French items were 

averaged regardless of post-translation results. All target 

items were baselined to the average of activity in the 40 ms 

pre-target period and were lowpass filtered at 15 Hz. 1 The 

ERPS were then quantified by measuring the mean amplitude 

in two latency windows: 175–275 ms to capture pre-N400 

activity, and 300–500 ms to capture the N400 itself. In order 

to analyze the scalp distribution of the various ERP components 

omnibus repeated measures analyses of variance 

(ANOVAs) were carried out for 12 electrode sites from 

representative frontal (FC1, Fz and FC2) middle (C3, Cz and 

C4), parietal (CP1, Pz and CP2) and occipital (O1, Oz, and O2) 

locations. This arrangement allowed for a single omnibus 

ANOVA with factors of language (French vs. English), crossneighborhood-size 

(many vs. few), electrode-site (F vs. C vs. 

CP vs. O) and laterality (left vs. medial vs. right). Significant 

interactions in the omnibus analyses involving language and 

cross-neighborhood-size were decomposed with followed-up 

ANOVAs looking at each LANGUAGE (French/English) separately. 

The Geisser-Greenhouse (1959) correction was applied 

to repeated measures with more than one degree of freedom 

in the numerator. 2 



Twenty participants (11 women) were recruited and compensated 

for their time (mean age=20 years, SD=1.3). All were 

right handed (Edinburgh Handedness Inventory — Oldfield, 

1971) with normal or corrected-to-normal visual acuity and no 

history of neurological insult or language disability. All 

1 A 40ms baseline was chosen because using the more traditional 

100 pre-stimulus baseline resulted in a substantial difference 

between conditions in the first 50ms after target word onset. 

2 We performed a first pass analysis including the factor of 

order to test for differential effects of which target language block 

occurred first. There were no interactions involving the order and 

language or cross-neighborhood-size factors (all Fs b 2). In all of 

the analyses reported we collapsed across this factor. 

participants reported to be monolingual native English speakers 

and to have had no classroom exposure to French as an L2. 

4.2.2. Stimuli and procedure 

Materials and experimental task were the same as in Experiment 

1 but only the English list was presented to these 

participants. 


Trials contaminated by eye movement activity were rejected 

prior to averaging (8.9%). ERPs were averaged for English 

target words that had many or few orthographic neighbors in 

French. All target items were baselined to the average of 

activity in the 40 ms pre-target period and were lowpass 

filtered at 15 Hz. The ERPs were then quantified, as in 

Experiment 1, by measuring the mean amplitude in two 

latency windows: 175–275 ms and 300–500 ms. The analysis 

approach was identical to Experiment 1, but the factor of 

target language was eliminated as these monolingual participants 

only read words in their L1. 

4.3. Simulation study 

The model was implemented with a 4 and 5-letter French 

word lexicon extracted from the Lexique database (New et al., 

2004), and a 4 and 5-letter English word lexicon from the CELEX 

database (Baayen et al., 1995). Only words with at least 2 

occurrences per million (opm) were included in the lexicons. 

The bilinguals of Experiment 1 were not perfectly balanced 

bilinguals, therefore word frequencies (implemented as resting-level 

activations of word nodes in the BIA+ model) were 

adjusted to simulate such unbalanced high proficiency 

bilinguals (see Dijkstra & van Heuven, 1998). The restinglevel 

activations of French (L1) were scaled between the 

default word node resting-level activation values of the 

Interactive Activation (IA) model (McClelland & Rumelhart, 

1981). Thus, the resting-level activation of the most frequent 

word was set to 0 and the resting-level activation of the least 

frequent words (2 opm) was set to −0.92. Other word nodes 

were assigned resting-level values between −0.92 and −0.01 

based on their word frequency. The resting-level activations of 

the English (L2) words were scaled for the bilinguals between 

−1.20 and 0. To simulate the English monolingual data of 

Experiment 2 we conducted simulations with only English 

words with resting-level activations between −0.92 and 0. 

Parameters of the BIA+ model with 4-letter words were 

identical to those of the IA model. Parameters for the 

simulations with the 5-letter word lexicons were identical to 

the simulation of the 4-letter words except for the letter-toword 

excitation parameter, which was reduced from 0.07 to 

0.06 as in the simulations of Grainger and Jacobs (1996). Target 

words were presented to the model until the target word 

reached the word identification threshold of 0.70. 

Acknowledgments 

This research was supported by grant numbers HD25889 and 

HD043251. The authors would like to thank Courtney Brown 

for her help in data collection.


135 

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Effets de cognats 

Chapitre 4 

Les effets de cognats sur 

la compréhension des mots chez les apprenants 

en langue seconde : une étude en potentiels évoqués* 

La technique des potentiels évoqués a permis d’examiner différents patterns concernant le 

traitement des cognats et des non-cognats chez des apprenants en langue seconde. Des 

apprenants du français (L2), dont la première langue (L1) est l’anglais, ont lu des listes de 

mots en L1 et L2. Les potentiels évoqués ont été enregistrés par rapport aux deux 

conditions : cognats et non-cognats. Des comparaisons entre cognats et non-cognats ont 

été réalisées pour les deux langues. Dans les deux langues, les cognats ont produit des 

amplitudes réduites dans la région de la N400 par rapport aux non-cognats. Néanmoins, 

les différences entre les cognats et les non-cognats pendant le traitement en L1 se 

manifestaient dans la première partie de la composante N400 alors que ces mêmes 

différences pour le traitement en L2 n'ont été observées que sur une partie plus tardive de 

cette même composante. La discussion abordera les effets des cognats sur la 

compréhension des mots chez des apprenants en langue seconde. 

Mots-clefs : Bilinguisme, Cognats, Acquisition en langue seconde, Reconnaissance 

visuelle des mots, Potentiels évoqués 

________________________ 

* Article submitted, Journal of Cognitive Neuroscience, January 2009 

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Effects of cognate status on word comprehension in second language learners: 

an ERP investigation 

Katherine J. Midgley 

Tufts University, Medford, Ma USA & CNRS & Université d'Aix-Marseille, 

Marseille, France 

Phillip J. Holcomb 

Tufts University, Medford, Ma USA 

Jonathan Grainger 

CNRS & Université d'Aix-Marseille, Marseille, France 

Address for correspondence: 

Katherine J Midgley 

Department of Psychology 

Tufts University 

Medford, MA 02155 USA 

kj.midgley@tufts.edu 

Voice: (617) 627-3521 

Fax: (617) 627-3181 

*This Research was supported by grant numbers HD043251 & HD25889. 

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Abstract 

ERPs were used to explore the different patterns of processing of cognate and noncognate 

words in the first (L1) and second language (L2) of a population of second 

language learners. L1 English students of French were presented with blocked lists of L1 

and L2 words, and ERPs to cognates and non-cognates were compared within each 

language block. For both languages, cognates had smaller amplitudes in the N400 

component when compared to non-cognates. L1 items that were cognates showed early 

differences in amplitude in the N400 epoch when compared to non-cognates. L2 items 

showed later differences between cognates and non-cognates than L1 items. The results 

are discussed in terms of how cognate status affects word recognition in second language 

learners. 

Keywords: Bilingualism, Cognates, Second language acquisition, ERPs, Visual word 

recognition, 

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The 1066 victory of William the conqueror at the battle of Hastings and the 

subsequent centuries of Norman rule had enormous impact on the England of the middle 

ages. One of the legacies of this period can be found in the relationship of the French and 

English languages. The imposition of French on English during that time resulted in the 

incorporation of many tokens of French into English, a language already accepting of 

many borrowed forms. This shared history leaves the two languages today with a 

multitude of shared words like “table”. This type of non-accidental overlap of form in 

translation equivalents is what defines cognate words. Many English–French cognates 

have complete written overlap like “fruit” or near complete overlap like “mask” and 

“masque”. In the study presented here, we examined the processing of cognate words 

such as these as compared to non-cognate words by English-French beginning bilinguals. 

Cognates’ membership in both of a bilingual’s lexicons make them a special case. It 

is this special status that will be exploited in the present study in order to address different 

questions of bilingual lexical access. Because of their shared form with L1 items, 

cognates, during L2 acquisition, could be a learner’s first foothold into the new lexicon. 

Presumably in the early stages of acquisition this would result in different patterns of 

processing for cognates and non-cognates while processing L2. In the case of L1 

processing, if cognates showed different patterns of processing when compared to noncognates 

this would be evidence of the L1 changing as a function of learning an L2, and 

also point to an integrated lexicon with non-selective access for the two languages. 

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In behavioral studies cognate items have been shown to elicit different response 

patterns compared to non-cognate items. Cognates are more rapidly recognized than noncognates 

in isolated word recognition tasks such as lexical decision (Dijkstra, Grainger & 

van Heuven, 1999; Lemhöfer & Dijkstra, 2004; Lemhöfer, Dijkstra & Michel, 2004). 

Cognate items have been shown to be translated more quickly than non-cognate items (de 

Groot, 1992; Sánchez-Casas, Davis, & García-Albea, 1992). Both Dijkstra et al. (1999) 

and Lemhöfer and Dijkstra (2004) tested cognates mixed with non-cognate words from 

L2. However, studies testing cognate processing in an L1 context have given mixed 

results. Some authors failed to observe a difference between cognate and non-cognate 

words in an L1 context (Caramazza & Brones, 1979; Gerard & Scarborough, 1989) while 

others did find effects (van Hell & de Groot,1998; de Groot, Delmaar, & Lupker, 2000; 

van Hell & Dijkstra, 2002). Thus, in general, it would appear that word recognition in L2 

benefits from cognate status, whereas word recognition in L1 is more impervious to such 

influences. This is in line with other observed asymmetries in bilingual lexical 

processing, such as the greater strength of translation priming from L1-L2 compared with 

L2-L1 (see Midgley, Holcomb, & Grainger, in press-b, for a recent example). 

Effects of cognate status on word recognition in L1 have, however, been 

documented. Van Hell and Dijkstra (2002) showed clear effects of cognate status during 

L1 processing and this while testing 2 groups of trilinguals of different proficiencies in 

their L3. In experiments 2 and 3 they used a lexical decision task in L1 (Dutch) to 

examine the influence of cognates from both L2 (English) and L3 (French). They found a 

similar advantage for L2 cognates for both groups. However a significant advantage for 

L3 cognate items was observed only for the groups having more proficiency in L3. The 

group with less proficiency in L3 showed only a weak trend toward a cognate advantage. 

They concluded that a certain level of proficiency is necessary in the bilinguals’ non- 

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target language relative to their target language in order to observe effects on processing 

in the target language. In other words a bilingual must have enough fluency in an L2 or 

L3 for cognate status to influence L1 processing. 

Strong cognate effects have also been reported in a variety of priming paradigms 

(Bowers, Mimouni, & Arguin, 2000; Cristoffanini, Kirsner, & Milech, 1986; Lalor & 

Kirsner, 2001), including masked priming (e.g., de Groot & Nas, 1991; Gollan, Forster, & 

Frost, 1997; Sánchez-Casas et al., 1992) where the contribution of strategic factors are 

less likely to have influenced the findings. Voga and Grainger (2007) found priming for 

both cognates and non-cognates across different scripts (Greek and French). When 

cognates and non-cognates were compared to unrelated primes cognates showed greater 

priming, but when cognates and non-cognates were compared to phonologically related 

primes this advantage disappeared. Voga and Grainger concluded that this difference in 

priming size as a function of baseline comparison was evidence that the cognate 

advantage is simply due to the additional form overlap of cognates and not some special 

status of cognate words. Together this literature points towards an advantage in 

processing for words from a bilingual’s two languages when the items share both form 

and meaning. 

The nature and locus of the cognate advantage 

In behavioral studies the locus of the cognate effect is difficult to establish. In 

laboratory tasks such as lexical decision, demand characteristics of an experiment could 

exert their influence on performance in ways that are relatively uninformative about the 

word recognition system per se. Furthermore the observation that a certain level of L2 

proficiency is needed in order to observe behavioral effects on L1 processing raises the 

possibility that effects with lower levels of proficiency were not observed because of poor 

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measurement sensitivity. Perhaps a more sensitive measure could be used to observe L2 

effects on L1 processing even at relatively early stages of second language acquisition. 

Consistent with this view van Hell and Dijkstra showed a non-significant trend in less 

proficient bilinguals in the same direction as the significant effect they reported for the 

more proficient participants. Of interest here is whether with a more sensitive measure 

they would have found stronger evidence for an effect of cognate status on L1 even in 

relatively non-proficient learners of a second language. Such an effect would be strong 

evidence that even at early stages of becoming bilingual that there are profound changes 

in the L1 as a function of learning a new language. 

What mechanisms could be at the basis of the observed behavioral advantage in 

processing cognate words compared with non-cognates in bilinguals and L2 learners? The 

most straightforward interpretation is in terms of increased exposure to the same 

orthographic and/or phonological patterns, and most critically, the same association 

between a given form representation and its corresponding meaning. This would account 

for why increased proficiency in the non-native language causes an increase in the effects 

of cognate status when processing L1 words (van Hell & Dijkstra, 2002). The strong 

cognate advantage found when processing L2 words would be due to the cognate words 

benefiting from pre-existing form-meaning associations in the L1. However, this specific 

processing advantage must be evaluated against a general background of overall 

differences in processing L1 and L2 words related to a multitude of other factors 

(Midgley, Holcomb & Grainger, in press-a). 

ERPs and bilingual word recognition 

The present experiment examined the nature and time course of cognate processing 

as it compares to non-cognate processing in a bilingual’s two languages by using 

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electrophysiological measures. Electrophysiological measures are used because they more 

directly reflect the processing of items, being an on-line measure of brain activity rather, 

as in the case with RTs, just one data point after processing has been completed. Eventrelated 

potentials (ERPs) are measures of the brain’s electrical activity recorded at the 

scalp and obtained by averaging time-locked responses to stimuli onset thus extracting 

the voltage signature of the processing of the items of interest from the background 

electroencephalogram. ERPs are multidimensional in that they contain time-course 

information, scalp distribution information along with the voltage measures. This 

multidimensionality is informative not only about the time course of word processing but 

also about differences in the nature of this processing. 

Of particular interest to studies of word processing using ERPs is a negative going 

component that starts around 250 ms post word onset and continues on until about 600 

ms. This ERP component, called the N400, has been shown to reflect lexical and 

semantic processes associated with word recognition, being larger whenever a word is 

more difficult to process or integrate into its surrounding context (Lau, Phillips & 

Poeppel, 2008; Holcomb et al., 1993). Numerous studies have shown that the amplitude 

of the N400 is sensitive to a host of linguistic variables including word frequency (larger 

to low frequency words than high, e.g., Van Petten & Kutas, 1990; Münte et al., 2001) 

and orthographic neighborhood density (larger to words with more dense neighborhoods, 

Holcomb, Grainger & O’Rourke, 2002; Midgley, Holcomb, van Heuven & Grainger, 

2008). These results, plus the results of many other studies using single word stimuli 

(e.g., Holcomb & Grainger, 2006; 2007) all suggest that an increased amplitude in the 

N400 component reflects an increased difficulty in processing the target word, and more 

specifically in terms of settling on a unique form-meaning interpretation. 

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The present study 

In the present experiment, we sought electrophysiological evidence for the cognate 

advantage reported in previous behavioral experiments, and investigated whether this 

cognate effect differs while processing in L2 and L1. Participants read lists of words for 

meaning while making occasional button presses to probes from a specific semantic 

category. The critical items were words that were either cognates or non-cognates. In one 

block of trials all items were in L1, and in the other block all items were in L2. This 

design allowed us to directly compare ERPs to cognates and non-cognates in the two 

language blocks. Based on previous ERP work investigating single word recognition and 

prior behavioral research on cognate processing we expected to see reduced negativities 

to cognate words compared with non-cognate words in the N400 time window. 

Furthermore, on the hypothesis that the cognate advantage reflects an accumulation of the 

benefits of exposure to a given form-meaning association across two languages, then we 

would expect to see stronger effects when processing L2 words than when processing L1 

words. However, with respect to the relative time-course of visual word recognition in L1 

and L2 (L1 being arguably faster than L2), we expect to see earlier effects of cognate 

status in L1 compared with L2 words. This is because the mapping between form and 

meaning, the hypothesized locus of the cognate advantage, will occur earlier in the 

processing of an L1 word than an L2 word. Here it is assumed that cognates are processed 

differently in L1 and L2, due to a global influence of language context that tunes the 

lexical processor to be prepared for words from one or the other language (Grainger, 

Midgley & Holcomb, in preparation). 

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Methods 

Participants 

Fifty participants were recruited and compensated for their time. The data from 

eight participants was not used due to excessive artifacts in their data or incomplete scalp 

recordings. Of the remaining 42, 33 were women. The mean age of participants was 20 

years (SD = 1.7), all reported to be right handed and had normal or corrected-to-normal 

visual acuity with no history of neurological insult or language disability. English was 

reported to be the first language learned by all participants (L1) and French their primary 

second language (L2). All participants were undergraduate students at Tufts University 

who were either currently enrolled in a French class or had previously studied French at 

Tufts. 

Stimuli 

One hundred and sixty items were chosen that were cognates in English and French. 

These items were cognates with complete overlap of form (eg. “table” in both English 

and French) and very close cognates (“victim” and “victime”). The mean orthographic 

overlap of the items was 89.0% (SD=14.7%). One hundred and sixty items were chosen 

(80 English items and 80 French items) that were non-cognates between English and 

French. That is, they had no obvious form overlap (e.g., “apple” and “pomme”). The 

mean orthographic overlap of these non-cognate items was 7.2% (SD=10.5%). All items 

in all conditions and for both languages were between four and seven letters in length. 

The English cognates had a mean frequency per million of 31.48 (SD = 49.94) (CELEX 

database, 1993; Baayen, Piepenbrock, & Gulikers, 1995) while the French cognates had a 

mean frequency per million of 26.50 (SD = 30.91) (Lexique database; New, Pallier, 

Brysbaert, & Ferrand, 2004). These means were not statistically different (t(318) = 1.19, 

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p = 0.24). The English non-cognates had a mean frequency per million of 38.33 (SD = 

43.16) while the French non-cognates had a mean frequency per million of 28.17 (SD = 

24.92). These means were not statistically different (t(158) = 1.82, p = 0.07). Furthermore 

English cognate mean frequency compared to English non-cognate mean frequency did 

not differ significantly (t(238) = 1.16, p = 0.25) nor did French cognate mean frequency 

differ from French non-cognate mean frequency (t(238) = 0.42, p = 0.68). 

Two lists were formed, each list being composed of two blocks; an English block 

and a French block. Each list contained 80 English cognates and English 80 non-cognates 

for the English block and 80 French cognates and 80 French non-cognates. The items in 

these two lists were counterbalanced to avoid repetition of the cognate items across 

language. That is to say that no one participant saw both an English cognate and its 

French equivalent. The items in each language block were in a pseudorandom order. 

Intermixed in each list was a second group of 40 probe items which were all members of 

the semantic category of “animal names” (probes were English animal names in the 

English block and French animal names in the French block). All participants saw the 

same animal names. The animal names varied in cognate status similar to the critical 

items (i.e., a mix of complete and close cognates and non-cognates) and were also four to 

seven letters in length. The order of the language blocks was counter-balanced across 

participants. 

Procedure 

The word stimuli in each list were presented as white letters centered vertically and 

horizontally on a black background on a 19 inch color CRT monitor. Presentation of all 

visual stimuli and digitizing of the EEG was synchronized with the vertical retrace 

interval (60 Hz refresh rate) of the stimulus PCs video card (ATI Radeon) to assure 

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precise time marking of ERP data. The participants were seated so that their eyes were at 

a distance of approximately 1.5 meters from the screen. The maximum height and width 

of the stimuli were such that no saccades would be required during reading of the single 

word stimuli. Participant responses were made using a button box held in the lap 

throughout the experiment. A go/no-go semantic categorization task was used in which 

participants were instructed to read all words for meaning and to press a button whenever 

they saw a word referring to an animal name. Forty trials in each language block were 

animal names (12% of all trials – see Figure 1 for a typical series of trials). As can be 

seen, each trial began with the presentation of an item for a duration of 300 ms followed 

by a blank screen for a duration of 1000 ms. Each trial ended with a stimulus indicating 

that it was permissible to move or blink the eyes. This blink stimulus [“( - - )”] had a 

duration of 2000 ms followed by 500 ms of blank screen before the next item appeared. 

Figure 1. Schematic of three trials in the English block, a cognate, a probe word and a non-cognate. 

Only the probe word (buffalo) requires a button pressing response. 

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After electrode placement instructions for the experimental task were given in 

English, the L1 of the participants, then a short practice list in the language of the first 

block was presented to assure good performance during experimental runs and to 

accustom the participant to the coming language. A practice list was also run before the 

second block in the language of that block. There were four pauses within each block; the 

length of these pauses was determined by the participant. Each language block typically 

required 15 minutes. Participants were asked to press a button on the response box every 

time they saw an animal name. At the end of the ERP experiment participants were asked 

to give a translation of the English words that they had seen during the experiment. These 

post-translations were graded for accuracy. 

EEG recording 

Participants were seated in a comfortable chair in a sound attenuating room and 

were fitted with an elastic cap equipped with 29 tin electrodes (Electro-cap International - 

- see Figure 2 for the location of electrodes). Two additional electrodes were used to 

monitor for eye-related artifact (blinks and vertical or horizontal eye movement); one 

below the left eye (VE) and one horizontally next to the right eye (HE). All electrodes 

were referenced to an electrode placed over the left mastoid (A1). A final electrode was 

placed over the right mastoid (A2 - used to determine if there was any asymmetry 

between the mastoids; none was observed). The 32 channels of electrophysiological data 

were amplified using an SA Instruments Bio-amplifier system with 6db cutoffs set at .01 

and 40Hz. The output of the bio-amplifier was continuously digitized at 200 Hz 

throughout the experiment. 

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Figure 2. Electrode Montage. 

Data analysis 

Averaged ERPs time-locked to item onset of words in each category were formed 

off-line from trials free of ocular and muscular artifact (less than 8.1 % of trials). ERPs 

were averaged separately for English cognates, English non-cognates, French cognates 

and French non-cognates providing factors of LANGUAGE and COGNATE-STATUS IN A 2X2 

DESIGN. All items were baselined to the average of activity in the 100 ms pre-target 

period and were lowpass filtered at 15 Hz. The ERPs were then quantified by measuring 

the mean amplitude in three latency windows: 200 -300 ms to capture pre-N400 activity, 

and 300-500 ms to capture the N400 itself and 500 – 800 to capture late cognate effects. 

In order to thoroughly analyze the full montage of 29 scalp sites we employed an 

approach to data analysis that we have successfully applied in a number of previous 

studies (e.g., Holcomb, Reder, Misra & Grainger, 2005). In this scheme the 29 channel 

electrode montage is divided up into seven separate parasagittal columns along the 

antero-posterior axis of the head (see Figure 2). The electrodes in each of three pairs of 

lateral columns and one midline column are analyzed in four separate ANOVAs. Three of 

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these analyses (referred to as column 1 or c1, column 2 or c2 and column 3 or c3) 

involved an anterior/posterior ELECTRODE-SITE factor with either three, four or five levels, 

as well as a HEMISPHERE factor (left vs. right). The forth “midline” analysis included a 

single anterior/posterior ELECTRODE-SITE factor with five levels. 

Significant interactions in the omnibus analyses involving factors of language and 

cognate-status were decomposed with followed-up ANOVAs looking at each language 

(English and French) separately. The Geisser-Greenhouse (1959) correction was applied 

to repeated measures with more than one degree of freedom in the numerator. Finally, to 

more carefully track the temporal properties of cognate effects we also performed timecourse 

analyses (TCAs) comparing the cognate and non-cognate ERPs at each of five the 

midline electrodes and for the two languages in eight consecutive 100 ms windows 

between 0 and 800 ms. 

Results 

Visual inspection of ERPs 

Plotted in Figure 3 are the grand mean ERP waveforms for cognate and non-cognate 

L1 (English) items. Contained in Figure 3a are ERPs from all 29 scalp sites, in Figure 3b 

enlarged plots of three midline sites Figure 4 contains the same plots for the L2 (French) 

block of trials. Figure 5a shows voltage maps at six points in time for L1 items, Figure 5b 

for L2 items. The voltage maps are a subtraction of ERPs for items that are cognates from 

ERPs for items that are non-cognates. Accompanying time-course analyses are presented 

in Table 1. As can be seen in these figures 3 and 4 for ERPs anterior to the occipital sites 

the first visible component was a negative-going deflection between 90 and 150 ms after 

stimulus onset (N1). This was followed by a positive deflection occurring at 

approximately 200 ms (P2). A negativity followed the P2 peaking around 400 ms (N400). 

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At occipital sites the first observable component is the P1, which peaked near 100 ms and 

was followed by the N1 at 190 ms and a broad P2 between 250 and 300 ms. The P2 was 

followed by the N400 between 400 and 600 ms. 

Analyses of ERP data 

200 - 300 ms epoch. 

An omnibus ANOVA on the mean amplitude values in this epoch revealed 

significant main effects of LANGUAGE at all columns (midline: F(1,41) = 7.64, p = 0.009, 

c1: F(1,41) = 9.14, p = 0.004, c2: F(1,41) = 12.69, p = 0.001, c3: F(1,41) = 7.59, p = 

0.009). There was also a main effect of COGNATE-STATUS, but it reached significance only 

at column 1 (F(1,41) = 9.14, p = 0.004). The two-way interaction between LANGUAGE and 

COGNATE-STATUS was reliable at all columns (midline: F(1,41) = 9.93, p = 0.003, c1: 

F(1,41) = 11.76, p = 0.001, c2: F(1,41) = 10.23, p = 0.003, c3: F(1,41) = 9.23, p = 0.003). 

Follow-up analyses examining the effects of COGNATE-STATUS separately for the 

two languages in this epoch revealed effects at all columns for L1 (midline: F(1,41) = 

14.14, p = 0.001, c1: F(1,41) = 16.03, p < 0.001, c2: F(1,41) = 13.04, p = 0.001, c3: 

F(1,41) = 11.01, p = 0.002) with non-cognates being more negative than cognates. For L2 

no effect of COGNATE-STATUS was observed in this epoch. 

300 - 500 ms epoch. 


significant main effects of COGNATE-STATUS at all columns (midline: F(1,41) = 8.86, p = 

0.005, c1: F(1,41) = 9.53, p = 0.004, c2: F(1,41) = 11.21, p = 0.002, c3: F(1,41) = 13.46, 

p = 0.001) as well as three-way interactions of LANGUAGE x COGNATE-STATUS x 

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ELECTRODE-SITE at all columns (midline: F(4,164) = 7.34, p < 0.001, c1: F(2,82) = 9.36, p 

= 0.001, c2: F(3,123) = 9.56, p < 0.001, c3: F(4,164) = 4.39, p = 0.021). 


two languages revealed effects of COGNATE-STATUS at all columns for L1 (midline: 

F(1,41) = 23.44, p < 0.001, c1: F(1,41) = 16.18, p < 0.001, c2: F(1,41) = 15.48, p < 0.001, 

c3: F(1,41) = 14.70, p < 0.001). These analyses suggest that during the English task noncognate 

words tended to produce more negative-going ERPs in this epoch than cognate 

words. For the L2 task (French target words) there were no main effects of COGNATE- 

STATUS, however, there were significant interactions of COGNATE-STATUS x ELECTRODE- 

SITE (midline: F(4,164) = 12.21, p < 0.001, c1: F(2,82) = 9.86, p = 0.001, c2: F(3,123) = 

14.59, p < 0.001, c3: F(4,1641) = 9.53, p = 0.001). As can be seen at Pz in Figure 4b 

while French non-cognates tended to be more negative-going at anterior and central sites, 

at the more posterior sites cognates tended to be more negative-going than non-cognates. 

500 - 800 ms epoch. 


significant main effects of COGNATE-STATUS in all four columnar analyses (midline: 

F(1,41) = 4.41, p = 0.042, c1: F(1,41) = 6.17, p = 0.017, c2: F(1,41) = 6.94, p = 0.012, c3: 

F(1,41) = 4.39, p = 0.042). There were also two-way interactions of LANGUAGE x 

ELECTRODE-SITE (midline: F(4,164) = 3.75, p = 0.026, c1: F(2,82) = 4.47, p = 0.021, c2: 

F(3,123) = 4.07, p = 0.034) and a three-way interaction of LANGUAGE x COGNATE-STATUS 

x ELECTRODE-SITE (midline: F(4,164) = 7.39, p = 0.001, c1: F(2,82) = 3.96, p = 0.039, c2: 

F(3,123) = 6.32, p = 0.004, c3: F(4,164) = 4.00, p = 0.027). 

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Figure 3a. Results of L2 learners reading L1 (English) items that are cognates or non-cognates 

Figure 3b. Enlargement of five sites from 3a. 

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Figure 4a. Results of L2 learners reading L2 (French) items that are cognates or non-cognates. 

Figure 4b. Enlargement of five sites from 4a. 

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Figure 5a. Scalp voltage maps at six time points showing the difference in voltage between L1 noncognate 

items and L1 cognate items (units are in microvolts) 

Figure 5b. Scalp voltage maps at six time points showing the difference in voltage between L2 noncognate 

items and L2 cognate items (units are in microvolts). 


two languages revealed no effects at any column for L1 (all p > .150). For L2, COGNATE- 

STATUS was marginally significant at midline and column 1 (F(1,41) = 3.83, p = 0.057, 

F(1,41) = 3.39, p = 0.073) and reached significance at columns 2 and 3 (F(1,41) = 5.78, p 

= 0.021, F(1,41) = 7.82, p = 0.008). As can be seen in Figure 4 non-cognates tended to be 

more negative-going than cognates at the more lateral sites in this epoch. 

Time-course analysis 

Table 1. Time-course analysis of the Cognate effect in 100 ms epochs at five midline sites. 

0-100ms 100-200ms 200-300ms 300-400ms 400-500ms 500-600ms 600-700ms 700-800ms 

L1 : FPz - - N~C N>>C - - C>>N C>>N 

Fz N>C N>>>C N~C - C>N - 

Cz N>>>C N>>>C N>C - - - 

Pz - N>C N>>>C N>>>C N>>C N>C N~C N>>C 

Oz - N>>C - - - N>>C 

L2 : FPz - - - - N>>>C N>C N~C - 

Fz - N>>>C N>>C N~C N~C 

Cz - N>C N>C - - 

Pz - - - C~N - N>C - - 

Oz C~N C>>>N - - - C~N 

C= cognates, N = non-cognates, letter on the left is more negative than the one on the right 

- ns, ~ p = 0.1, > p = 0.05, >> p = 0.01, >>> p = 0.001 

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Behavioral results 

Participants averaged 39.4 (SD = 1.7) out of 40 hits in their L1 (98.4%) and 34.2 

(SD = 4.3) out of 40 hits in their L2 (85.5%) for the animal probe words. Participants 

produced false alarms on an average of 0.8 items (SD = 1.1) in L1 (0.3%) and on 15.8 

items (SD = 5.7) in L2 (2.4%). In a post translation task participants were asked to 

translate all 240 L2 items that they had seen in the experiment. The mean number of 

correct translations was 175 (SD = 25.0) or 73%. 

Discussion 

In this experiment, testing a group of second language learners, we sought 

electrophysiological evidence for effects of cognate status reported in prior behavioral 

research. We recorded and compared ERPs to cognate and non-cognate words while 

participants were processing blocked lists of words in their L1 and their L2. ERP 

negativities in the region of the N400 component were found to be sensitive to cognate 

status in both language blocks. As in a number of previous behavioral studies (Dijkstra et 

al., 1999; Lemhöfer & Dijkstra, 2004; Lemhöfer et al., 2004; de Groot, 1992; Sánchez- 

Casas et al., 1992) there were robust effects of cognate status when participants were 

processing words in L2. In the present experiment ERPs were more negative for noncognates 

(i.e., larger N400s) than cognates, although this effect did not start until around 

300 ms and did not become widespread across the scalp until after 550 ms. Perhaps more 

interesting, because there have been fewer behavioral studies showing these effects, there 

were also cognate effects in the L1 block. Like L2, non-cognates were more negative than 

cognates, but this difference started earlier, in a 200-300 ms window. These effects were 

widespread across the scalp and continued through the traditional 300-500 ms N400 

window. 

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The principle effect of cognate status in the present experiment was therefore a 

reduced negativity (smaller N400 amplitude) to cognate words compared with noncognate 

words in both L1 and L2. This fits with the general hypothesis that the mapping 

of form to meaning is facilitated in cognate words. Other examples of an interpretation of 

reduced N400 amplitude as reflecting greater ease in mapping form onto meaning in 

single word recognition are effects of word frequency (Van Petten & Kutas, 1990; Münte 

et al., 2001) effects of orthographic neighborhood (Midgley et al., 2008; Holcomb et al., 

2002), and effects of masked primes (Holcomb & Grainger, 2006; 2007). 

However, perhaps the central finding of the present experiment is that of an 

influence of cognate status on word recognition in the first language (L1). Prior 

behavioral research had provided mixed findings on this particular issue. Several previous 

studies had not found cognate effects in L1 (Caramazza & Brones, 1979; Gerard & 

Scarborough, 1989) and others found an influence of cognate status on L1 items only in 

relatively proficient participants (van Hell & Dijkstra, 2002). Here, using 

electrophysiological measures, we were able to observe cognate effects in relatively low 

proficiency language learners processing words in their L1. 

The ERP data were also informative about the timing of cognate effects. These 

effects began to emerge at about 200 ms in L1, but not until about 400 ms in L2. In the 

introduction we hypothesized that the cognate advantage seen in behavioral research 

would reflect an accumulation of the benefits of exposure to a given form-meaning 

association across two languages. On this basis we not only expected to see effects of 

cognate status on processing L1 words, but we also were led to predict earlier effects of 

cognate status in L1 compared with L2 words. This is because the mapping between form 

and meaning, the hypothesized locus of the cognate advantage, should arise earlier in the 

processing of an L1 word than an L2 word. The results of the present experiment are in 

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line with this prediction, and therefore lend support to an account of cognate effects in 

terms of increased exposure to form-meaning associations. Again, as mentioned in the 

introduction, interpreting cognate effects as effects of cumulative exposure to the same 

(or similar) form-meaning associations does not imply that these words will be processed 

identically in each language. Language context is thought to have a global influence on 

lexical processing in L1 and L2, such that a cognate word will be processed like a word in 

L1 or L2 as function of the context. 

There is, however, an alternative interpretation of the difference in timing of 

cognate effects in L1 and L2 found in the present experiment. This interpretation is 

described within the framework of the revised hierarchical model (RHM) of second 

language vocabulary acquisition (Kroll & Stewart, 1994). In the RHM, beginning 

bilinguals first learn to map new word forms in the L2 onto their translation equivalents 

in L1. Hence meaning access from an L2 word is initially achieved via a translation route 

from the L2 word to its L1 translate, and from there, to the word meaning. Increased 

exposure to the L2 eventually allows the development of direct associations between L2 

word forms and meaning. Within this theoretical framework, one could argue that 

cognate words are particularly easy to process in the early phases of L2 acquisition given 

that their translations equivalents have the same or very similar orthographic forms. Noncognate 

words would be harder to process because of the increased difficulty in mapping 

the L2 form onto its translation equivalent in L1. This would therefore explain why the 

cognate effect arises quite late in processing L2 words, but it does not explain why there 

is an effect in L1. Extra exposure to form-meaning associations while learning an L2 

therefore remains one viable account of the early effects of cognate status found in L1. 

The pattern of effects found in L2 also differed with respect to the L1 pattern in one 

other notable way. That is the reversed cognate effect found in posterior sites at around 

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300 ms post-stimulus onset in L2. This might well reflect a conflict in the mapping of 

orthography to phonology that is exaggerated in the case of cognate words, since the 

same orthographic pattern maps onto two distinct pronunciations (e.g., the different 

pronunciations of the word “table” in French and English). The fact that this is only seen 

in L2 can be explained by the relative dominance of the L1 pronunciation over the L2 

pronunciation of cognate words. Furthermore, the timing of this putative phonological 

effect is in line with estimates of phonological influences on visual word recognition in 

monolinguals (e.g., Bentin, Mouchetant-Rostaing, Giard, Echallier, & Pernier, 1999; 

Grainger, Kiyonaga, & Holcomb, 2006). 

Are cognates special in any way that would not be predicted by a simple 

combination of shared form and meaning across languages? On the basis of the results of 

their masked priming study, Voga and Grainger (2007) suggested not. On the other hand, 

Van Hell and Dijkstra and others (e.g., De Groot et al., 2000; Dijkstra et al., 1998, 1999) 

have argued that cognates have a special type of representation in the mental lexicon, and 

cognate effects are not just cumulative frequency effects (i.e., that it is not just the sum of 

the frequencies of the cognate items across languages that is driving the cognate effect). 

They point to effects of “faux amis” or inter-lingual homographs as evidence against a 

cumulative frequency interpretation of cognate effects. Unlike cognates, inter-lingual 

homographs, whose accidental overlap of form with an absence of overlap of meaning 

(“four” in French means “oven”) show a disadvantage in processing, with slower RTs 

than control words. According to a cumulative frequency explanation of the cognate 

advantage, inter-lingual homographs should also show a processing advantage and they 

do not. However, the critical difference between cross-language homographs and cognate 

words is that homographs map onto different meanings in each language. Therefore, if as 

we hypothesize, it is the frequency of form-meaning mappings that underlies the cognate 

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advantage, one would not expect to see such an advantage for cross-language 

homographs. 

Nevertheless, there is one remaining problem with the form-meaning frequency 

account of cognate effects that we propose. This is that one would expect to see a much 

larger cognate effect in L2 than in L1, because L2 words should benefit from much larger 

amounts of exposure to L1 words than vice versa. There was no evidence for this in the 

present experiment, with effects of comparable magnitude in L1 and L2. As already 

suggested above, the fact that relatively low-proficiency bilinguals were tested in the 

present experiment might point to differences in ease of translation as the source of the 

cognate effect in L2. Thus, it could be that cognates do have a special status during the 

earliest phases of second language learning, and that this special status is gradually lost as 

proficiency in L1 increases. In order to investigate this possibility, future work should 

compare cognate effects in participants with different levels of proficiency in their L2. 

It is clear that more empirical work must be done to address questions like these, but 

it is always interesting to provide parsimonious explanations for language effects. In a 

bilingual context, parsimony could be achieved by turning to well documented, well 

understood and well modeled L1 lexical phenomena to explain L2 phenomena rather than 

developing a long list of particulars for L2 processing. A true universal account of 

language processing must parsimoniously describe both monolingual processing and 

bilingual processing and the representations and processes involved. 

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L'amorçage masqué par équivalent de traduction 

Chapitre 5 

L'amorçage masqué de répétition et par équivalent de 

traduction chez des apprenants en langue seconde : un regard 

sur le décours temporel de l'activation de la forme et du sens* 

La technique des potentiels évoqués et celle de l'amorçage masqué par équivalent de 

traduction ont permis d'examiner le décours temporel de l'activation de la forme et du 

sens pendant la reconnaissance de mots chez des apprenants en langue seconde. Les 

cibles étaient soit identiques et dans la même langue que l'amorce, soit des traductions de 

l'amorce, soit des items non reliés à l'amorce. Lors de la première expérience, les cibles 

étaient choisies dans la L2 des participants et, dans la deuxième, elles l'étaient dans la L1. 

En ce qui concerne le traitement en L2, les conditions d'amorçage de répétition et 

d'équivalent de traduction ont produit des effets sur les composantes N250 et N400. Pour 

le traitement en L1, seule la répétition a modulé la N250 tandis que les deux conditions 

d'amorçage ont eu des effets sur la N400. Ces résultats suggèrent une activation rapide 

des représentations sémantiques lors du traitement de la forme des mots écrits et 

permettent de supposer l'absence de connexions facilitatrices entre les représentations des 

traductions chez les apprenants en L2. Leurs implications dans les théories du traitement 

des mots chez les bilingues seront abordées. 

Mots-clefs : Bilinguisme, Acquisition en langue seconde, Reconnaissance visuelle des 

mots, N400, N250, Amorçage masqué 

________________________ 

* Article in press, Psychophysiology, August 2008 

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Masked Repetition and Translation Priming in Second Language Learners: 

A Window on the Time-Course of Form and Meaning Activation using ERPs 

Katherine J. Midgley 

Tufts University, Medford, Ma USA & CNRS & Université d'Aix-Marseille, 

Marseille, France 

Phillip J. Holcomb 

Tufts University, Medford, Ma USA 

Jonathan Grainger 

CNRS & Université d'Aix-Marseille, Marseille, France 

Address for correspondence: 

Katherine J Midgley 

Department of Psychology 

Tufts University 

Medford, MA 02155 USA 

kj.midgley@tufts.edu 

Voice: (617) 627-3521 

Fax: (617) 627-3181 

*This Research was supported by grant numbers HD043251 & HD25889. 

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Abstract 

ERPs and masked translation priming served to examine the time-course of form and 

meaning activation during word recognition in second language learners. Targets were 

repetitions of, translations of, or were unrelated to the immediately preceding prime. In 

Experiment 1 all targets were in the participants’ L2. In Experiment 2 all targets were in 

the participants’ L1. In Exp 1 both within-language repetition and L1-L2 translation 

priming produced effects on the N250 component and the N400 component. In Exp 2 

only within-language repetition produced N250 effects while both types of priming 

produced N400 effects. These results suggest rapid involvement of semantic 

representations during on-going form-level processing of printed words, and an absence 

of facilitatory connections between the form representations of non-cognate translation 

equivalents in L2 learners. The implications for bilingual theories of word processing are 

discussed. 

Keywords: Bilingualism, second language acquisition, visual word recognition, N400, 

N250, masked priming 

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Bilinguals and second-language learners provide an ideal testing ground for general 

theories of how form and meaning representations interact during language 

comprehension. They also represent a fascinating example of the versatility with which 

humans manipulate abstract symbols in order to communicate complex information. 

Learning a second language (once a first language has been acquired) involves acquiring 

a new set of arbitrary forms to re-represent a pre-established set of concepts (although 

some new concepts will of course be acquired with the new language). This likely 

involves at least a partial restructuring of the form representations in the first language, as 

proposed by two prominent models of bilingual word comprehension and second 

language learning – the Revised Hierarchical Model (RHM, Kroll & Stewart, 1994) and 

the Bilingual Interactive Activation (BIA) model (Grainger & Dijkstra, 1992; van 

Heuven, Dijkstra, & Grainger, 1998). According to the RHM, newly acquired lexical 

form representations in L2 are connected to their equivalent lexical form representations 

in L1 in order to facilitate access to semantics. According to the BIA model, the newly 

acquired lexical form representations are gradually integrated into a common network of 

lexical form representations for both languages. One specific goal of the present study is 

to test the predictions of these two models with respect to effects of non-cognate 

translation primes (i.e., translation equivalents having minimal form overlap). 

A more general goal of the present study is to investigate the nature of formmeaning 

interactions at the level of individual words. Part of that general endeavor 

involves describing exactly when semantic information becomes available during visual 

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word recognition, and the nature of the form-level processing that is necessary for that to 

occur. Demonstrations of early involvement of semantics during visual word recognition 

are few and far between. Standard semantic priming effects (e.g., bread-butter) are easily 

obtained when primes are clearly visible and targets immediately follow primes (e.g., 

Meyer & Schvaneveldt, 1971). However, when prime exposure duration is reduced such 

that primes are barely visible, then the standard result is no semantic priming, but 

significant form priming effects (e.g., teble-table). This is true for behavioral studies (e.g., 

Rastle, Davis, Marslen-Wilson, & Tyler 2000), and for electrophysiological studies (e.g., 

Holcomb et al., 2005; Holcomb & Grainger, submitted). 1 This pattern therefore fits with 

models of visual word recognition according to which form-level processing must be 

complete (or close to completion) before any semantic-level information can be accessed 

(e.g., Forster, 1976). In cascaded activation models, on the other hand, semantic-level 

processing ought to follow form-level processing very rapidly (McClelland, 1979; 

McClelland & Rumelhart, 1981). According to this account, as soon as form 

representations are even partially activated by a given stimulus, activation immediately 

starts to spread to higher levels. 

The rather weak evidence for any early semantic activation obtained using the 

standard semantic priming paradigm might, however, be due to the relatively weak 

manipulation involved, and the fact that there is no general consensus as to how to 

measure semantic relatedness. Non-cognate translation equivalents (e.g., the English 

word “tree” and its French translation “arbre”) arguably provide the closest possible 

1 There is some controversy surrounding the presence/absence of N400 masked semantic priming effects. 

While Deacon et al. (2000), Kiefer (2002) and Grossi (2006) have reported significant N400 effects in 

masked semantic priming experiments, Holcomb et al. (2005) have shown that masked semantic priming 

N400 effects are predicted by conscious awareness of the prime. This suggests that monolingual masked 

semantic priming is unreliable at best and is most likely due to conscious processing of the primes. 

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semantic relation between two distinct word forms. They therefore provide an ideal 

testing ground for the interplay between form-level and semantic-level processes during 

visual word recognition. 

However, in line with the rather weak evidence for masked within-language 

semantic priming effects, behavioral studies investigating masked non-cognate translation 

priming effects have also produced mixed results. One standard finding in this area is that 

close-cognates (e.g., the English word “chair” and its French translation “chaise”) 

generate stronger priming effects than non-cognates (De Groot & Nas, 1991; Gollan, 

Forster, & Frost, 1997; Sanchez-Casas et al., 1992). Evidence for significant effects of 

non-cognate translation primes has mostly been obtained in language pairs with different 

scripts, such as Japanese and English, Hebrew and English or Greek and French 

(Finkbeiner, Forster, Nicol, & Nakamura, 2004; Gollan et al., 1997; Voga & Grainger, 

2007). The change in script across prime and target would allow improved processing of 

masked primes by providing the lexical processor with a distinct cue as to which 

language the word belongs to. However, robust non-cognate priming was reported by 

Grainger and Frenck-Mestre (1998) in same-script conditions (English-French 

bilinguals), but the effect was only robust when participants had to perform a semantic 

categorization task on target words (see Finkbeiner et al. 2004, for a replication with 

Japanese-English bilinguals). In the Grainger and Frenck-Mestre study, non-cognate 

translation primes did not significantly facilitate lexical decision responses to target 

words. The presence of translation priming in a semantic categorization task and not in 

the lexical decision task suggests that the effect is indeed semantically mediated, and not 

the result of direct form-level connections between translation equivalents as postulated 

in the RHM of Kroll and Stewart (1994). 

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The present study combines masked within-language and between-language (i.e., 

non-cognate translation) priming with ERP recordings in order to: a) examine the relative 

contributions of form and meaning based representations in bilingual word processing, b) 

have a potentially overall more sensitive measure of priming effects, and c) provide finer 

grained information about the time-course of priming effects both within and betweenlanguages. 

Two prior ERP studies have examined unmasked non-cognate translation 

priming effects. (Alvarez et al., 2003; Phillips et al, 2006). 2 Of particular relevance to the 

current study is one by Alvarez et al. Using visually presented words these authors found 

evidence for translation priming effects in the N400 component that were larger and 

started earlier when primes were in L2 and targets in L1. This result is in line with the 

predictions of the RHM (Kroll & Stewart, 1994). According to this model, L2 words 

should automatically activate their L1 translate, and should do so to a greater extent and 

more rapidly than L1 words activate their L2 translate. However, there is an alternative 

interpretation of the Alvarez et al findings, Because the SOA in their study was 2700 ms 

and the primes were unmasked translation priming might have been due to participants 

using an overt translation strategy. If this strategy was employed it would presumably be 

used primarily in one direction to aid in L2 comprehension. In other words the L2 items 

during the long SOA would be overtly translated into L1 in order to facilitate the semantic 

categorization decision required on each trial and the resulting priming on subsequent L1 

targets would actually be more like L1-L1 priming. In the current study we rectify the 

problems of the Alvarez et al study by using masked priming and by blocking by 

language. This combination should minimize the possibility of any strategic influences on 

2 Unlike the Alvarez et al. study and the current study the bilinguals in the Phillips et al. study were nearly 

equally competent in both languages and the stimuli were auditory which makes comparisons between 

studies difficult. However, Phillips et al. did report asymmetrical N400 effects for within and betweenlanguage 

priming on the N400. 

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processing as participants should be unaware of the occurrence of primes in the non-target 

language and therefore should not engage in overt prime translation (Forster et al., 2002). 

Blocking by language for target words should also minimize the bilingual nature of the 

study because participants should only be aware of words in a single language in each 

block. This is important because it has been suggested (Grosjean & Miller, 1994) that 

bilinguals may have different processing modes; one for situations where both the 

bilinguals languages are required and one for monolingual situations. In the current 

experiment we were interested in biasing the participants towards monolingual processing 

in order to more clearly explore the more automatic aspects of interactivity between 

languages, that is, those not under strategic control. 

In recent research, the masked priming paradigm has been combined with ERP 

recordings to successfully map out the time-course of component processes in visual 

word recognition (e.g., Grainger et al., 2006; Holcomb & Grainger, 2006; Kiyonaga et al., 

2007). Holcomb and Grainger (2006) described a cascade of ERP components found to 

be sensitive to their repetition priming manipulation. The first of these relevant to the 

current study is the N250, a negative-going component which peaks near 250 ms. 

Holcomb and Grainger reported that the N250 was more negative and had a slightly 

earlier peak latency to target words that were not full repetitions of or that had no overlap 

with their primes. Full repetitions produced the least N250 activity. Holcomb and 

Grainger postulate that the N250 reflects processes in visual word recognition where 

sublexical form representations (letters and letter combinations) are mapped onto the 

lexical system. The second component of relevance here was the N400, a negativity that 

starts around 350 ms and peaks between 400 and 600 ms. The N400 was more negative 

for unrelated items than for items that were partial repetitions and was least negative for 

fully repeated items. The results of a host of studies are consistent with the hypothesis 

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that the N400 reflects some aspect of semantic processing (e.g., Kutas & Hillyard, 1980; 

Kounios & Holcomb, 1992, 1994). Given the influence of partially overlapping nonword 

primes (e.g., teble-table), Holcomb and Grainger (2006) argued however, that the N400 

may also be sensitive to processing at the interface between whole-word form 

representations and semantics. 

In order to obtain an improved picture of the time-course of form and meaning 

activation both within and between the lexical and semantic systems of second language 

learners, the present study compares within-language repetition priming and non-cognate 

translation priming using the same paradigm as Holcomb and Grainger (2006). This 

methodology should allow us to observe and compare the time course of processing 

during L1 and L2 repetition priming as well as translation priming in both directions (L1- 

L2, L2-L1). The N250 and N400 ERP components will be used to infer form-level and 

semantic-level influences on processing. Even if these two components reflect to some 

extent a combination of form and semantic influences, we expect form-level influences to 

be greater on the N250, and semantic level influences to be greater on the N400. This 

then allows us to test the predictions of the RHM (Kroll & Stewart, 1994) and BIA model 

(Grainger & Dijkstra, 1992). In the RHM there are stronger links from L2 to L1 than from 

L1 to L2 lexical form representations, and weaker links between L2 lexical 

representations and meaning than between L1 lexical representations and meaning. L2 

primes should therefore affect form-level processing of the upcoming translate in L1, 

modulating the N250 component, and in consequence the N400. L1 primes, on the other 

hand, should mostly affect semantic level processing of upcoming L2 translates, and 

therefore only modulate the N400 component. According to the BIA model, translation 

priming is always semantically mediated (i.e., there are no excitatory connections 

between lexical form representations of translation equivalents), hence most of the effects 

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should be evident in the N400. Some priming effects are nevertheless expected on the 

N250 component via feedback from semantics to lexical representations (Voga & 

Grainger, 2007), and these should be most evident with L1 primes and L2 targets, simply 

because it is assumed that L1 words are processed more rapidly and efficiently than L2 

words. If this is indeed the case, we should also observe smaller and later effects in L2-L2 

repetition priming than L1-L1 repetition priming. 

Experiment 1 

In Experiment 1, ERP masked repetition priming effects of both within and crosslanguage 

primes (L2 – L2 repetition priming and L1 to L2 translation priming) on L2 

targets were measured in a 67ms SOA prime-target paradigm designed to decompose the 

different components elicited by priming. In this experiment all visible items are targets 

in participants’ L2. Masked primes are either L1 or L2 words. 

Methods 

Participants. Thirty-six participants (32 female, mean age = 20.3 SD = 1.2) were 

recruited during their second year of the English studies at the Université de Provence in 

Aix-en-Provence, France and paid for their participation. All were right handed 

(Edinburgh Handedness Inventory - Oldfield, 1971) and had normal or corrected-tonormal 

visual acuity with no history of neurological insult or language disability. French 

was reported to be the first language learned by all participants (L1) and English their 

primary second language (L2). All participants began their study of English in their sixth 

year of primary school at approximately the age of 12 years, as is customary in the French 

school system. 

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Participants’ auto-evaluation of English and French language skills were surveyed 

by questionnaire. On a seven point Likert scale (1 = unable; 7 = expert) participants 

reported their abilities to read, speak and comprehend English and French as well as how 

frequently they read in both languages (1 = rarely; 7= very frequently). The overall 

average of self-reported languages skills in French was 6.8 (SD = 0.1) and in English was 

4.9 (SD = 0.1). Our participants reported their average frequency of reading in French as 

6.4 (SD = 0.9) and in English as 5.4 (SD = 1.3). After the experiment participants were 

asked to translate all of the L2 target words that they saw into their L1. The mean score 

on this post-test was 82.4% (SD = 9.0, range 63.9% to 97.7%.). 

Stimuli The critical stimuli for this experiment were 400 four to eight letter English 

words and their translations into French. The English items had a mean CELEX 

(http://www.ru.nl/celex) log frequency of 1.74 (SD = 0.61, range 0.00 - 3.51). The French 

items had a mean Lexique (New et al., 2001) log frequency of 1.65 (SD = 0.63, range 

0.00 – 3.14). The correlation of the log frequencies of the English and French items was 

0.74 (p < .001). In selecting items care was taken to avoid any cross language 

homophones (e.g., lasse-lace) as well as cross language homographs (e.g., "coin" 

meaning corner in French). Overly polysemous words were also avoided (e.g., carte in 

French could mean map, menu or card in English). Words with accents were excluded, to 

prevent the eventual identification of French items in the prime position and (important in 

Experiment 2 where all targets are in caps and in French) because the use of accents in 

upper case French words is non-standardized (état could be written ETAT or ÉTAT, or 

PASSE could be passe or passé). Finally all stimuli were morphemically simple items. 

The non-critical stimulus pairs (used in probe trials) were formed by combining four to 

eight letter English animal names with unrelated non-animal words. 

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For both the critical and probe trials, the first stimulus was referred to as the prime 

and the second as the target. Primes were presented in lower case letters and targets in 

upper case (this was done in order to minimize the physical similarity between repeated 

items). Stimulus lists consisted a pseudorandom mixture of trials where the target was a 

full repetition of the prime in L2 (e.g. beach - BEACH), trials where the prime was an L1 

translation of the target (e.g. plage - BEACH), trials where the prime and target were 

unrelated L2 words (e.g. sleep - BEACH) and trials where the prime was an L1 word 

unrelated to the L2 target (e.g. miel - BEACH). Lists were formed so as participants saw a 

subset of 40 of the 400 critical items in each condition. Across lists (and participants), 

each target word appeared in each of the four conditions (REPETITION, 

TRANSLATION, UNRELATED WITHIN LANGUAGE, UNRELATED ACROSS 

LANGUAGE), but within lists each target stimulus was presented only once. An 

important feature of this design is that the prime and target ERPs in the repeated, 

translation and unrelated conditions are formed from exactly the same physical stimuli 

(across participants) which should reduce the possibility of ERP effects across conditions 

due to differences in physical features or lexical properties. 

Each list also contained 36% non-critical trials, half of which had an English animal 

name in the prime position and an English filler word in the target position and the other 

half of which had an unrelated filler word in the prime position and an English animal 

name in the target position. The animal names served as probe items in a go/no-go 

semantic categorization task in which participants were instructed to rapidly press a 

single button whenever they detected an animal name. Participants were told to read all 

other words passively without responding (i.e., critical stimuli did not require an overt 

response). Probe items were placed in the prime position to serve as a measure of prime 

detectability and provide an objective measure of the effectiveness of the masking 

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procedure. A practice session was administered before the main experiment to familiarize 

the participant with the task. 

Procedure Visual stimuli were presented on a 15” monitor set to a refresh rate of 60 Hz 

(which allows 16.67 ms resolution of stimulus control) and located 143 cm directly in 

front of the participant. Stimuli were displayed at high contrast as white letters on a black 

background in the Verdana font (letter matrix 20 pixels wide x 40 pixels tall). Each trial 

began with a forward mask of 12 hash marks (############) presented for a duration of 

200ms. The forward mask was replaced at the same location on the screen by a lower 

case prime item for 50ms. The prime was then immediately replaced by a 10 character 

uppercase random consonant string backward mask (ZJGRRFMXHG). The backward 

mask remained on the screen for 17ms (one frame) and was immediately replaced by the 

target in upper case letters for a duration of 300 ms. All target words were followed by a 

1000ms blank screen which was replaced by a blink stimulus (see Figure 1). The 

participants were instructed to blink only during the 1500ms that this stimulus was on the 

screen. The blink stimulus was followed by 500ms of blank screen after which the next 

trail began. 

Figure 1. A typical trial. Here an L1-L2 translation prime. 

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EEG recording procedure Participants were seated in a comfortable chair in a sound 

attenuated darkened room. The electroencephalogram (EEG) was recorded from 29 active 

tin electrodes held in place on the scalp by an elastic cap (Electrode-Cap International – 

see Figure 2). In addition to the 29 scalp sites, additional electrodes were attached to 

below the left eye (to monitor for vertical eye movement/blinks), to the right of the right 

eye (to monitor for horizontal eye movements), over the left mastoid bone (reference) and 

over the right mastoid bone (recorded actively to monitor for differential mastoid 

activity). All EEG electrode impedances were maintained below 5 kΩ (impedance for eye 

electrodes was less than 10 kΩ). The EEG was amplified by an SA Bioamplifier with a 

bandpass of 0.01 and 40 Hz and the EEG was continuously sampled at a rate of 200 Hz 

throughout the experiment. 

Figure 2. Electrode montage and four analysis columns used for ANOVAs. 

Data analysis Averaged ERPs time-locked to target onset were formed off-line 

from trials free of ocular and muscular artifact (less than 10% of trials) and were 

bandpass filtered at .5 and 15 Hz. Four types of targets were formed from two levels of 

PRIMING-TYPE (within language v. between language) and two levels of REPETITION 

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(repeated vs. unrelated, note that between language repetition is L1-L2 translation 

priming, e.g., plage-BEACH). The main analysis approach involved measuring mean 

amplitudes in three temporal epochs surrounding the two primary repetition ERP effects 

reported by Holcomb and Grainger: the N250 and N400. To best capture activity in the 

N250 epoch we selected a typical window surrounding the component from 200-300 ms. 

To best capture N400 activity, which varied in its time-course as a function of language 

and priming (see Figures 3a and 3b), we selected two windows, the first of which was 

within the range typical for this component in many previous L1 studies (350ms-500ms) 

and a second which was later (500-650 ms) and more in line with the later time-course of 

the N400 for L2 translation priming reported by Alvarez et al (2003). Separate repeated 

measures analyses of variance (ANOVAs) were used to analyze the data in each of these 

three epochs. The Geisser-Greenhouse (1959) correction was applied to all repeated 

measures with more than one degree of freedom in the numerator. Separate follow-up 

analyses for the within- and between-language conditions were performed in cases of 

significant REPETITION by PRIME-TYPE interactions. 

In order to thoroughly analyze the full montage of 29 scalp sites we employed an 

approach to data analysis that we have successfully applied in a number of previous 

studies (e.g., Holcomb et al., 2005). In this scheme the 29 channel electrode montage is 

divided up into seven separate parasagittal columns along the antero-posterior axis of the 

head (see Figure 2). The electrodes in each of three pairs of lateral columns and one 

midline column are analyzed in four separate ANOVAs. Three of these analyses (referred 

to as Column 1, Column 2 or Column 3) involved an anterior/posterior ELECTRODE- 

SITE factor with either three, four or five levels, as well as a HEMISPHERE factor (Left 

vs. Right). The forth “midline” analysis included a single anterior/posterior 

ELECTRODE-SITE factor with five levels. 

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Results 

Visual Inspection of ERPs 

The ERPs time locked to targets from 29 electrode sites for the repetition and 

translation priming conditions are plotted in Figure 3a&b. Figure 4 presents enlargements 

of the CP1 and CP2 sites from Figure 3. Figures 5 and 6 are the voltage maps for the 

repetition and translation priming conditions for time periods surrounding the N250 and 

N400. As can be seen in Figure 3, ERPs in the target epoch varied substantially as a 

function of both the REPETITION and the PRIMING-TYPE factors. In looking over 

these plots one must keep in mind that at the short SOA used in this experiment, the ERPs 

time locked to the target are a composite of neural activity generated by both the target 

and the immediately preceding prime and masking stimuli. The influence of the pre-target 

stimuli can be seen in the sequence of positive and negative peaks which start prior to the 

vertical calibration bar and run through the first 150 ms of the target epoch. However, 

starting at about 150-200 ms the morphology of the waveforms more closely conform to 

typical target ERP components which include the anteriorally distributed P2 peaking at 

approximately 180 ms post-target onset and more posterior negativities probably 

reflecting N1 target activity also peaking just before 200 ms. Starting at approximately 

180 ms the various independent variables appear to start exerting their influence on the 

ERPs. In the following sections we detail these effects in each of four measurement 

windows. 

Analyses of ERP Data 

N250: 200 - 300 ms epoch. In this epoch an omnibus ANOVA on the mean amplitudes 

between 200 and 300 ms produced a main effect of PRIMING-TYPE at all columns 

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(midline: F(1,19) = 14.694, p = 0.001; C1: F(1,19) = 10.034, p = 0.003; C2: F(1,19) = 

11.953, p = 0.001; C3: F(1,19) = 15.535, p < 0.000) indicating that target ERPs were 

more negative going for trials with a language switch between the prime and target (i.e., 

L1-L2) than for trials where both the prime and target were in the same language (i.e., 

L2-L2). The main effect of REPETITION was also significant at all columns (midline: 

F(1,19) = 5.071, p = 0.031; C1: F(1,19) = 5.162, p = 0.029; C2: F(1,19) = 5.562, p = 

0.024; C3: F(1,19) = 7.746, p = 0.009) indicating that targets following unrelated primes 

were more negative-going than targets that were repetitions or translations of the primes. 

Although there was not a significant interaction between REPETITION and 

PRIMING-TYPE, examination of Figures 3 to 6 suggests that the negativity in this 

measurement window has a somewhat different time-course for the within-language and 

between-language conditions. To assess this visual impression we employed an analysis 

strategy used by Phillips et al (2006) for analyzing the time-course of bilingual priming. 

We divided the theN250 epoch into two sub-windows, an earlier 200-250 ms epoch and a 

later 250-300 ms epoch. TIME EPOCH was then entered as an additional factor into the 

ANOVA. These analyses resulted in significant TIME EPOCH (early vs. late) by 

REPETITION by PRIMING-TYPE by HEMISPHERE interactions in the C2 and C3 

columns (C2: F(1,35) = 5.08, p = .031; C3: F(1,35) = 6.29, p = .017; marginal C1: 

F(1,35) = 2.90, p = .098). Following these significant interactions we then used separate 

follow-up analyses of the two priming types to better characterize the interactions in each 

sub-epoch for the three lateral analysis columns (C1, C2 and C3). In the earlier window 

(200-250 ms) only the within-language comparison resulted in significant REPETITION 

effects (C1: F(1,19) = 3.635, p = 0.065; C2: F(1,19) = 5.606, p = 0.024; C3: F(1,19) = 

5.477, p = 0.025). However, in the later epoch (250-300 ms) there were no significant 

REPETITION effects for the within-language condition (all Fs < 3; p > .098), but in the 

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between language condition there were significant interactions between REPETITION 

and HEMISPHERE at all three lateral columns (C1: F(1,19) ) = 4.617, p = 0.039; C2: 

F(1,19) = 4.237, p = 0.047; C3: F(1,19) = 6.793, p = 0.013). As can be seen in Figures 4 

and 6 these later effects were due to the between-language REPETITION effect being 

larger over the right hemisphere in this later epoch. 

N400 early: 350-500 ms epoch. There was a REPETITION by ELECTRODE SITE 

interaction at the midline sites (F(4, 140) = 4.34, p = .026; marginal at C3:F(4,140) = 

3.51, p = .054) indicating that the small REPETITION effect in this window tended to be 

larger at central and posterior sites. There were no interactions between REPETITION 

and PRIME_TYPE in this epoch (all Fs < 1.0). 

N400 late: 500-650 ms epoch. There were robust effects of REPETITION across the 

four analysis columns (midline: F(1,35) = 5.18, p = .029; C1: F(1,35) = 5.28, p = .028; 

C2: F(1,35) = 4.81, p = .035; C3: F(1,35) = 4.90, p = .033) with unrelated targets 

producing more negative-going responses. At the midline and more lateral columns this 

effect tended to be larger at posterior sites as indicated by significant REPETITION by 

ELECTRODE SITE interactions (midline: F(4,140) = 6.39, p = .005; C2: F(3, 105) = 

5.92, p = .011; C3: F(4,140) = 6.59, p = .007). There were no significant REPETITION 

by PRIME-TYPE interactions in this epoch (all Fs < 2.2). 

Behavioral Data 

Participants detected 81.5% (SD = 6.6) of animal probes in the target position and 

had on average 1.9 false alarms (SD = 2.4). No participants detected, or pressed to any 

animal probes in the prime position and no participants reported seeing any primes, 

during debriefing at the end of the experiment. 

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Figure 3a-b. ERPs time locked to L2 target onset in the repeated (solid) and unrelated (dashed) 

conditions for the: (a) within-language (L2-L2) and (b) between-language (L1-L2) comparisons. In 

this and all subsequent ERP figures negative voltages are plotted upward and target onset is 

indicated by the vertical calibration bar marked by the arrow with a “T” below it in the lower left 

time scale legend (prime onset, which was 67 ms earlier, is marked by the arrow with a “P” below it). 

Refer to Figure 2 for electrode locations. 

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Figure 5. Voltage maps calculated from difference waves (Unrelated-Repeated) for the withinlanguage 

condition at each of nine time points encompassing the N250 and N400 epochs (L2 – L2 

priming). 

Figure 4. Enlargement of CP1 and CP2 sites from Figure 3a & b. ERPs are time-locked to targets in 

L2. 

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Figure 6. Voltage maps calculated from difference waves (Unrelated-Translation) for the betweenlanguage 


priming). 

Discussion 

As in several recent ERP studies (e.g., Holcomb & Grainger, 2006; Chauncey et al., 

2008), two negativities; the first peaking at around 250 ms (N250) and the second after 

400 ms (N400) were modulated by repetition. The N250 has been argued to reflect the 

mapping of sublexical orthography onto lexical representations and the N400, the 

mapping of lexical form onto meaning (Grainger and Holcomb, in press). The effects on 

the N400 are consistent with two previous studies of unmasked repetition priming in L2 

and translation priming from L1 to L2 (Alvarez et al., 2003; Phillips et al., 2006). 

Likewise the extended time-course of the N400 translation priming effect found here is 

also consistent with these previous studies. 3 

New here is the observation that when 

3 The continuation of the priming effects into the 550-650 ms range might appear too late to be an N400 

effect. Therefore it would be reasonable to entertain the alternative interpretation that the effects may reflect 

a late positive component. However Alvarez et al. (2003) and Phillips et al. (2006) both showed prolonged 

N400 effects in the case of L1-L2 translation priming and to a lesser extent for L2-L2 priming. Moreover at 

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primes are masked repetition effects occur within a second language (L2-L2) on both the 

N400 and the earlier N250. This is important proof that our L2 prime words were being 

effectively processed in the extreme masking conditions used in the present study. 

Also new here is the finding of a clear modulation of both the N250 and N400 

components when the prime words were presented in L1 and the targets in L2. This is a 

critical finding given that there was minimal form overlap in the non-cognate translation 

equivalents used in the present study. This therefore suggests a semantic influence on 

processing that is reflected in the N250 component. The architecture of the BIA model 

(Grainger & Dijkstra, 1992; van Heuven et al., 1998) enables such semantic influences on 

lexical form representations. For the RHM (Kroll & Stewart, 1994), on the other hand, 

such influences could arise via direct connections between lexical representations of 

translation equivalents. However, given the asymmetrical nature of these connections, the 

RHM predicts relatively weak effects from L1 to L2, which should be amplified when 

primes are in L2 and targets in L1. Experiment 2 tests this prediction by presenting all 

targets in L1. 

Experiment 2 

In Experiment 2, ERP masked repetition priming effects of both within and crosslanguage 

primes (L1 – L1 repetition priming and L2 to L1 translation priming) on L1 

targets were measured in a 67ms SOA prime-target paradigm that was procedurally 

identical to Experiment 1 except that the targets were in participants’ L1 while masked 

primes were in both L1 and L2. 

least one previous study has concluded that LPC repetition effects are non-existent or greatly attenuated in 

masked priming (Misra, 2003), So it would seem that the most parsimonious explanation is that the late 

negative difference is due to a prolonged N 

400 for words processed in L2. 

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Methods 

Participants The same 36 participants who served in Experiment 1 also participated in 

this experiment. 

Stimuli and procedure. The critical and non-critical stimuli were the same as in 

Experiment 1 but the lists were constructed and counter-balanced with all of the targets in 

L1 (French). The lists were constructed with subsets of 400 critical items from each 

language so that there would be no repetition of primes or targets for any given 

participant between Experiment 1 and 2. The order of the experiments was 

counterbalanced across participants. The timing of the masked priming paradigm, the 

procedure and the laboratory were the same as in Experiment 1, as well as the EEG 

recording, electrode montage and the data analysis. The time between the experiments 

was varied according to the availability of the participants, from same day to four weeks. 

The order of the experiments was varied across participants. 

Data analysis The same approach to data analysis as Experiment 1 was used for 

Experiment 2. 

Results 

Electrophysiological Data 

Visual Inspection of ERPs 

The ERPs time locked to targets from 29 electrode sites for the repetition and 

translation priming conditions are plotted in Figure 7a&b. Figure 8 presents enlargements 

of the CP1 and CP2 sites from Figure 7. Figures 9 and 10 are the voltage maps for the 

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REPETITION effect in the within-language priming condition and the between-language 

priming condition for time periods surrounding the N250 and N400. As can be seen in the 

Figure 7 plots, ERPs in the target epoch varied substantially as a function of both the 

REPETITION and the PRIMING-TYPE factors. 

Analyses of ERP Data 

N250: 200 - 300 ms epoch. The omnibus ANOVA on the mean amplitudes between 200 

and 300 ms produced an interaction between REPETITION and PRIMING-TYPE at all 

columns (midline: F(1,19) = 5.046, p = 0.031; C1: F(1,19) = 4.873, p = 0.034; C2: 

F(1,19) = 5.482, p = 0.025; C3: F(1,19) = 7.110, p = 0.012). To better understand this 

interaction separate follow-up analyses of the two priming types were run. In these 

analyses there were significant effects of REPETITION at all columns for the withinlanguage 

condition (midline: F(1,19) = 8.203, p = 0.007; C1: F(1,19) = 8.339, p = 0.007; 

C2: F(1,19) = 8.502, p = 0.006; C3: F(1,19) = 12.371, p = 0.001). No significant effects 

were found for the between-language condition in this epoch (all Fs < 1 – see Figures 7, 8 

and 10). 

N400 early: 350-500 ms epoch: In this window there were again significant 

REPETITION by PRIME-TYPE interactions (midline: F(1,35) = 4.69, p = .037; C1: 

F(1,35) = 6.14, p = .018; C2: F(1,35) = 6.59, p = .015; C3: F(1,35) = 5.78, p = .022). To 

better understand these interactions separate follow-up analyses of the two priming types 

were run. For the within-language condition there were significant REPETITION effects 

(midline: F(1,35 = 7.77, p = .009; C1: F(1,35) = 10.28, p = .003, p = ; C2: F(1,35) = 

10.75, p = .002; C3: F(1,35) = 7.63, p = .009) and significant REPETITION by 

ELECTRODE SITE effects (midline: F(4,140) = 6.69, p = .003; C2: F(3,105) = 4.50, p = 

.023; C3:F(4,140) = 4.99, p = .015). Examination of Figures 7a, 8 and 9 reveals that the 

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unrelated targets were more negative-going across the scalp than were the repeated 

targets. Unlike the previous epoch there were now also significant REPETITION by 

ELECTRODE SITE effects for the between-language condition (midline: F(4,140) = 

3.56, p = .034; C3: F(4,140) = 4.10, p = .032). However, while the within-language 

REPETITION effect was due to consistently more negative going potentials for unrelated 

compared for repeated targets across the scalp, for the between-language REPETITION 

there was a negative-going effect at the back of the head (unrelated more negative than 

translation targets), but a reversed positive-going pattern at more frontal sites (see Figures 

8b and 10). This latter effect took the form of a more positive potential for unrelated 

compared to translation targets. 

N400 late: 500-650 ms epoch: In this temporal window there were again significant 

interactions between REPETITION, PRIME-TYPE and ELECTRODE SITE at the 

midline and the more lateral sites (midline: F(4,140) = 4.17, p = .023; C2: F(3,105) = 

3.30, p = .061; C3: F(4,140) = 3.98, p = .03). Separate follow-up analyses for the two 

prime types did not reveal any significant REPETITION effects for the within-language 

contrasts (all Fs < 1). However, like the previous epoch the between-language contrast 

revealed a posterior negativity for unrelated compared to translation targets, and an 

anterior positivity for this same contrast (REPETITION by ELECTRODE SITE effect, 

midline: F(4,140) = 4.54, p = .02; C3: F(4,140) = 3.88, p = .039). 

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Figure 7a-b. ERPs time locked to L1 target onset in the repeated (solid) and unrelated (dashed) 

conditions for the: (a) within-language (L1-L1) and (b) between-language (L2-L1) comparisons. All 

else is as in Figure 3. 

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Figure 8a. Enlargement of sites CP1 and CP2 from Figure 7a & b. Targets in L1. 

Figure 8b. Enlargement of sites Fpz and Oz from Figure 7a & b. Targets in L1. 

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Figure 9. Voltage maps calculated from difference waves (Unrelated-Repeated) for the withinlanguage 


priming). 

Figure 10. Voltage maps calculated from difference waves (Unrelated-Repeated) for the betweenlanguage 


priming). 

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Behavioral Data 

Participants detected 95.7% (SD = 5.5) of animal probes in the target position and 

had on average 0.75 false alarms (SD = 0.8). No participants reported seeing any primes, 

even when prompted. Two participants detected, or pressed to one animal probe in the 

prime position each. These were presumably false alarms to the targets associated to these 

animal probe primes. 

Discussion 

As in Experiment 1 we again found robust ERP repetition priming effects when the 

prime and target were within the same language. These effects replicate those of 

Holcomb and Grainger (2006) finding similar N250 effects and N400 effects for 

repetition priming. Moreover, the N400 effect for L1-L1 priming did not extend past the 

traditional N400 window as it did in Experiment 1 for L2-L2 priming. Also, unlike 

Experiment 1, but compatible with the bulk of the behavioral literature examining L2-L1 

priming (e.g., Jiang, 1999), we found no evidence of a translation priming in the N250 

epoch, although there was evidence of such priming in both the early and late N400 

measurement epoch. The nature of these N400 effects was not like that found in 

Experiment 1 for translation priming. In Experiment 1 both within and between-language 

priming in the N400 windows appeared to modulate a broadly distributed negativity. In 

Experiment 2, within-language priming followed this same pattern (although it terminated 

earlier). However, the between-language contrast revealed a very different pattern with 

what appeared to be a posterior N400 effect but a reversed anterior positive-going effect. 

Finally, it is important to contrast the total absence of between-language priming 

(L2-L1) in the N250 component in Experiment 2 with the presence of within-language 

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(L2-L2) priming found in Experiment 1. The absence of translation priming effects in this 

ERP component when primes are in L2, in association with the robust effects found in 

Experiment 1 when primes are in L1, counters the predictions of the RHM and provides 

support for the BIA model. The full implications of these findings are discussed below. 

General Discussion 

The present study tested within-language repetition priming and between-language 

non-cognate translation priming in second language learners using the masked priming 

paradigm and ERP recordings. It was argued in the Introduction that this paradigm offers 

a strong test of the time-course of interactivity at the lexical and semantic level of 

representation between a bilingual’s two language systems. It was also pointed out that 

non-cognate translation priming is an ideal testing ground for semantic priming effects in 

the absence of form overlap across primes and targets. On the basis of prior work 

combining masked priming and ERPs (e.g., Holcomb & Grainger, 2006) we expected to 

observe within-language repetition effects in an early component (N250), thought to 

reflect sublexical processing, and both within-language repetition priming and between 

language translation priming in the later N400 component (thought to at least partly 

reflect semantic-level processing). 

The N400 was found to be sensitive to non-cognate translation priming, in both 

directions, although the distribution of the effect and the presence of a temporally 

coincident anterior positive effect in Experiment 2 suggest that there are likely 

differences in the mechanisms supporting priming in the two directions. The findings on 

the N400 then are in line with the general consensus that this component reflects 

processing at a semantic / conceptual level. The fact that the pattern of the effect with L2 

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primes and L1 targets is somewhat different, could be due to the amount of processing 

necessary to generate such semantic-level effects (i.e., primes would be less efficiently 

and less rapidly processed in L2 than L1 in our participants who are learners and not 

balanced bilinguals). 

The N250 was found to be sensitive to within-language repetition priming in both 

L1 and L2, and most important, non-cognate translation primes were also found to 

modulate N250 amplitude when primes were in L1 and targets in L2, although the timecourse 

of this effect was somewhat later. No such translation priming effect on N250 

amplitude was found in Experiment 2 when primes were in L2 and targets in L1. The fact 

that the N250 ERP component was found to be sensitive to non-cognate translation 

priming when primes were in L1 and targets in L2 (Experiment 1) is perhaps the key 

finding of the present study. Holcomb and Grainger (2006) suggested that the N250 

reflects purely form-level processing – the mapping of sublexical form (letters and letter 

clusters) onto whole-word orthographic representations. The present results provide a 

clear demonstration that semantic overlap across primes and targets, in the absence of 

form overlap, can influence N250 amplitude. In the present study, this semantic influence 

occurred in the later phase of the N250, peaking at around 300 ms post-target onset (see 

Figure 6). This therefore provides us with an upper limit for the onset of semantic 

influences during visual word recognition. Based on the delayed time-course of the N250 

in L1-L2 translation condition this suggests that there is a rather short lag (around 50 ms) 

between sublexical form processing and availability of semantic information. This is in 

line with cascaded activation accounts of lexical processing (e.g., McClelland & 

Rumelhart, 1981), according to which higher level codes are activated with a minimal lag 

relative to lower-level processing. In a similar vein pointing to the possibility of cascaded 

processing, Grainger, Kiyonaga, and Holcomb (2006) have also shown a lag of 

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approximately 50 ms between the earliest modulation of the N250 by an orthographic 

manipulation (transposed-letter priming), and a later effect produced by a phonological 

manipulation (pseudohomophone priming). 

The observed effect of translation primes on the N250 fits nicely with a recent 

finding reported by Morris, Franck, Holcomb, and Grainger (2007) that the N250 is 

sensitive to the semantic transparency of morphologically related primes and targets. In 

this study, a distinct pattern of N250 priming effects was found for transparent primetarget 

pairs, where the prime has a clear semantic relation with the target (e.g., baker - 

bake) compared with opaque pairs, where there is no obvious semantic relation between 

primes and targets (e.g., corner - corn). Morris et al. argued that these semantic influences 

on the N250 likely reflect interactive processing, whereby higher-level semantic 

information feeds back to influence on-going form-level processing. In such an account, 

semantic information is rapidly accessed during visual word recognition, after some 

minimal form-level processing. This information is then fed back to lower levels of 

processing in order to generate a resonant activation state allowing a single form-meaning 

association to emerge as the best interpretation of the stimulus. 

In terms of models of bilingual word recognition, the present results fit well with 

the bilingual extension of McClelland and Rumelhart’s (1981) interactive-activation 

model – the BIA model (Grainger & Dijkstra, 1992; van Heuven et al., 1998). L1 primes 

would rapidly activate the corresponding semantic representation that would in turn 

feedback information to appropriate form-level representations in L1 and L2, hence 

modifying processing of L2 targets that are translates of the L1 prime. One could argue, 

however, that this translation priming effect reflects direct connectivity between the form 

representations of translation equivalents, as postulated in the RHM (Kroll & Stewart, 

1994). In this case, translation priming would not reflect semantic-level processing, as 

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argued above. The fact that the N250 translation priming effect was asymmetrical (i.e. 

observed only when translation primes were in L1 in Experiment 1 and not observed 

when translation primes were in L2 in Experiment 2) as has been found in behavioral 

studies of translation priming, would appear to be strong evidence against a lexically 

mediated (form-based) account of these effects as per the RHM. According to Kroll and 

Stewart’s model, direct connectivity across translation equivalents is stronger from L2 to 

L1 than vice versa, particularly in second language learners such as the participants of the 

present study. Therefore, according to a direct connectivity account of translation 

priming, we ought to have observed stronger effects with L2 primes and L1 targets. 

It is nevertheless possible that the absence of translation priming from L2 to L1 in 

the present study is simply a reflection of the inability of our participants to rapidly 

process briefly presented primes in their L2. This handicap in processing briefly 

presented primes in L2 would be further exaggerated when all visible words (i.e., targets) 

are in L1. This could arise via a global inhibition operating between languages, such that 

all L2 representations would be partially suppressed when processing in a seemingly 

monolingual L1 context. This would explain why we obtained robust effects on N250 

amplitude when both primes and targets were in L2 (repetition priming), since L2 prime 

processing would be enhanced in this context. If this interpretation is correct, then we 

ought to be able to increase L2-L1 translation priming effects by having a large number 

of L2 targets intermixed with the L1 targets. This would disable any kind of monolingual 

processing mode and therefore prevent the global inhibition of L2 representations. 

One problem with the above characterization is that although there were no N250 

effects for translation priming in Experiment 2, there were significant priming effects 

later during the N400 window. If L2 primes in an L1 processing mode are not being 

processed, then they should not have produced these later effects. Therefore it seems 

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more likely that the L2 primes in Experiment 2 were processed but that because 

processing of L2 items is less efficient and slower (as indicated by the later N400 effects 

to L2 targets) there was not sufficient time in this short SOA paradigm for feedback from 

the semantic level to the form level to exert its influence on the L1 N250. If this is correct 

than lengthening the SOA so as to allow the prime processing to progress further might 

boost feedback enough to support N250 type effects with L2 primes and L1 translation 

targets. 

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Discussion générale 

Chapitre 6 


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In the four articles presented in chapters two through five of this dissertation we 

presented studies using electrophysiological measures with the goal of adding to the 

existing body of research on the nature of the bilingual lexicon. These chapters addressed 

important questions about similarities and differences of processing in L1 and L2, 

language selectivity and the level of integration and interactivity of the bilingual lexicon. 

Chapter two presented studies that sought similarities and differences in processing 

in L1 and L2 and this in both late learners and in late bilinguals. We observed that the 

processing of L1 and L2 words in late L2 learners and late bilinguals diverged in two 

distinct ways as reflected in the ERP waveforms generated by these words during silent 

reading for meaning. For learners, an anterior part of the N400 component showed a 

distinct latency shift with L2 amplitudes peaking later than L1 amplitudes while the 

posterior part of the N400 revealed larger amplitudes to L1 compared with L2 words. 

Even the late bilinguals showed an anterior latency shift with L2 amplitudes peaking later 

than L1 amplitudes, although this latency shift was smaller. However the bilinguals 

showed no significant difference in amplitude between L1 and L2 in posterior regions. 

We attempted explanations for these effects in learners with factors known to affect 

the N400 component in monolingual processing but to no avail. We could find no 

possible subjective frequency account that fit our data nor was there any straightforward 

AoA explanation, nor was there a viable orthographic neighborhood explanation. 

We were led to conclude, given the pattern of observed effects that word 

recognition in L2 involves distinct mechanisms compared with the first language, at least 

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in the relatively early phases of L2 acquisition in late learners of an L2. This conclusion 

steered us away from the BIA model (Grainger & Dijkstra, 1992; van Heuven et al., 

1998) that posits an integrated lexicon with processing much like a monolingual IA 

model, and towards a model that predicts processing differences, due to different 

mechanisms, between L1 and L2, like the RHM (Kroll & Stewart, 1994). 

Another important observation from chapter two had to do with the N400 as a 

measure of proficiency. The posterior N400 language effect observed in learners was not 

present in proficient bilinguals. However, the anterior N400 latency shift observed for 

learners was also observed for proficient bilinguals, but the latency difference was much 

smaller. This would suggest that the posterior N400 language effect reflects competence 

in L2, but the anterior latency shift of the N400 effect continues to reflect differences in 

L1 and L2 processing even in relatively competent bilinguals; i.e., even competent late 

learners of an L2 conserve some form of asymmetry. Thus there remains an empirical 

question: would early bilinguals show any pattern of anterior latency shift of the N400? 

And if so would it be modulated by language dominance? 

In the studies in chapter three the participants saw lists of words in one language 

only and were therefore in appropriate conditions for using language-specific selection 

processes. The presented words were of differing neighborhood density in the nonpresented 

language. We observed effects of cross-language neighborhood density for both 

L1 and L2. This cross-language neighborhood effect appeared earlier (in the 175–275 ms 

epoch) and was more widely distributed across the scalp when the target words were in 

L2 and the neighbors in L1. Effects of cross-language neighborhood on L1 words only 

appeared in the 300–500 ms epoch and were limited to the most posterior electrode sites. 

These results contradict the notion of early language-specific selection in bilingual 

language comprehension while providing support for the non-selective access hypothesis 

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embodied in the BIA+ model (Dijkstra & van Heuven, 2002). In fact, simulations run on 

the BIA+ model with the stimuli form the experiments showed that cross-language 

neighborhood effects are stronger when targets are in L2 compared with targets in L1. 

These results provide further evidence in favor of non-selective access to a highly 

integrated and interactive lexicon in bilinguals. 

In addition to any observations about language non-selectivity these results show 

that L2 neighbors have a later and less widely distributed effect on L1 target processing 

than L1 neighbors have on L2 target processing. This is in line with one major principle 

implemented in all connectionist models of language processing – that frequency of 

exposure determines connection strength. In late bilinguals L2 words have much lower 

exposure overall than L1 words. This exposure difference is thus reflected in word 

frequency differences between L1 and L2. This could account for why the effects of L2 

neighbors are weaker, less widely distributed, and since more time is required for 

propagation, appear later than the effects of L1 neighbors. With this observation of timecourse 

differences it is important to point out that these participants were proficient 

bilinguals and late learners of L2. If the difference of subjective frequency is what is 

driving the results it follows that this will continue to have effects in late learners of an L2 

even if they are competent bilinguals. 

The two first articles of this dissertation therefore appear to come down on opposite 

sides of a supposed opposition between the RHM and the BIA model. One way of 

integrating the findings is to remark that the BIA model better reflects processing in 

relatively proficient bilinguals, while the RHM is a better model of lexical processing in 

beginning bilinguals. However our findings with late bilinguals lead us to believe that the 

BIA model must account for an on-going asymmetry in bilinguals. 

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The results of these studies lead us to the observation that although the BIA model 

may be a preferable model in that it is an extension of monolingual models, it needs some 

mechanism for explaining the developmental story of late learners of a second language – 

especially since our results seem to say that the asymmetry of late learners is never 

completely vanquished. In the RHM there exists the idea that during L2 acquisition, the 

L2-L1 translation route would be gradually replaced by L2 lexical representations that 

become part of an integrated network along with L1 representations establishing strong 

L2 lexical-semantic links. In a bilingual IA model this could be achieved by gradually 

increasing the L2 resting levels, and gradually strengthening the weights of the 

connections between L2 word-forms and semantics. Thus as proficiency develops in L2, 

lexical processing in L2 becomes more and more akin to lexical processing in L1. 

In order to further pursue questions of language integration and interactivity in the 

article presented in chapter four we recorded and compared ERPs to cognate and noncognate 

words while participants were processing blocked lists of words in their L1 and 

L2. ERP negativities in the region of the N400 component were found to be sensitive to 

cognate status in both language blocks with non-cognates being more negative than 

cognates; i.e., larger N400s reflecting more difficult processing for non-cognates. This 

fits with the general hypothesis that the mapping of form to meaning is facilitated in 

cognate words. An important finding of this article was the influence of cognate status on 

word recognition in L1 because prior behavioral research had provided mixed findings on 

this particular issue. Using electrophysiological measures, we were able to observe 

cognate effects in relatively low proficiency language learners processing words in their 

L1. 

Furthermore we hypothesized that the cognate advantage would reflect an 

accumulation of the benefits of exposure to a given form-meaning association across two 

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languages. This would presumably benefit L2 more than L1, particularly in the case of 

learners. Thus we predicted to see stronger cognate effects in L2 compared to L1 and we 

did not. 

However, it is notable that the time-course of the N400 effects differed between the 

two language blocks. The cognate effects began to emerge about 200 ms earlier in L1. In 

addition to predicting cognate effects in both L1 and L2, we predicted earlier effects in 

L1. This is because the locus of the cognate advantage, the mapping between form and 

meaning, should arise earlier in the processing of an L1 word than an L2 word. 

Our results can, at first blush, be taken as evidence for a factor, known to affect 

monolingual word processing; frequency. If we are arguing that our effects are the result 

of the accumulation of exposure to a given form-meaning association we are putting forth 

an argument of a frequency account of our effects. But the difference in timing of these 

effects could point to something else; different mechanisms underlying the observed 

differences in time-course of cognate effects between L1 and L2. 

Within the framework of the RHM, one could argue that cognate words are 

particularly easy to process in the early phases of L2 acquisition given that their 

translations equivalents have the same or very similar orthographic forms. Non-cognate 

words would be harder to process because of the increased difficulty in mapping the L2 

form onto its translation equivalent in L1. This would therefore explain why the cognate 

effect arises quite late in processing L2 words, but it cannot explain why there is an effect 

in L1. 

Differences in the time-course of the N400 component were observed in the studies 

in chapter two, three and four. An anterior delay in the N400 for L2 processing was 

observed in the language effects article. In chapter three, the article regarding the effects 

of cross-language neighborhood found an earlier influence of L1 neighbors on L2 words. 

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The cognate manipulation in chapter four also produced time-course differences. The 

cognate effect was earlier in L1 than in L2. In order to more clearly observe and specify 

any differences in the timing of processing between an L1 and an L2 we chose to use a 

masked priming paradigm that manipulated two crucial factors in word recognition; form 

and meaning. Chapter five presents these studies in which we tested within-language 

repetition priming and between-language non-cognate translation priming in second 

language learners using the masked priming paradigm. 

In the case of within-language repetition priming for both L1 and L2 both the N250 

and the N400 components were found to be sensitive, thus much resembling and 

reproducing Holcomb and Grainger (2006) results for both L1 and L2. (See Table 1 for a 

summary of results.) At this point it is helpful to remember that Holcomb and Grainger 

propose that the N250 component reflects form based processing and the N400 

component reflects semantic processes. 

In the case of translation priming the N400 effect for the L1-L2 direction was robust 

and widespread and in the predicted direction, while in the L2- L1 priming direction an 

anterior effect in the opposite direction was found. N250 amplitude was found to be 

modulated by translation primes only when primes were in L1 and targets in L2. 

Table 1. summary of results of priming in N250 and N400 components. 

within language repetition translation priming 

L1-L1 L2-L2 L2-L1 L1-L2 

N250 x x x 

N400 x x ~ x 

x = clear significant result expected as per Holcomb & Grainger 

~ = results in opposite direction 

In terms of models of bilingual word recognition, the present results fit well with a 

bilingual IA model such as the BIA model. L1 primes would rapidly activate the 

corresponding semantic representation that would in turn feedback information to 

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appropriate form-level representations in L1 and L2, hence modifying processing of L2 

targets that are translations of the L1 prime. This would account for N400 effects in L1- 

L1 repetition priming and in L1-L2 translation priming. 

This pattern of results for the N250 component is most interesting. N250 effects 

were predicted and found in L1-L1 and L2-L2 priming replicating Holcomb and Grainger 

(2006). However, the fact that the N250 component was found to be sensitive to 

translation priming when primes were in L1 and targets in L2 is perhaps the key finding 

of this study. Holcomb and Grainger suggested that the N250 reflects purely form-level 

processing. The present results provide a clear demonstration that semantic overlap across 

primes and targets, in the absence of form overlap, can influence N250 amplitude. These 

semantic influences on the N250 likely reflect interactive processing, whereby higherlevel 

semantic information feeds back to influence on-going form-level processing. In 

such an account, semantic information is rapidly accessed during visual word recognition, 

after some minimal form-level processing. This finding is interesting for word 

recognition in general. 

It is notable that we obtained robust effects on both the N250 component and the 

N400 component in the case of L2-L2 priming and an absence of these effects in L2-L1 

priming. The participants were not unable to process L2 primes masked at 50 ms, they 

were only unable to process these L2 primes when overtly processing a list of L1 words. 

It is possible that at 50 ms there was not sufficient time in this short SOA paradigm for 

feedback from the semantic level to the form level to exert its influence on the L1 item 

given the slow processing of L2 and the rapid processing of L1. If this is correct then 

lengthening the SOA so as to allow the prime processing to progress further might boost 

feedback enough to support effects with L2 primes and L1 translation targets. Also our 

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results were found in a population of L2 learners. Perhaps proficient bilinguals would 

show translation priming at this SOA. 

A note on the RHM - according to Kroll and Stewart’s model, direct connectivity 

across translation equivalents is stronger from L2 to L1 than vice versa, particularly in 

second language learners such as the participants of this study. Therefore, according to a 

direct connectivity account of translation priming, we ought to have observed stronger 

effects with L2 primes and L1 targets and we observed effects only with L1 primes and 

L2 targets. 

In Conclusion 

The studies in this dissertation and the body of existing research lead us to draw 

some tentative conclusions about the nature of the bilingual lexicon. First of all, the 

research in this dissertation suggests that even though L1 and L2 are processed in much 

the same way there are nevertheless clear differences in L1 and L2 processing, notably in 

learners engaged in L2 acquisition. Moreover, it seems that subtle differences persist 

between L1 and L2 processing even in proficient bilinguals that are late learners of their 

second language. A second conclusion that can be drawn is that the bilingual lexicon can 

be regarded as a highly integrated, interactive system. And access to this integrated 

lexicon appears to be non-selective. A third conclusion is that the acquisition of a second 

language restructures certain aspects of the existing L1 lexicon. If, as we have argued, the 

structure of this integrated lexicon of the late bilingual is similar to that of a monolingual 

then if follows that many of the things that we know about ways that monolinguals 

achieve visual word recognition apply. However, it is important to keep in mind that the 

persisting asymmetry associated with late learning adds to the complexity of the bilingual 

lexicon. 

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In the introduction we stated that many of the existing accounts of lexical 

processing describe monolingual processing with rare contingencies for describing 

bilingual processing. We also presented two models that attempt descriptions of the 

bilingual lexicon and that are very different in nature. It is our idea that both of these 

models capture some essence of the bilingual lexicon. We favor a model of bilingual 

word processing that is based solidly on known word processing phenomena with 

contingencies for handling the case of second language acquisition and the asymmetries 

that persist as well as the case of simultaneous early bilingualism. A bilingual IA model 

such as the BIA model appears to us to be a good candidate for a model of the bilingual 

lexical processing providing that the model includes contingencies for describing both the 

evolution of the lexicon in the case of acquisition and the case of simultaneous 

bilingualism. 

A true universal account of language processing must parsimoniously describe both 

monolingual processing and bilingual processing and the representations and processes 

involved. To achieve this grand ideal it is clear that more empirical work must be done to 

completely inform any description of the bilingual lexicon and it is our position that 

electrophysiological methods can provide a wealth of information to this end. 

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