[Abstract Title]. - Society for Neuroscience

Authors: *S. BESTMANN 1 , M. MUNNEKE 2 , L. M. HARRISON 3 , R. MARS 4 , J. C.
ROTHWELL 2 ;
1 Sobell Dept, Inst. of Neurol, London, United Kingdom; 2 Sobell Dept., Inst. of Neurol.,
University College London, United Kingdom; 3 Wellcome Trust Ctr. for Neuroimaging, Univ.
Col. London, London, United Kingdom; 4 Psychology, Univ. of Oxford, Oxford, United
Kingdom
Abstract: We often prepare and select actions based on regularities in our physical world. These
regularities enable us to predict forthcoming events, and prepare actions in anticipation of these.
Here we tested whether corticospinal excitability (CSE), prior to action, is influenced by changes
in probabilistic context, i.e. the conditional uncertainty about sequential events (stimuli) in a
sequential reaction time task.
Four subjects performed 4-5 sessions (12 blocks with 60 trial per session; separated by several
days), with informed consent, yielding a minimum of 2880 trials for each subject. One of 4
arbitrary stimuli was presented o each trial. Responses were made with the left and right index
and small finger, respectively. We generated 1 st order Markov sequences of different
predictability. Therefore, the event on the current trial Ti was conditionally dependent on the
previous trial Ti-1. The transition matrix specifying the probability of transition between
consecutive events was changed for each block. Each event (and hence each action) was equiprobable
over the course of the experiment. CSE was measured from the right FDI and ADM
muscle, 200ms before presentation of a visual stimulus, using transcranial magnetic stimulation
to left primary motor cortex. We could therefore measure how CSE was sculpted by changes in
probabilistic context, before an event occurred 1 .
Information theoretic measures of the conditional uncertainty were used to predict behavioural
and CSE data during each block. Specifically, we computed the mutual information (MI) among
events that provides a quantification of the conditional uncertainty on each trial 2 . The influence
of MI on CSE (and RTs) was estimated using a hierarchical general linear model (GLM) whose
parameters were optimized by empirical Bayes procedures 1 . We modelled subjects as ideal
Bayesian observers, starting with flat prior at the beginning of each block 2 .
Initial analyses show that CSE was larger when the conditional uncertainty about what action
will be required next decreased (0.14mV/bit). These effects were effector-specific, i.e. dependent
on the prior expectation that a certain response had to be made. Correspondingly, reaction times
were faster when MI increased (55ms/bit) 2 .
Our results suggest that CSE prior to action is shaped on a trial-by-trial basis by the probabilistic
context in which events guiding our actions occur. This may help to specify actions in
anticipation of an event. Moreover, it indicates how activity in the motor system is biased by
probabilistic context, which itself is learned and represented in the brain.
1.Bestmann et al (2008) Curr Biol
2.Harrison et al (2006) Neural Netw
Disclosures: S. Bestmann , None; M. Munneke, None; J.C. Rothwell, None; R. Mars,
None; L.M. Harrison, None.