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*Manuscript Click here to view linked References 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 Abstract Electrical artifacts caused by the cochlear implant (CI) contaminate electroencephalographic (EEG) recordings from implanted individuals and corrupt auditory evoked potential (AEPs). Independent component analysis (ICA) is efficient in attenuating the electrical CI artifact and AEPs can be successfully reconstructed. However the manual selection of CI artifact related independent components (ICs) obtained with ICA is unsatisfactory, since it contains expert-choices and is time consuming. We developed a new procedure to evaluate temporal and topographical properties of ICs and semi- automatically select those components representing electrical CI artifact. The CI Artifact Correction (CIAC) algorithm was tested on EEG data from two different studies. The first consists of published datasets from 18 CI users listening to environmental sounds. Compared to the manual IC selection performed by an expert the sensitivity of CIAC was 91.7% and the specificity 92.3%. After CIAC- based attenuation of CI artifacts, a high correlation between age and N1-P2 peak-to-peak amplitude was observed in the AEPs, replicating previously reported findings and further confirming the algorithm’s validity. In the second study AEPs in response to pure tone and white noise stimuli from 12 CI users that had also participated in the other study were evaluated. CI artifacts were attenuated based on the IC selection performed semi-automatically by CIAC and manually by one expert. Again, a correlation between N1 amplitude and age was found. Moreover, a high test-retest reliability for AEP N1 amplitudes and latencies suggested that CIAC based attenuation reliably preserves plausible individual response characteristics. We conclude that CIAC enables the objective and efficient attenuation of the CI artifact in EEG recordings, as it provided a reasonable reconstruction of individual AEPs. The systematic pattern of individual differences in N1 amplitudes and latencies observed with different stimuli at different sessions, strongly suggests that CIAC can overcome the electrical artifact problem. Thus CIAC facilitates the use of cortical AEPs as an objective measurement of auditory rehabilitation. 1
27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 Keywords: cochlear implant, AEPs, N1, artifact attenuation, test-retest reliability 1. Introduction Auditory evoked potentials (AEPs) are important for the evaluation of auditory cortex functions in normal hearing and hearing impaired humans. Several studies have used AEPs to investigate how the auditory cortex adapts to the artificial input provided by a cochlear implant (CI). Examples are the measurement of the P1 response to investigate the functional development of the auditory cortex in children fitted with CIs (Gilley et al., 2008; Sharma et al., 2005), the study of brain asymmetries in the auditory cortex (Debener et al., 2008; Sandmann et al., 2009), the investigation of neural correlates of musical sound perception (Koelsch et al., 2004; Sandmann et al., 2010), and the relationship of AEPs to speech perception (Henkin et al., 2009; Kelly et al., 2005; Lonka et al., 2004; Zhang et al., 2010; Zhang et al., 2011). Based on those and other studies it has been suggested that the functional integrity of the auditory system from CI users, which varies widely across patients, as well as the capacity for cortical plasticity, deserves more attention when investigating implantation outcome (Moore and Shannon, 2009; Wilson and Dorman, 2008). One of the limitations of using AEPs as a routine research or clinical tool is the fact that the EEG recordings taken from CI users are contaminated by electrical artifacts which coincide in time with auditory stimulation. Other authors have already described in detail the characteristics of the CI artifact (Gilley et al., 2006). The CI artifact properties vary widely across devices, individuals, and types of stimulation (Gilley, et al., 2006; Viola et al., 2011) and the literature is inconsistent concerning the prevalence of the artifact. In some CI users the absence of artifacts in EEG recordings has been reported (Zhang, et al., 2010). Moreover, at least one study suggested electrical artifacts only occur at response latencies different from cortical AEPs and thus did not report difficulties in the measurement of AEPs (Koelsch, et al., 2004). It has also been speculated that the CI artifact may be present until one year after CI activation (Lonka, et al., 2004). Despite these reports, most studies presenting multi-channel EEG data have found that AEPs from CI users are strongly corrupted by a large electrical artifact generated by the CI device, thus impairing any type of analysis unless tailored, sophisticated and often time-consuming artifact processing techniques are applied. Accordingly, 2
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