QUANTIFYING AND COMPENSATING FOR P300 VARIATIONS IN AMYOTROPHIC LATERAL SCLEROSIS

Abstract

P300-based brain–computer interface (BCI) systems enable people with neuromuscular disabilities, including amyotrophic lateral sclerosis (ALS), to communicate and to control their environments using brain activity. However, BCI systems have not yet fulfilled their promise as reliable communication systems for all who need them. Despite continued work on improving BCIs for end users, people with ALS can experience both reduced performance overall compared to neurotypical users and significant day to day variations in BCI performance and event-related potential (ERP) characteristics. The P300 response, which the P300 speller is based on, is also known to exhibit trial-to-trial latency variability. The importance of latency jitter is established in cognitive studies, and its relevance to BCIs is of growing interest. Increased latency jitter is associated with decreased BCI performance, and preliminary comparisons indicated that jitter may be increased in ALS, similar to increased jitter found in a variety of neurological conditions. Therefore, we quantify latency jitter and its correlates in people with ALS, longitudinally investigate within-session variability in event-related potentials (ERPs), session-average ERPs, and their relationships, and develop and evaluate a correction method to compensate for latency jitter in BCI use. To this end, we use longitudinal EEG data collected from 6 participants with ALS, and, when applicable, from neurotypical control participants, using a P300 BCI. Data recorded in each session had session-average ERP amplitudes and latencies extracted. Stepwise linear discriminant analysis was used both to evaluate BCI performance and to support the use of classifier- based latency estimation (CBLE) to estimate whole-epoch latency shifts for single trials in all aims. To quantify latency jitter and its correlates in people with ALS, latency jitter was calculated with CBLE. Then, ERP components and latency jitter were compared between participants with ALS and neurotypical control participants using Wilcoxon rank-sum tests. Correlations between latency jitter and each of the clinical measures, ERP features, and performance measures were investigated using Spearman and repeated measures correlations. We found that latency jitter was significantly increased in participants with ALS and significantly negatively correlated with BCI performance in both ALS and control participants. We also found significant correlations between ERP amplitudes and latency jitter in neurotypical participants and reduced ERP amplitudes in participants with ALS. However, there was no significant correlation between latency jitter and clinical measures. Based on these results, we proposed a data augmentation and jitter correction (A/C) scheme with parameters determined individually using latency shifts calculated with CBLE.