AUTHOR=Kenny Bret , Power Sarah D. TITLE=Toward a Subject-Independent EEG-Based Neural Indicator of Task Proficiency During Training JOURNAL=Frontiers in Neuroergonomics VOLUME=1 YEAR=2021 URL=https://www.frontiersin.org/journals/neuroergonomics/articles/10.3389/fnrgo.2020.618632 DOI=10.3389/fnrgo.2020.618632 ISSN=2673-6195 ABSTRACT=
This study explores the feasibility of developing an EEG-based neural indicator of task proficiency based on subject-independent mental state classification. Such a neural indicator could be used in the development of a passive brain-computer interface to potentially enhance training effectiveness and efficiency. A spatial knowledge acquisition training protocol was used in this study. Fifteen participants acquired spatial knowledge in a novel virtual environment via 60 navigation trials (divided into ten blocks). Task performance (time required to complete trials), perceived task certainty, and EEG signal data were collected. For each participant, 1 s epochs of EEG data were classified as either from the “low proficiency, 0” or “high proficiency, 1” state using a support vector machine classifier trained on data from the remaining 14 participants. The average epoch classification per trial was used to calculate a neural indicator (NI) ranging from 0 (“low proficiency”) to 1 (“high proficiency”). Trends in the NI throughout the session—from the first to the last trial—were analyzed using a repeated measure mixed model linear regression. There were nine participants for whom the neural indicator was quite effective in tracking the progression from low to high proficiency. These participants demonstrated a significant (