Abstract
Feature of event-related potential (ERP) has not been completely understood and illiteracy problem remains unsolved. To this end, P300 peak has been used as the feature of ERP in most brain–computer interface applications, but subjects who do not show such peak are common. Recent development of convolutional neural network provides a way to analyze spatial and temporal features of ERP. Here, we train the convolutional neural network with 2 convolutional layers whose feature maps represented spatial and temporal features of event-related potential. We have found that nonilliterate subjects' ERP show high correlation between occipital lobe and parietal lobe, whereas illiterate subjects only show correlation between neural activities from frontal lobe and central lobe. The nonilliterates showed peaks in P300, P500, and P700, whereas illiterates mostly showed peaks in around P700. P700 was strong in both subjects. We found that P700 peak may be the key feature of ERP as it appears in both illiterate and nonilliterate subjects.
Highlights
A brain–computer interface (BCI) is a system which provides a communication method by utilizing biophysiological signals [1]
As the convolutional neural network (CNN) identifies most of the event-related potential (ERP) to be positive, the result indicates that discriminant feature of target ERP was not found
This study has investigated the difference in spatial and temporal features of ERP between high performance group (H group) and low performance group (L group)
Summary
A brain–computer interface (BCI) is a system which provides a communication method by utilizing biophysiological signals [1]. BCI system enables the users to communicate with external world through measurements of biological signals and mostly do not require voluntary muscle movement. Electroencephalography (EEG) has been most widely used in BCI field for its easiness in and low cost of measurement [8, 9]. Among different applications of BCI, event-related potential (ERP) based speller system has been one of the most widely used paradigms. The system was pioneered by Farwell and Donchin [10] in 1988 which utilized oddball paradigm in order to induce visual evoked potential (VEP), especially the P300 response. There has been reports of ERP features other than P300 [13, 14] which may be a key feature of distinguishing identifying illiterates
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