Reconfiguration of Brain Network between Resting-state and Oddball Paradigm

TL;DR

This study investigates how brain network architecture changes from resting-state to an oddball task using EEG data, revealing significant connectivity reconfigurations and their relation to P300 amplitudes, with implications for brain-computer interfaces.

Contribution

It provides new insights into brain network reconfiguration during cognitive tasks and demonstrates the potential for classifying P300 amplitude groups based on EEG connectivity features.

Findings

Enhanced delta/theta connectivity during oddball task

Decreased alpha default mode network connectivity

Reconfigured network features predict P300 amplitude groups with 77.78% accuracy

Abstract

The oddball paradigm is widely applied to the investigation of multiple cognitive functions. Prior studies have explored the cortical oscillation and power spectral differing from the resting-state conduction to oddball paradigm, but whether brain networks existing the significant difference is still unclear. Our study addressed how the brain reconfigures its architecture from a resting-state condition (i.e., baseline) to P300 stimulus task in the visual oddball paradigm. In this study, electroencephalogram (EEG) datasets were collected from 24 postgraduate students, who were required to only mentally count the number of target stimulus; afterwards the functional EEG networks constructed in different frequency bands were compared between baseline and oddball task conditions to evaluate the reconfiguration of functional network in the brain. Compared to the baseline, our results showed the significantly (p < 0.05) enhanced delta/theta EEG connectivity and decreased alpha default mode network in the progress of brain reconfiguration to the P300 task. Furthermore, the reconfigured coupling strengths were demonstrated to relate to P300 amplitudes, which were then regarded as input features to train a classifier to differentiate the high and low P300 amplitudes groups with an accuracy of 77.78%. The findings of our study help us to understand the changes of functional brain connectivity from resting-state to oddball stimulus task, and the reconfigured network pattern has the potential for the selection of good subjects for P300-based brain- computer interface.