Brain connectivity evaluation during selective attention using EEG-based brain-computer interface

Soheil Borhani, Reza Abiri, Yang Jiang, Taylor Berger, Xiaopeng Zhao

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Attentional deficits may be caused by neurological diseases, including Attention-Deficit/Hyperactivity Disorder (ADHD), Alzheimer’s disease (AD), Traumatic Brain Injuries (TBI), etc. This work aims to evaluate selective attention under visual stimulations of faces and scenes using electroencephalogram (EEG)-based brain-computer interface.The experiment consisted of two phases: 1) image recognition and 2) attention evaluation. In phase 1, the mean response time was 547 ms vs. 633 ms to faces and scenes, respectively. In phase 2, the mean response time was 667 ms vs. 706 ms to face and scene categories, respectively. We analyzed the event-related time-frequency representation of faces and scenes and the causal relationship between object recognition and the motor response associated with category selection using the brain connectivity based on Granger causality. The developed experimental protocols and connectivity evaluation methods may provide insights for a better understanding of the neural processes for object recognition and category selection.

Original languageEnglish
Pages (from-to)25-35
Number of pages11
JournalBrain-Computer Interfaces
Volume6
Issue number1-2
DOIs
StatePublished - 2019

Bibliographical note

Publisher Copyright:
© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • Brain-computer interface
  • EEG
  • Granger Causality
  • brain connectivity
  • event-related potential
  • selective attention
  • time-frequency

ASJC Scopus subject areas

  • Biomedical Engineering
  • Human-Computer Interaction
  • Behavioral Neuroscience
  • Electrical and Electronic Engineering

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