Classification of visual comprehension based on EEG data using sparse optimal scoring

Linda Katherine Wood Ford*, Joshua Borneman, Julia Krebs, Evguenia Malaia, Brendan Ames

*Corresponding author for this work

Research output: Contribution to journalArticle


OBJECTIVE: Understanding and differentiating brain states is an important task in the field of cognitive neuroscience with applications in health diagnostics (such as detecting neurotypical development vs. Autism Spectrum or coma/vegetative state vs. locked-in state). Electroencephalography (EEG) analysis is a particularly useful tool for this task as EEG data can detect millisecond-level changes in brain activity across a range of frequencies in a non-invasive and relatively inexpensive fashion. The goal of this study is to apply machine learning methods to EEG data in order to classify visual language comprehension across multiple participants.

APPROACH: 26-channel EEG was recorded for 24 Deaf participants while they watched videos of sign language sentences played in time-direct and time-reverse formats to simulate interpretable vs. uninterpretable sign language, respectively. Sparse Optimal Scoring (SOS) was applied to EEG data in order to classify which type of video a participant was watching, time-direct or time-reversed. The use of SOS also served to reduce the dimensionality of the features to improve model interpretability.

MAIN RESULTS: The analysis of frequency-domain EEG data resulted in an average out-of-sample classification accuracy of 98.89%, which was far superior to the time-domain analysis. This high classification accuracy suggests this model can accurately identify common neural responses to visual linguistic stimuli.

SIGNIFICANCE: The significance of this work is in determining necessary and sufficient neural features for classifying the high-level neural process of visual language comprehension across multiple participants.

Original languageEnglish
JournalJournal of Neural Engineering
Publication statusE-pub ahead of print - 13 Jan 2021

Bibliographical note

© 2020 IOP Publishing Ltd.

Fields of Science and Technology Classification 2012

  • 107 Other Natural Sciences


  • Discriminant Analysis
  • Classification
  • Optimal Scoring
  • EEG
  • sign language

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