Discovering and visualizing patterns in EEG data

Erik W. Anderson, Catherine Chong, Gilbert A. Preston, Cláudio T. Silva

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Brain activity data is often collected through the use of electroencephalography (EEG). In this data acquisition modality, the electric fields generated by neurons are measured at the scalp. Although this technology is capable of measuring activity from a group of neurons, recent efforts provide evidence that these small neuronal collections communicate with other, distant assemblies in the brain's cortex. These collaborative neural assemblies are often found by examining the EEG record to find shared activity patterns. In this paper, we present a system that focuses on extracting and visualizing potential neural activity patterns directly from EEG data. Using our system, neuroscientists may investigate the spectral dynamics of signals generated by individual electrodes or groups of sensors. Additionally, users may interactively generate queries which are processed to reveal which areas of the brain may exhibit common activation patterns across time and frequency. The utility of this system is highlighted in a case study in which it is used to analyze EEG data collected during a working memory experiment.

Original languageEnglish (US)
Title of host publicationIEEE Symposium on Pacific Visualization 2013, PacificVis 2013 - Proceedings
Pages105-112
Number of pages8
DOIs
StatePublished - 2013
Event6th IEEE Symposium on Pacific Visualization, PacificVis 2013 - Sydney, NSW, Australia
Duration: Feb 26 2013Mar 1 2013

Publication series

NameIEEE Pacific Visualization Symposium
ISSN (Print)2165-8765
ISSN (Electronic)2165-8773

Other

Other6th IEEE Symposium on Pacific Visualization, PacificVis 2013
Country/TerritoryAustralia
CitySydney, NSW
Period2/26/133/1/13

Keywords

  • Computer Graphics [I.3.4]: Graphics Utilities - Application Packages, Electroencephalography

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Software

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