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

Other

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

Fingerprint

Electroencephalography
Brain
Neurons
Bioelectric potentials
Data acquisition
Chemical activation
Electric fields
Data storage equipment
Electrodes
Sensors
Experiments

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

Cite this

Anderson, E. W., Chong, C., Preston, G. A., & Silva, C. T. (2013). Discovering and visualizing patterns in EEG data. In IEEE Symposium on Pacific Visualization 2013, PacificVis 2013 - Proceedings (pp. 105-112). [6596134] https://doi.org/10.1109/PacificVis.2013.6596134

Discovering and visualizing patterns in EEG data. / Anderson, Erik W.; Chong, Catherine; Preston, Gilbert A.; Silva, Cláudio T.

IEEE Symposium on Pacific Visualization 2013, PacificVis 2013 - Proceedings. 2013. p. 105-112 6596134.

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

Anderson, EW, Chong, C, Preston, GA & Silva, CT 2013, Discovering and visualizing patterns in EEG data. in IEEE Symposium on Pacific Visualization 2013, PacificVis 2013 - Proceedings., 6596134, pp. 105-112, 6th IEEE Symposium on Pacific Visualization, PacificVis 2013, Sydney, NSW, Australia, 2/26/13. https://doi.org/10.1109/PacificVis.2013.6596134
Anderson EW, Chong C, Preston GA, Silva CT. Discovering and visualizing patterns in EEG data. In IEEE Symposium on Pacific Visualization 2013, PacificVis 2013 - Proceedings. 2013. p. 105-112. 6596134 https://doi.org/10.1109/PacificVis.2013.6596134
Anderson, Erik W. ; Chong, Catherine ; Preston, Gilbert A. ; Silva, Cláudio T. / Discovering and visualizing patterns in EEG data. IEEE Symposium on Pacific Visualization 2013, PacificVis 2013 - Proceedings. 2013. pp. 105-112
@inproceedings{f44ecdd8eecb45d2bb2930458650b62d,
title = "Discovering and visualizing patterns in EEG data",
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.",
keywords = "Computer Graphics [I.3.4]: Graphics Utilities - Application Packages, Electroencephalography",
author = "Anderson, {Erik W.} and Catherine Chong and Preston, {Gilbert A.} and Silva, {Cl{\'a}udio T.}",
year = "2013",
doi = "10.1109/PacificVis.2013.6596134",
language = "English (US)",
isbn = "9781467347976",
pages = "105--112",
booktitle = "IEEE Symposium on Pacific Visualization 2013, PacificVis 2013 - Proceedings",

}

TY - GEN

T1 - Discovering and visualizing patterns in EEG data

AU - Anderson, Erik W.

AU - Chong, Catherine

AU - Preston, Gilbert A.

AU - Silva, Cláudio T.

PY - 2013

Y1 - 2013

N2 - 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.

AB - 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.

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

UR - http://www.scopus.com/inward/record.url?scp=84888997725&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84888997725&partnerID=8YFLogxK

U2 - 10.1109/PacificVis.2013.6596134

DO - 10.1109/PacificVis.2013.6596134

M3 - Conference contribution

SN - 9781467347976

SP - 105

EP - 112

BT - IEEE Symposium on Pacific Visualization 2013, PacificVis 2013 - Proceedings

ER -