• DocumentCode
    632798
  • Title

    Discovering and visualizing patterns in EEG data

  • Author

    Anderson, E.W. ; Chong, Christian ; Preston, Gilbert A. ; Silva, Claudio T.

  • Author_Institution
    Univ. of Utah, Salt Lake City, UT, USA
  • fYear
    2013
  • fDate
    Feb. 27 2013-March 1 2013
  • Firstpage
    105
  • Lastpage
    112
  • 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
    biomedical electrodes; data analysis; data visualisation; electroencephalography; feature extraction; medical signal processing; query processing; EEG data analysis; activation patterns; brain activity data; data acquisition modality; electric fields; electrodes; electroencephalography; potential neural activity pattern extraction; potential neural activity pattern visualization; query processing; sensors; shared activity patterns; small neuronal collections; spectral signal dynamics; Brain; Correlation; Data mining; Data visualization; Electroencephalography; Sensors; Time-frequency analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visualization Symposium (PacificVis), 2013 IEEE Pacific
  • Conference_Location
    Sydney, NSW
  • ISSN
    2165-8765
  • Type

    conf

  • DOI
    10.1109/PacificVis.2013.6596134
  • Filename
    6596134