Spatio-Temporal Modeling of Neural Source Activation from EEG Data

This paper proposes a new computer-vision based information visualization paradigm for the electrophysiological study of face recognition. The proposed approach first generates video sequences of voltage maps from EEG data. Next, projections of active sources are detected in each frame using colour...

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Bibliographic Details
Published in2007 Canadian Conference on Electrical and Computer Engineering pp. 1014 - 1017
Main Authors Albu, A.B., Mahajan, S.V., Zeman, P.M., Tanaka, J.W.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2007
Subjects
Brain modeling
Data visualization
Electroencephalography
Electrophysiology
Enterprise resource planning
Face recognition
Humans
Spatiotemporal phenomena
Video sequences
Voltage
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ISBN9781424410200
1424410207
ISSN0840-7789
DOI10.1109/CCECE.2007.259

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Summary:This paper proposes a new computer-vision based information visualization paradigm for the electrophysiological study of face recognition. The proposed approach first generates video sequences of voltage maps from EEG data. Next, projections of active sources are detected in each frame using colour information and spatiotemporal consistency. The evolution of source activation is thus translated into a deformable motion of 2D patterns. Hence, the last step of the proposed approach builds a new motion representation, called the Spatio-Temporal Activation Response (STAR), which extracts stimulus-and subject-specific information about neural source activations occurring during the experiment. It is shown that STAR is able to capture relevant information about differences in the cognitive representations elicited by two different visual stimuli.
ISBN:9781424410200
1424410207
ISSN:0840-7789
DOI:10.1109/CCECE.2007.259