Detecting symmetric patterns in EEG data: a new method of analysis.

Published

Journal Article

Theoretical models of higher cognitive function predict that cortical activity will exhibit families of spatial-temporal patterns of activity whose individual members are related to each other by specific symmetry transformations. In the trion model, it is suggested that these inherent symmetries play a vital role in how we think and reason. We have developed a method of analysis (SYMMETRIC analysis), which detects families of patterns in EEG data, and characterizes the symmetry relationships between members of those pattern families. Using this analysis, significant symmetry families have been found in EEG and single unit spike train data. If symmetry is a crucial aspect of brain function, it is possible that different pathologies are associated with specific types of symmetry relationships in brain activity that could be detected in EEG data by a SYMMETRIC analysis.

Full Text

Duke Authors

Cited Authors

  • Bodner, M; Shaw, GL; Gabriel, R; Johnson, JK; Murias, M; Swanson, J

Published Date

  • October 1999

Published In

Volume / Issue

  • 30 / 4

Start / End Page

  • 143 - 150

PubMed ID

  • 10513320

Pubmed Central ID

  • 10513320

International Standard Serial Number (ISSN)

  • 0009-9155

Digital Object Identifier (DOI)

  • 10.1177/155005949903000406

Language

  • eng