Guided learning algorithms: An application of constrained spectral partitioning to functional magnetic resonance imaging (fMRI)

Henry L. Phillips, Peter B. Walker, Carrie H. Kennedy, Owen Carmichael, Ian N. Davidson

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

3 Scopus citations

Abstract

Innovations in neuro-technology have created a potential gap in our ability to measure human performance and decision making in dynamic environments. Therefore, a need exists to create more reliable testing methodologies and data analytic solutions. The primary aim of this paper is to describe work to integrate subject matter expertise with algorithms designed to measure human brain activity in real time. Specifically, Guided Learning using constrained spectral partitioning to increase the reliability and interpretability of fMRI data is explicated and applied as a test case to the Default Mode Network in the elderly population. How Guided Learning can be further applied to other neuro-imaging technologies that may be more conducing to furthering the field of augmented cognition is discussed.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages709-716
Number of pages8
Volume8027 LNAI
DOIs
StatePublished - 2013
Event7th International Conference on Foundations of Augmented Cognition, AC 2013, Held as Part of 15th International Conference on Human-Computer Interaction, HCI International 2013 - Las Vegas, NV, United States
Duration: Jul 21 2013Jul 26 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8027 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other7th International Conference on Foundations of Augmented Cognition, AC 2013, Held as Part of 15th International Conference on Human-Computer Interaction, HCI International 2013
CountryUnited States
CityLas Vegas, NV
Period7/21/137/26/13

Keywords

  • augmented cognition
  • fMRI
  • functional connectivity

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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    Phillips, H. L., Walker, P. B., Kennedy, C. H., Carmichael, O., & Davidson, I. N. (2013). Guided learning algorithms: An application of constrained spectral partitioning to functional magnetic resonance imaging (fMRI). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8027 LNAI, pp. 709-716). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8027 LNAI). https://doi.org/10.1007/978-3-642-39454-6_76