Cognitive states classification from FMRI data using support vector machines

Ye Ji, Hong Bo Liu, Xiu Kun Wang, Yi Yuan Tang

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

7 Scopus citations

Abstract

It is useful to find the sequence of hidden cognitive states that subjects pass through when performing some complex task. We present a method to classify cognitive states from fMRI data usingc SVMs. A dataset of the study of Chinese character vs.Pinyin is considered. The data images are firstly processed and transformed to normalized coordinates. The features are extracted based on activities of voxel and index of Brodmann's areas. Then, they are used as input vectors to train the classifiers of SVMs. The results indicate it is feasible for either single subject cognitive classification or multiple subjects'. The method is helpful to decode cognitive states.

Original languageEnglish
Title of host publicationProceedings of 2004 International Conference on Machine Learning and Cybernetics
Pages2919-2923
Number of pages5
StatePublished - 2004
EventProceedings of 2004 International Conference on Machine Learning and Cybernetics - Shanghai, China
Duration: Aug 26 2004Aug 29 2004

Publication series

NameProceedings of 2004 International Conference on Machine Learning and Cybernetics
Volume5

Conference

ConferenceProceedings of 2004 International Conference on Machine Learning and Cybernetics
CountryChina
CityShanghai
Period08/26/0408/29/04

Keywords

  • Classification
  • Cognitive states
  • FMRI
  • Neuroinformatics
  • SVMs

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  • Cite this

    Ji, Y., Liu, H. B., Wang, X. K., & Tang, Y. Y. (2004). Cognitive states classification from FMRI data using support vector machines. In Proceedings of 2004 International Conference on Machine Learning and Cybernetics (pp. 2919-2923). (Proceedings of 2004 International Conference on Machine Learning and Cybernetics; Vol. 5).