Semi-supervised subspace analysis of human functional magnetic resonance 
imaging data

Shelton, J; Blaschko, M; Bartels, A

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Semi-supervised subspace analysis of human functional magnetic resonance imaging data

Shelton, J., Blaschko, M., & Bartels, A.(2009). Semi-supervised subspace analysis of human functional magnetic resonance imaging data (185). Tübingen, Germany: Max Planck Institute for Biological Cybernetics.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-C509-D Version Permalink: https://hdl.handle.net/21.11116/0000-0002-85B8-8

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Shelton, J^{1, 2}, Author
Blaschko, M^{1, 2}, Author
Bartels, A^{2, 3}, Author

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1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794
3Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798

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Abstract: Kernel Canonical Correlation Analysis is a very general technique for subspace learning that incorporates
PCA and LDA as special cases. Functional magnetic resonance imaging (fMRI) acquired data is naturally
amenable to these techniques as data are well aligned. fMRI data of the human brain is a particularly interesting
candidate. In this study we implemented various supervised and semi-supervised versions of KCCA on human
fMRI data, with regression to single- and multi-variate labels (corresponding to video content subjects viewed
during the image acquisition). In each variate condition, the semi-supervised variants of KCCA performed better
than the supervised variants, including a supervised variant with Laplacian regularization. We additionally analyze
the weights learned by the regression in order to infer brain regions that are important to different types of visual
processing.

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Dates: Date issued: 2009-05

Publication Status: Issued

Pages: 10

Publishing info: Tübingen, Germany : Max Planck Institute for Biological Cybernetics

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Identifiers: Report Nr.: 185
BibTex Citekey: 5901

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Title: Technical Report of the Max Planck Institute for Biological Cybernetics

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Pages: - Volume / Issue: 185 Sequence Number: - Start / End Page: - Identifier: -