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Functional Multiple-Set Canonical Correlation Analysis

Published online by Cambridge University Press:  01 January 2025

Heungsun Hwang ,
Kwanghee Jung ,
Yoshio Takane  and
Todd S. Woodward
Heungsun Hwang*
Affiliation:
McGill University
Kwanghee Jung
Affiliation:
McGill University
Yoshio Takane
Affiliation:
McGill University
Todd S. Woodward
Affiliation:
University of British Columbia and British Columbia Mental Health and Addiction Research Institute
*
Requests for reprints should be sent to Heungsun Hwang, Department of Psychology, McGill University, 1205 Dr. Penfield Avenue, Montreal, QC, H3A 1B1, Canada. E-mail: [email protected]
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Abstract

We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the method solves a matrix eigen-analysis problem through the adoption of a basis expansion approach to approximating data and weight functions. We apply the proposed method to functional magnetic resonance imaging (fMRI) data to identify networks of neural activity that are commonly activated across subjects while carrying out a working memory task.

Keywords

functional datamultiple-set canonical correlation analysisfunctional canonical correlation analysisfunctional magnetic resonance imaging data
Type
Original Paper
Information
Psychometrika , Volume 77 , Issue 1 , January 2012 , pp. 48 - 64
Copyright
Copyright © 2011 The Psychometric Society

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