Functional Multiple-Set Canonical Correlation Analysis

Heungsun Hwang, Kwanghee Jung, Yoshio Takane, Todd S. Woodward

Research output: Contribution to journalArticle

10 Scopus citations

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.

Original languageEnglish
Pages (from-to)48-64
Number of pages17
JournalPsychometrika
Volume77
Issue number1
DOIs
StatePublished - Jan 2012

Keywords

  • functional canonical correlation analysis
  • functional data
  • functional magnetic resonance imaging data
  • multiple-set canonical correlation analysis

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