An illustrative application of generalized structured component analysis for brain connectivity research

Kwanghee Jung, Sang Soo Cho, Jaehoon Lee, Seungman Kim, Ji Hoon Ryoo

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Generalized structured component analysis (GSCA) has been extensively enhanced in terms of data-analytic capability and flexibility as well as computational efficiency. This article illustrates a novel application of GSCA for brain connectivity research, the purpose of which is to facilitate its uses with functional neuroimaging data among applied researchers and practitioners. Using data collected during encoding of source memory in a functional magnetic resonance imaging study, this article demonstrates how to specify and evaluate a fully and bidirectionally connected structural model of brain connectivity using GSCA. Implications of the GSCA approach and future directions for brain research are discussed.

Original languageEnglish
Pages (from-to)273-289
Number of pages17
JournalBehaviormetrika
Volume47
Issue number1
DOIs
StatePublished - Jan 1 2020

Keywords

  • Brain connectivity
  • Functional neuroimaging data
  • Generalized structured component analysis
  • Source memory
  • Structural equation modeling

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