Multisubject independent component analysis of fMRI: A decade of intrinsic networks, default mode, and neurodiagnostic discovery

Vince D. Calhoun, Tülay Adali

Research output: Contribution to journalArticle

Abstract

Since the discovery of functional connectivity in fMRI data (i.e., temporal correlations between spatially distinct regions of the brain) there has been a considerable amount of work in this field. One important focus has been on the analysis of brain connectivity using the concept of networks instead of regions. Approximately ten years ago, two important research areas grew out of this concept. First, a network proposed to be a default mode of brain function since dubbed the default mode network was proposed by Raichle. Secondly, multisubject or group independent component analysis (ICA) provided a data-driven approach to study properties of brain networks, including the default mode network. In this paper, we provide a focused review of how ICA has contributed to the study of intrinsic networks. We discuss some methodological considerations for group ICA and highlight multiple analytic approaches for studying brain networks. We also show examples of some of the differences observed in the default mode and resting networks in the diseased brain. In summary, we are in exciting times and still just beginning to reap the benefits of the richness of functional brain networks as well as available analytic approaches.

Original languageEnglish (US)
Article number6268324
Pages (from-to)60-73
Number of pages14
JournalIEEE reviews in biomedical engineering
Volume5
DOIs
StatePublished - Dec 18 2012
Externally publishedYes

Keywords

  • Brain
  • complex-valued
  • fMRI
  • independent component analysis (ICA)
  • phase

ASJC Scopus subject areas

  • Biomedical Engineering

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