Decomposition of spontaneous brain activity into distinct fMRI co-activation patterns

Xiao Liu, Catie Chang, Jeff H. Duyn

Research output: Contribution to journalArticlepeer-review

128 Scopus citations


Recent fMRI studies have shown that analysis of the human brain's spontaneous activity may provide a powerful approach to reveal its functional organization. Dedicated methods have been proposed to investigate co-variation of signals from different brain regions, with the goal of revealing neuronal networks (NNs) that may serve specialized functions. However, these analysis methods generally do not take into account a potential non-stationary (variable) interaction between brain regions, and as a result have limited effectiveness. To address this, we propose a novel analysis method that uses clustering analysis to sort and selectively average fMRI activity time frames to produce a set of co-activation patterns. Compared to the established networks extracted with conventional analysis methods, these co-activation patterns demonstrate novel network features with apparent relevance to the brain's functional organization.

Original languageEnglish (US)
Article number101
JournalFrontiers in Systems Neuroscience
Issue numberDEC
StatePublished - Dec 4 2013

All Science Journal Classification (ASJC) codes

  • Neuroscience (miscellaneous)
  • Developmental Neuroscience
  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience


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