Functional connectomics from resting-state fMRI

Stephen M. Smith, Diego Vidaurre, Christian F. Beckmann, Matthew F. Glasser, Mark Jenkinson, Karla L. Miller, Thomas E. Nichols, Emma C. Robinson, Gholamreza Salimi-Khorshidi, Mark W. Woolrich, Deanna M. Barch, Kamil Uǧurbil, David C. Van Essen

Research output: Contribution to journalReview articlepeer-review

406 Scopus citations

Abstract

Spontaneous fluctuations in activity in different parts of the brain can be used to study functional brain networks. We review the use of resting-state functional MRI (rfMRI) for the purpose of mapping the macroscopic functional connectome. After describing MRI acquisition and image-processing methods commonly used to generate data in a form amenable to connectomics network analysis, we discuss different approaches for estimating network structure from that data. Finally, we describe new possibilities resulting from the high-quality rfMRI data being generated by the Human Connectome Project and highlight some upcoming challenges in functional connectomics.

Original languageEnglish
Pages (from-to)666-682
Number of pages17
JournalTrends in Cognitive Sciences
Volume17
Issue number12
DOIs
StatePublished - Dec 2013

Keywords

  • Connectomics
  • Network modelling
  • Resting-state fMRI

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