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Resting-State Networks

  • Rami K. Niazy
  • David M. Cole
  • Christian F. Beckmann
  • Stephen M. Smith
Chapter
Part of the Biological Magnetic Resonance book series (BIMR, volume 30)

Abstract

Resting-state networks (RSNs) in fMRI are ‘activation-like’, spatially structured maps of grey matter brain areas exhibiting temporally correlated signal changes, which are believed to reflect neuronal activities of the ‘resting’ brain and which robustly and consistently appear in both resting and task data. They are purported to reflect the intrinsic energy demands of neuron populations that fire together with a common functional purpose. This chapter introduces the concept of RSNs and why they are of interest to neuroscience, describes their characteristics, reviews the methods used for their analysis, and discusses a few areas of application.

Keywords

Functional Connectivity Independent Component Analysis Independent Component Analysis Bold Signal Physiological Noise 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer New York 2015

Authors and Affiliations

  • Rami K. Niazy
    • 1
  • David M. Cole
    • 2
  • Christian F. Beckmann
    • 3
    • 4
  • Stephen M. Smith
    • 5
  1. 1.Biomedical Physics DepartmentKing Faisal Specialist Hospital & Research CentreRiyadhSaudi Arabia
  2. 2.Centre for Neuroscience, Division of Experimental MedicineImperial College London, Hammersmith HospitalLondonUK
  3. 3.Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging (DCCN)Radboud University NijmegenNijmegenThe Netherlands
  4. 4.MIRA Institute for Biomedical Technology and Technical MedicineUniversity of TwenteEnschedeThe Netherlands
  5. 5.Oxford University Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical NeurosciencesJohn Radcliffe HospitalOxfordUK

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