Intrinsic brain activity and resting state networks

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

4 Scopus citations


Intrinsic brain activity, that is, neural processes unrelated to immediate sensory and motor functions, has been known to exist for nearly a century. However, the physiological functions of this activity remain poorly understood. Resting state functional magnetic resonance imaging (RS-fMRI) has emerged as a major technique for studying the brain’s intrinsic activity. This review briefly discusses the history of related scientific developments antecedent to the discovery of RS-fMRI. Next, the major features of intrinsic activity, as observed using RSfMRI, are presented in some detail. Intrinsic activity is spatio-temporally organized into functional systems known as resting state networks (RSNs). Several aspects of RSNs are discussed, including topographic relations to task-evoked responses, plasticity, state dependence, and development over the lifespan. Several crucial aspects of practical RS-fMRI are discussed, including the problem of artifact and strategies for minimizing the impact of artifact. The last part of this review discusses the current state of RS-fMRI as applied to the study of neurologic and psychiatric conditions.

Original languageEnglish
Title of host publicationNeuroscience in the 21st Century
Subtitle of host publicationFrom Basic to Clinical, Second Edition
PublisherSpringer New York
Number of pages52
ISBN (Electronic)9781493934744
ISBN (Print)9781493934737
StatePublished - Jan 1 2016


  • Acquisition
  • Alzheimer’s disease (AD)
  • Anatomical vs. functional connectivity
  • Artifact
  • Artifact reduction
  • Autism spectrum disorders (ASD)
  • BOLD RS-fMRI acquisition
  • BOLD fMRI functional connectivity
  • Blood oxygen level dependent (BOLD) signal
  • Covariance
  • Default mode network (DMN)
  • Depends on level of arousal
  • Frame censoring
  • Functional connectivity
  • Graph theory
  • Intrinsic BOLD fluctuations
  • Lifespan changes
  • Nonneural low-frequency oscillations
  • Phaseamplitude coupling (PAC)
  • Physiological noise
  • Plasticity
  • Practical considerations
  • Preprocessing schemes
  • Rebalancing of synaptic weights
  • Resting state fMRI (RS-fMRI)
  • Resting state networks (RSNs)
  • Spatial independent component analysis (sICA)
  • Voxelwise amplitude of low-frequency fluctuations (ALFF)


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