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Brainstem Modulation of Large-Scale Intrinsic Cortical Activity Correlations.

R L van den Brink1, T Pfeffer1, T H Donner1,2,3

  • 1Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

Frontiers in Human Neuroscience
|October 26, 2019
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Summary
This summary is machine-generated.

Brain

Keywords:
acetycholinebrainstemdopaminefunctional connectivityneuromodulationnorepinepherineresting-stateserotonin

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Area of Science:

  • Neuroscience
  • Computational Neuroscience

Background:

  • Intrinsic brain activity exhibits continuous fluctuations, organized into large-scale correlated networks.
  • These fluctuations are shaped by anatomical connections and influenced by subcortical neuromodulatory systems.
  • Neuromodulatory systems are implicated in neurological and psychiatric disorders and their treatments.

Purpose of the Study:

  • To review how subcortical neuromodulatory systems influence intrinsic activity correlations in the cortex.
  • To synthesize emerging principles governing the interaction between neuromodulation and large-scale brain network dynamics.
  • To explore the implications for understanding brain disorders and developing novel treatments.

Main Methods:

  • Review of recent studies investigating neuromodulatory effects on intrinsic cortical activity.
  • Focus on non-invasive human brain recordings (e.g., fMRI, EEG).
  • Integration of findings across human, monkey, and rodent models.

Main Results:

  • Neuromodulatory systems play a critical role in shaping the temporal and spatial structure of intrinsic cortical correlations.
  • Variations in neuromodulation impact network strength, topography, and topology.
  • Emerging principles highlight the influence of specific neuromodulators and receptors on network dynamics.

Conclusions:

  • Understanding neuromodulatory influences on intrinsic brain activity is crucial for deciphering healthy brain function.
  • Altered cortical dynamics in neurological and psychiatric disorders may be linked to disrupted neuromodulation.
  • This knowledge can inform the development of mechanistically inspired biomarkers and personalized treatments.