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A dynamic gradient architecture generates brain activity states.

Jesse A Brown1, Alex J Lee1, Lorenzo Pasquini1

  • 1Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA.

Neuroimage
|August 1, 2022
PubMed
Summary
This summary is machine-generated.

Brain activity states arise from dynamic spatial gradients. These intrinsic gradients interact to generate diverse functional brain patterns, offering insights into brain organization.

Keywords:
Dimensionality reductionDynamical systemsFunctional connectivityGlobal signalGradients

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Computational Neuroscience

Background:

  • The human brain operates in a limited set of activity states, representable in a low-dimensional latent space.
  • Understanding the functional anatomy underlying these brain states is an ongoing challenge.

Purpose of the Study:

  • To investigate if latent dimensions derived from functional magnetic resonance imaging (fMRI) data represent intrinsic brain systems.
  • To explore how these systems interact to generate distinct brain activity states.

Main Methods:

  • Applied dimensionality reduction to task-free and task-based fMRI data.
  • Utilized dynamical systems modeling to analyze the causal interactions between identified gradients.

Main Results:

  • Identified dynamic activity gradients, including a sensory-association gradient linked to the global signal.
  • Demonstrated gradient stability across individuals and cognitive states, reflecting functional connectivity properties.
  • Showed that gradients causally interact via state-specific coupling to produce distinct brain activity patterns.

Conclusions:

  • A set of dynamic, intrinsic spatial gradients interact to define the range of possible brain activity states.
  • These findings provide a framework for understanding the functional architecture of brain states.