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Individualized functional networks reconfigure with cognitive state.

Mehraveh Salehi1, Amin Karbasi1, Daniel S Barron2

  • 1Department of Electrical Engineering, Yale University, New Haven, CT, 06511, USA; Yale Institute for Network Science (YINS), Yale University, New Haven, CT, 06511, USA.

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Human brain networks dynamically reconfigure across cognitive states and individuals. This dynamic functional network organization can predict cognitive state with high accuracy, challenging the notion of static brain networks.

Keywords:
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Area of Science:

  • Neuroscience
  • Cognitive Neuroscience
  • Network Science

Background:

  • Human brain functional organization dynamically shifts with cognitive states and individual differences.
  • Previous models often treated brain functional networks as static entities.

Purpose of the Study:

  • To investigate state- and subject-specific functional network parcellation using fMRI data.
  • To determine if brain functional networks are spatially fixed or dynamically reconfigurable.

Main Methods:

  • Utilized functional magnetic resonance imaging (fMRI) data across multiple cognitive states (task and rest).
  • Developed a parcellation approach to measure node-to-network assignment (NNA) changes.
  • Analyzed NNA variations across cognitive states and subjects.

Main Results:

  • Demonstrated that many brain regions change network membership depending on the cognitive state.
  • Identified robust and reliable functional network reconfigurations.
  • Achieved up to 97% accuracy in predicting cognitive state based on network reconfigurations.

Conclusions:

  • Human brain functional networks are not spatially fixed but are fluid and cognitive-state dependent.
  • Dynamic network reconfigurations are crucial for cognitive state prediction.
  • Future definitions of functional networks should account for their dynamic and state-dependent nature.