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James A Roberts1,2, Leonardo L Gollo3,4, Romesh G Abeysuriya5

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This study models human brain activity as dynamic waves, revealing metastable patterns like traveling and spiral waves. These findings unify diverse neuroimaging data and explain brain state transitions.

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Complex Systems

Background:

  • Traveling brain waves are observed across species and states but their human emergence is poorly understood.
  • Spontaneous neural activity in the human brain exhibits complex nonlinear dynamics.

Purpose of the Study:

  • To model large-scale spontaneous neural activity on a human whole-brain network.
  • To understand the emergence and nature of traveling brain waves in the human brain.

Main Methods:

  • Utilized a whole-brain network model derived from human tractography.
  • Analyzed complex nonlinear dynamics of spontaneous neural activity.
  • Identified and characterized emergent spatiotemporal wave patterns.

Main Results:

  • Discovered a variety of 3D wave patterns including traveling waves, spiral waves, sources, and sinks.
  • Observed that these patterns are metastable, with sequential state transitions.
  • Found transitions correspond to phase flow reconfigurations driven by nonlinear instabilities.

Conclusions:

  • The metastable dynamics align with empirical data from electrocorticography, MEG, and cortical tissue recordings.
  • This dynamic, wave-based framework unifies diverse neuroimaging phenomena.
  • The study provides a new perspective on functional brain networks and predicts future experimental outcomes.