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Related Experiment Video

Updated: May 20, 2026

Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study
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Published on: July 21, 2021

Fundamental dynamical modes underlying human brain synchronization.

Catalina Alvarado-Rojas1, Michel Le Van Quyen

  • 1Centre de Recherche de l'Institut du Cerveau et de la Moelle Épinière, INSERM, UMRS 975 and CNRS UMR 7225, UPMC, Hôpital de la Pitié-Salpêtrière, 75651 Paris cedex 13, France.

Computational and Mathematical Methods in Medicine
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Summary

Brain activity during sleep and wakefulness shows complex synchronization patterns. These patterns can be simplified into a few key dynamic modes, revealing distinct brain states and their transitions.

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Systems Neuroscience

Background:

  • Understanding the long-term dynamics of interacting cortical and subcortical brain networks across the wake-sleep cycle is limited.
  • High-dimensional brain recording data necessitates effective summary information for analysis and modeling.

Purpose of the Study:

  • To investigate local and long-range synchronization patterns in brain networks over several days using intracranial recordings.
  • To develop a compact representation for understanding complex brain dynamics during the wake-sleep cycle.

Main Methods:

  • Utilized large-scale intracranial recordings from epileptic patients during seizure-free periods.
  • Applied principal component analysis to create a reduced-dimension state space representation of brain synchrony.
  • Analyzed synchronization dynamics across multiple brain regions over extended durations.

Main Results:

  • Complex brain synchrony patterns during wake-sleep cycles can be represented by a small number of characteristic dynamic modes.
  • These dynamic modes exhibit remarkable similarity across patients, irrespective of electrode placement.
  • Transitions between behavioral states follow specific trajectories within this dynamic mode state space.

Conclusions:

  • The study provides a simplified yet informative model for brain network dynamics across the wake-sleep cycle.
  • Dominant synchrony patterns are successively activated, correlating with different brain states at a coarse temporal resolution.
  • This approach offers insights into the fundamental organization of brain states and their transitions.