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Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice
10:56

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Published on: August 2, 2017

Complex propagation patterns characterize human cortical activity during slow-wave sleep.

Balázs Hangya1, Benedek T Tihanyi, László Entz

  • 1Department of Cellular and Network Neurobiology, Institute of Experimental Medicine, Hungarian Academy of Sciences, Budapest, Hungary. bhangya@cshl.edu

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
|June 17, 2011
PubMed
Summary
This summary is machine-generated.

Slow-wave activity (SWA) during non-REM sleep shows complex propagation patterns at fine spatial scales, unlike the global waves seen at larger scales. This suggests scale-dependent dynamics in brain activity during sleep.

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Area of Science:

  • Neuroscience
  • Sleep Science
  • Computational Neuroscience

Background:

  • Non-rapid eye movement (non-REM) sleep is characterized by slow-wave activity (SWA).
  • At large spatial scales, SWA propagates globally as traveling waves, potentially facilitating neural plasticity.
  • The propagation dynamics of SWA at finer spatial scales remain largely uninvestigated in humans.

Purpose of the Study:

  • To investigate the local, fine spatial scale (1-6 cm) patterns of SWA propagation during non-REM sleep.
  • To reveal the characteristics of SWA dynamics at a resolution finer than scalp EEG.

Main Methods:

  • Electrocorticographic (ECoG) recordings from subdurally implanted electrode grids.
  • Application of a nonlinear correlation technique, mutual information (MI), to analyze SWA propagation.
  • Generation of spatial correlation maps to identify propagation direction, speed, and coupling strength.

Main Results:

  • MI analysis revealed complex SWA propagation patterns at fine spatial scales, differing from large-scale global waves.
  • SWA predominantly propagated between adjacent cortical areas, with frequent spatial noncontinuities.
  • Significant convergence and divergence patterns were observed, with reciprocal and circular propagation occurring.

Conclusions:

  • SWA exhibits distinct propagation attributes depending on the observed spatial scale.
  • Large-scale SWA propagation appears orderly, while fine-scale ECoG recordings reveal complex, non-uniform dynamics during non-REM sleep.
  • These findings highlight the scale-dependent nature of cortical activity during sleep.