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Sleep disrupts complex spiking dynamics in the neocortex and hippocampus
Joaquín González1,2, Matias Cavelli3, Adriano B L Tort2
1Departamento de Fisiología de Facultad de Medicina, Universidad de la República, Montevideo, Uruguay.
Plos One
|August 17, 2023
Summary
During slow-wave sleep (SWS), brain activity complexity decreases due to synchronous neuronal DOWN states. Removing these DOWN states makes brain activity patterns during sleep and wakefulness indistinguishable.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Systems Neuroscience
Background:
- Neuronal interactions create complex dynamics in cortical networks.
- Brain signal complexity decreases during slow-wave sleep (SWS), but the mechanisms are unclear.
Purpose of the Study:
- To investigate the neural mechanisms behind the decrease in brain signal complexity during SWS.
- To determine the role of synchronous neuronal DOWN states in SWS-associated complexity reduction.
Main Methods:
- Analysis of in-vivo electrophysiological recordings from rat neocortical and hippocampal neuronal populations.
- Implementation of a critical branching model of cortical activity.
Main Results:
- Synchronous neuronal DOWN states during SWS increase population activity recurrence and determinism, reducing signal complexity.
- Excluding DOWN states renders brain activity recordings from wakefulness and sleep states indistinguishable.
- A computational model demonstrated that inducing DOWN states in a subset of neurons replicates the observed complexity decrease during SWS.
Conclusions:
- Synchronous neuronal DOWN states are the primary drivers of complexity reduction in brain signals during SWS.
- The emergence of DOWN states alters cortical network dynamics, leading to more deterministic activity patterns.
- These findings provide a mechanistic explanation for complexity changes in brain activity across different sleep-wake states.
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