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Electrophysiological Substates of the Brain in Sleep and Wake

Maxwell Ruckstuhl

Open MIND January 1, 2026 DOI: 10.7302/dspace/29642 (opens in new tab) via OpenAlex

Summary

AI-generated from the abstract

The brain frequently shifts between distinct regimes of neural activity, each with different functions and behavioral features. Understanding these brain states is essential for comprehending how disorders affect the brain and how treatments are modulated by them. REM sleep contains substates that are distinct in eye movement but continuous in single-neuron and coordinated activity. Ketamine's effect on spiking and local field potential in cortex varies depending on a wake substate defined by high electromyographic activity. These findings have potential implications for treating depression and for analyzing multimodal brain data.

Study at a glance

Characteristics Peer reviewed
Keywords Electrophysiology Sleep system call Local field potential Electroencephalography Neural activity
Key finding REM sleep exhibits substates distinct in eye movement but continuous in neural activity, and ketamine's effect on cortical spiking and LFP differs during a wake substate defined by high pEMG.

Abstract

The brain shifts frequently between distinct regimes of neural activity with associated electrophysiological and behavioral features. These many brain states have different functions and subserve different goals of the animal. No understanding of the brain can be complete without characterization of its states, of how they are affected by disorders of the brain, and of how treatments are modulated by them. We present findings on the relationship between neural activity and substates of REM sleep and on the variance in ketamine's effect in cortex across substates of wake. Specifically, REM exhibits substates distinct in eye movement but continuous in single-neuron and coordinated activity, while the effect of ketamine on both spiking and LFP differs in character during a substate of wake defined by high pEMG. We discuss potential implications for treatment of depression and analysis of multimodal brain data.

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