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Research Articles, Systems/Circuits

State-Dependent Cortical Unit Activity Reflects Dynamic Brain State Transitions in Anesthesia

Heonsoo Lee, Shiyong Wang and Anthony G. Hudetz
Journal of Neuroscience 2 December 2020, 40 (49) 9440-9454; DOI: https://doi.org/10.1523/JNEUROSCI.0601-20.2020
Heonsoo Lee
Center for Consciousness Science, Department of Anesthesiology, University of Michigan, Ann Arbor, Michigan 48105
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Shiyong Wang
Center for Consciousness Science, Department of Anesthesiology, University of Michigan, Ann Arbor, Michigan 48105
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Anthony G. Hudetz
Center for Consciousness Science, Department of Anesthesiology, University of Michigan, Ann Arbor, Michigan 48105
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Abstract

Understanding the effects of anesthesia on cortical neuronal spiking and information transfer could help illuminate the neuronal basis of the conscious state. Recent investigations suggest that the brain state identified by local field potential spectrum is not stationary but changes spontaneously at a fixed level of anesthetic concentration. How cortical unit activity changes with dynamically transitioning brain states under anesthesia is unclear. Extracellular unit activity was measured with 64-channel silicon microelectrode arrays in cortical layers 5/6 of the primary visual cortex of chronically instrumented, freely moving male rats (n = 7) during stepwise reduction of the anesthetic desflurane (6%, 4%, 2%, and 0%). Unsupervised machine learning applied to multiunit spike patterns revealed five distinct brain states. A novel desynchronized brain state with increased spike rate variability, sample entropy, and EMG activity occurred in 6% desflurane with 40.0% frequency. The other four brain states reflected graded levels of anesthesia. As anesthesia deepened the spike rate of neurons decreased regardless of their spike rate profile at baseline conscious state. Actively firing neurons with wide-spiking pattern showed increased bursting activity along with increased spike timing variability, unit-to-population correlation, and unit-to-unit transfer entropy, despite the overall decrease in transfer entropy. The narrow-spiking neurons showed similar changes but to a lesser degree. These results suggest that (1) anesthetic effect on spike rate is distinct from sleep, (2) synchronously fragmented spiking pattern is a signature of anesthetic-induced unconsciousness, and (3) the paradoxical, desynchronized brain state in deep anesthesia contends the generally presumed monotonic, dose-dependent anesthetic effect on the brain.

SIGNIFICANCE STATEMENT Recent studies suggest that spontaneous changes in brain state occur under anesthesia. However, the spiking behavior of cortical neurons associated with such state changes has not been investigated. We found that local brain states defined by multiunit activity had a nonunitary relationship with the current anesthetic level. A paradoxical brain state displaying asynchronous firing pattern and high EMG activity was found unexpectedly in deep anesthesia. In contrast, the synchronous fragmentation of neuronal spiking appeared to be a robust signature of the state of anesthesia. The findings challenge the assumption of monotonic, anesthetic dose-dependent behavior of cortical neuron populations. They enhance the interpretation of neuroscientific data obtained under anesthesia and the understanding of the neuronal basis of anesthetic-induced state of unconsciousness.

  • anesthesia
  • consciousness
  • functional connectivity
  • neural network
  • spike dynamics
  • synchronization

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The Journal of Neuroscience: 40 (49)
Journal of Neuroscience
Vol. 40, Issue 49
2 Dec 2020
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State-Dependent Cortical Unit Activity Reflects Dynamic Brain State Transitions in Anesthesia
Heonsoo Lee, Shiyong Wang, Anthony G. Hudetz
Journal of Neuroscience 2 December 2020, 40 (49) 9440-9454; DOI: 10.1523/JNEUROSCI.0601-20.2020

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State-Dependent Cortical Unit Activity Reflects Dynamic Brain State Transitions in Anesthesia
Heonsoo Lee, Shiyong Wang, Anthony G. Hudetz
Journal of Neuroscience 2 December 2020, 40 (49) 9440-9454; DOI: 10.1523/JNEUROSCI.0601-20.2020
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Keywords

  • anesthesia
  • consciousness
  • functional connectivity
  • neural network
  • spike dynamics
  • synchronization

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