Complexity of cortical wave patterns of the wake mouse cortex

Yuqi Liang, Junhao Liang, Chenchen Song, Mianxin Liu, Thomas Knöpfel (), Pulin Gong () and Changsong Zhou ()
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Yuqi Liang: Hong Kong Baptist University
Junhao Liang: Hong Kong Baptist University
Chenchen Song: Laboratory for Neuronal Circuit Dynamics, Imperial College London
Mianxin Liu: Hong Kong Baptist University
Thomas Knöpfel: Laboratory for Neuronal Circuit Dynamics, Imperial College London
Pulin Gong: University of Sydney
Changsong Zhou: Hong Kong Baptist University

Nature Communications, 2023, vol. 14, issue 1, 1-13

Abstract: Abstract Rich spatiotemporal dynamics of cortical activity, including complex and diverse wave patterns, have been identified during unconscious and conscious brain states. Yet, how these activity patterns emerge across different levels of wakefulness remain unclear. Here we study the evolution of wave patterns utilizing data from high spatiotemporal resolution optical voltage imaging of mice transitioning from barbiturate-induced anesthesia to wakefulness (N = 5) and awake mice (N = 4). We find that, as the brain transitions into wakefulness, there is a reduction in hemisphere-scale voltage waves, and an increase in local wave events and complexity. A neural mass model recapitulates the essential cellular-level features and shows how the dynamical competition between global and local spatiotemporal patterns and long-range connections can explain the experimental observations. These mechanisms possibly endow the awake cortex with enhanced integrative processing capabilities.

Date: 2023
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DOI: 10.1038/s41467-023-37088-6

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