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Complexity of cortical wave patterns of the wake mouse cortex.

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.

SUBMITTER: Liang Y

PROVIDER: S-EPMC10015011 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Complexity of cortical wave patterns of the wake mouse cortex.

Liang Yuqi Y Liang Junhao J Song Chenchen C Liu Mianxin M Knöpfel Thomas T Gong Pulin P Zhou Changsong C

Nature communications 20230315 1

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 ...[more]

PMID: 36918572

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Project description:During non-rapid eye movement (NREM) sleep, cortical neurons alternate between ON periods of firing and OFF periods of silence. This bi-stability, which is largely synchronous across neurons, is reflected in the EEG as slow waves. Slow-wave activity (SWA) increases with wake duration and declines homeostatically during sleep, but the underlying mechanisms remain unclear. One possibility is neuronal "fatigue": high, sustained firing in wake would force neurons to recover with more frequent and longer OFF periods during sleep. Another possibility is net synaptic potentiation during wake: stronger coupling among neurons would lead to greater synchrony and therefore higher SWA. Here, we obtained a comparable increase in sustained firing (6 h) in cortex by: (1) keeping mice awake by exposure to novel objects to promote plasticity and (2) optogenetically activating a local population of cortical neurons at wake-like levels during sleep. Sleep after extended wake led to increased SWA, higher synchrony, and more time spent OFF, with a positive correlation between SWA, synchrony, and OFF periods. Moreover, time spent OFF was correlated with cortical firing during prior wake. After local optogenetic stimulation, SWA and cortical synchrony decreased locally, time spent OFF did not change, and local SWA was not correlated with either measure. Moreover, laser-induced cortical firing was not correlated with time spent OFF afterward. Overall, these results suggest that high sustained firing per se may not be the primary determinant of SWA increases observed after extended wake.Significance statementA long-standing hypothesis is that neurons fire less during slow-wave sleep to recover from the "fatigue" accrued during wake, when overall synaptic activity is higher than in sleep. This idea, however, has rarely been tested and other factors, namely increased cortical synchrony, could explain why sleep slow-wave activity (SWA) is higher after extended wake. We forced neurons in the mouse cortex to fire at high levels for 6 h in 2 different conditions: during active wake with exploration and during sleep. We find that neurons need more time OFF only after sustained firing in wake, suggesting that fatigue due to sustained firing alone is unlikely to account for the increase in SWA that follows sleep deprivation.

Project description:Artificial forms of mechanical limb stimulation are used within multiple fields of study to determine the level of cortical excitability and to map the trajectory of neuronal recovery from cortical damage or disease. Square-wave mechanical or electrical stimuli are often used in these studies, but a characterization of sensory-evoked response properties to square-waves with distinct fundamental frequencies but overlapping harmonics has not been performed. To distinguish between somatic stimuli, the primary somatosensory cortex must be able to represent distinct stimuli with unique patterns of activity, even if they have overlapping features. Thus, mechanical square-wave stimulation was used in conjunction with regional and cellular imaging to examine regional and cellular response properties evoked by different frequencies of stimulation. Flavoprotein autofluorescence imaging was used to map the somatosensory cortex of anaesthetized C57BL/6 mice, and in vivo two-photon Ca2+ imaging was used to define patterns of neuronal activation during mechanical square-wave stimulation of the contralateral forelimb or hindlimb at various frequencies (3, 10, 100, 200, and 300 Hz). The data revealed that neurons within the limb associated somatosensory cortex responding to various frequencies of square-wave stimuli exhibit stimulus-specific patterns of activity. Subsets of neurons were found to have sensory-evoked activity that is either primarily responsive to single stimulus frequencies or broadly responsive to multiple frequencies of limb stimulation. High frequency stimuli were shown to elicit more population activity, with a greater percentage of the population responding and greater percentage of cells with high amplitude responses. Stimulus-evoked cell-cell correlations within these neuronal networks varied as a function of frequency of stimulation, such that each stimulus elicited a distinct pattern that was more consistent across multiple trials of the same stimulus compared to trials at different frequencies of stimulation. The variation in cortical response to different square-wave stimuli can thus be represented by the population pattern of supra-threshold Ca2+ transients, the magnitude and temporal properties of the evoked activity, and the structure of the stimulus-evoked correlation between neurons.

Dataset Information

Complexity of cortical wave patterns of the wake mouse cortex.

Publications

Complexity of cortical wave patterns of the wake mouse cortex.

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