1. Using an animal model of schizophrenia, we demonstrate for the first time that this animal model displays specific deviations from ongoing avalanche dynamics that differs from a typical imbalance of excitation/inhibition in cortex. Altered avalanche dynamics in a developmental NMDAR hypofunction model of cognitive impairment (Seshradi et al., 2018): Disturbed activity patterns in cortical networks contribute to the pathophysiology of schizophrenia (SZ). Several lines of evidence implicate NMDA receptor hypofunction in SZ, and blocking NMDA receptor signaling during early neurodevelopment produces cognitive deficits in rodent models that resemble those seen in schizophrenic patients. However, the altered network dynamics underlying these cognitive impairments largely remain to be characterized, especially at the cellular level. Here, we use in vivo two-photon calcium imaging to describe pathological dynamics, occurring in parallel with cognitive dysfunction, in a developmental NMDA receptor hypofunction model. We observed increased synchrony and specific alterations in spatiotemporal activity propagation, which could be causally linked to a previously unidentified persistent bursting phenotype. This phenotype was rescued by acute treatment with the NMDA receptor co-agonist D-serine or the GABAB receptor agonist baclofen, which similarly rescued working memory performance. It was not reproduced by optogenetic inhibition of fast-spiking interneurons. These results provide novel insight into network-level abnormalities mediating the cognitive impairment induced by NMDA receptor hypofunction. 2. We demonstrated for the first time that avalanche dynamics govern cortical activity even when animals process sensory information to execute movements. This generalizes the framework of avalanches and criticality from resting activity to cortical processing of sensory information and motor commands. Maintained avalanche dynamics during task-induced changes of neuronal activity in nonhuman primates (Chou et al., 2017): Sensory events, cognitive processing and motor actions correlate with transient changes in neuronal activity. In cortex, these transients form widespread spatiotemporal patterns with largely unknown statistical regularities. Here, we show that activity associated with behavioral events carry the signature of scale-invariant spatiotemporal clusters, neuronal avalanches. Using high-density microelectrode arrays in nonhuman primates, we recorded extracellular unit activity and the local field potential (LFP) in premotor and prefrontal cortex during motor and cognitive tasks. Unit activity and negative LFP deflections (nLFP) consistently changed in rate at single electrodes during tasks. Accordingly, nLFP clusters on the array deviated from scale-invariance compared to ongoing activity. Scale-invariance was recovered using 'adaptive binning', that is identifying clusters at temporal resolution given by task-induced changes in nLFP rate. Measures of LFP synchronization confirmed and computer simulations detailed our findings. We suggest optimization principles identified for avalanches during ongoing activity to apply to cortical information processing during behavior. 3. We demonstrate solid evidence in sleep deprived normal human subjects and sleep deprived rats that sleep deprivation results from a deviation in avalanche dynamics due to a secondary process that interferes with ongoing critical dynamics in cortex. This introduces a new model of sleep (to recover from deviations in critical dynamics). The Interplay between Long- and Short-Range Temporal Correlations Shapes Cortex Dynamics across Vigilance States (Klaus et al., 2017): Increasing evidence suggests that cortical dynamics during wake exhibits long-range temporal correlations suitable to integrate inputs over extended periods of time to increase the signal-to-noise ratio in decision making and working memory tasks. Accordingly, sleep has been suggested as a state characterized by a breakdown of long-range correlations. However, detailed measurements of neuronal timescales that support this view have so far been lacking. Here, we show that the cortical timescales measured at the individual neuron level in freely behaving male rats change as a function of vigilance state and time awake. Although quiet wake and rapid eye movement (REM) sleep are characterized by similar, long timescales, these long timescales are abrogated in non-REM sleep. We observe that cortex dynamics exhibits rapid transitions between long-timescale states and sleep-like states governed by short timescales even during wake. This becomes particularly evident during sleep deprivation, when the interplay between these states can lead to an increasing disruption of long timescales that are restored after sleep. Experiments and modeling identify the intrusion of neuronal offline periods as a mechanism that disrupts the long timescales arising from reverberating cortical network activity. Our results provide novel mechanistic and functional links among behavioral manifestations of sleep, wake, and sleep deprivation and specific measurable changes in the network dynamics relevant for characterizing the brain's changing information-processing capabilities. They suggest a network-level function of sleep to reorganize cortical networks toward states governed by long timescales to ensure efficient information integration for the time awake. SIGNIFICANCE STATEMENT Lack of sleep deteriorates several key cognitive functions, yet the neuronal underpinnings of these deficits have remained elusive. Cognitive capabilities are generally believed to benefit from a neural circuit's ability to reliably integrate information. Persistent network activity characterized by long timescales may provide the basis for this integration in cortex. Here, we show that long-range temporal correlations indicated by slowly decaying autocorrelation functions in neuronal activity are dependent on vigilance states. Although wake and rapid eye movement (REM) sleep exhibit long timescales, these long-range correlations break down during non-REM sleep. Our findings thus suggest two distinct states in terms of timescale dynamics. During extended wake, the rapid switching to sleep-like states with short timescales can lead to an overall decline in cortical timescales. See also Decline of long-range temporal correlations in the human brain during sustained wakefulness. (Meisel et al., 2017). 4. We were able to provide a connection between certain models in neuroscience and the Neutral Theory of genetic drift. See Neutral Theory and Scale-Free Neural Dynamics (Martinello et al., 2017). 5. In our collaboration with Peter Basser (NICHD) we continued to identify the mechanism of BOLD independent MR signals in neural tissue. See Fast, Na+ /K+ pump driven, steady-state transcytolemmal water exchange in neuronal tissue: A study of rat brain cortical cultures (Bai et al., 2018).
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