State modulation in dynamical neuronal network models

报告专家:Prof.ChengchengHUANG(University of Pittsburgh)

报告时间:2023年12月26日 10:30-11:30


报告摘要:Neuronal responses to sensory stimuli can be strongly modulated by animal's brain state. Cognitive processes, such as attention and arousal state, have been shown to modulate activity statistics of neuronal population responses. However, theunderlying modulatory mechanisms remain unclear. We show that spatiotemporal dynamics in neuronal network models can produce large population-wide shared variability, consistent with cortical recordings. We predict that attention reduces neuronal correlations by stabilizing network dynamics.Further, we analyze the dynamical regimes of spatial network models and identify a parameter regime of spatiotemporal chaos. Lastly, we study how network state impacts information processing in the network and show that attention improves information flow by suppressing the internal dynamics of the recurrent network.