CRCNS US-French Research Proposal: Impact of network state on corticocortical communication

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In great contrast to a digital computer, the brain is constantly active and responses to stimuli of single cells are noisy and unreliable. Instead of speed and accuracy by a single processor, brains rely on the parallel, simultaneous sampling of information by thousands of neurons. Neuronal populations, albeit noisy and slow, together generate sufficiently accurate perceptual representations of reality to conduct behavior much more efficiently and orders of magnitude faster than any computer in existence today. Key to such parallel processing is efficient communication among neural networks in the cortex of the brain. The interaction of the fluctuating activity of the brain and the ability of populations of neurons to efficiently communicate between cortical networks in order to encode information is unknown. In this project, the investigators explore and test the mechanisms and rules of cortico-cortical communication using state of the art experimental and computational tools. The work will not only address long-standing hypotheses about cortico-cortical communication and result in the development of novel computational analysis tools but also help shed light on cognitive disorders believed to be due in part to faulty information transmission between cortical areas. In addition, the project will provide opportunities for students from diverse backgrounds to participate in cutting-edge international interdisciplinary research.In this project, the investigators examine how visual responses are communicated between local networks in layers 2-3 of primary visual cortex under those two well-defined network states. Specifically, the investigators will use electrophysiological, optogenetic, pharmacological and computational approaches to quantify cellular and network communication in primary visual cortex in vivo under network states that have been proposed to ideally allow corticocortical communication: gamma oscillations and non-oscillatory noisy states globally termed asynchronous irregular. The investigators are able to elicit and control those states with specific visual stimulation and will characterize the states’ neuronal background activity as well as their role in efficient transmission of information between cortical columns. The large volume and new qualitative aspects of the data will allow the investigators to generate novel analysis algorithms and theoretical approaches, as well as large-scale computational models. Ultimately, the computational models will help understand population dynamics for the transmission of information in well-defined network states. This project is funded jointly by the Neural Systems Cluster in the Biological Sciences Directorate and the Division of Information and Intelligent Systems in the Computer and information Science and Engineering Directorate. A companion project is being funded by the French National Research Agency (ANR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.