Project 5: Computational

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Abstract We will use detailed biophysical (Dynamical Systems) modeling to pursue two large questions critical to integrating and understanding the results of Projects 1-4. What are the physiological origins of the brain rhythms studied empirically in Projects 1-4? How do network level rhythms depend on the physiological properties of the underlying neuronal ensembles? Modeling uses differential equation descriptions of physiology at the level of single cells, synapses and networks. Data from Projects 2 and 4, along with prior models and in-vitro findings, will help to build and refine physiologically-plausible cell circuit models that generate oscillations. Models will help investigate how local brain rhythms, periodic (and aperiodic) sensory inputs and top-down signals combine in Active Sensing. We will rigorously test questions concerning the neuron populations, interconnections and cellular processes (e.g., conductances) that generate specific rhythms (e.g., alpha and delta) in multiple parts of the brain during Active Sensing tasks. Laminar activity profiles sampled concurrently from multiple cortical and thalamic areas in Projects 2 and 4 will allow us to model and constrain rhythmic dynamics at a network level, which is the a-priori level of analysis in Projects 1 and 3. In an “iterative loop,” models will generate testable predictions at cellular, cell-circuit and and small network levels to be tested in monkeys, and at larger network levels to be tested in humans (Core A), in each case feeding back into the modeling. Our SPECIFIC AIMS are: AIM 1: Model thalamocortical interactions underlying intrinsic sampling rhythms in Active Sensing. AIM 2: Model the physiology of selective thalamocortical entrainment to rhythmic input. An ongoing R21 AIM 3: Model the large scale circuitry orchestrating distinct operational modes of Active Sensing.. CENTER SYNERGIES: This project will use thalamic and cortical data from Project 4 to model cortical and thalamic interactions in selective entrainment to “extrinsic” rhythms, and data from Project 2 to model cortical and thalamic interactions underlying “intrinsic” rhythmic sampling of sensory input. After the computational models have incorporated sufficient empirically-derived information, results that make testable new predictions for the physiology studies will be used to refine their analyses. They will also provide tools with which to explain the effects of thalamic projections on cortical coherences seen in the analyses of projects 1 and 3. Specific model predictions will be tested with phamacological manipulations in monkeys, and with direct brain stimulation in monkeys and in selected ECoG sstudies (Core A), and the results will refine the model.