Brain Model of Information Based Exchange

Here we describe an “information based exchange” model of brain function that ascribes to neocortex, basal ganglia, and thalamus distinct network functions. The model allows us to analyze whole brain system set point measures, such as the rate and heterogeneity of transitions in striatum and neocortex, in the context of disease perturbations. Our closed-loop model invokes different forms of plasticity at specific tissue interfaces and their principle cell synapses to achieve these transitions. By modulating information based exchange of action potentials between modeled neocortical areas, we observe changes to these measures in simulation. We hypothesize that similar dynamic set points and modulations exist in the brain’s resting state activity, and that germ line modifications of information based exchange may increase the risk of diseases such as Huntington’s, Parkinson’s, and Alzheimer’s. Disturbances in synaptic plasticity at distinct tissue interfaces in the model may be used to estimate risks of system dysfunction and neuronal cell death from quantitative analyses of the global dynamics that maintain system set points. The model is targeted for further development using IBM’s Neural Tissue Simulator, which allows scalable elaboration of networks, tissues, and their neural and synaptic components towards ever greater complexity and biological realism. Elaboration of these simulations within each modeled neural tissue allows in silico study of therapeutic interventions in living brain tissue.