Predictive modeling of bioelectric activity on mammalian multilayered neuronal st

University Of Utah, Salt Lake City UT

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Abstract

DESCRIPTION (provided by applicant): The end goal of this multiscale modeling research is to bridge the gap existing between three-dimensional, full- wave, macro-modeling of electrical and magnetic biointeractions (global modeling) and cellular-level modeling strategies. Our research team is composed of engineers, neuroscientists, biophysicists, surgeons, and computer scientists that are experts in all computational and experimental aspects necessary to fill the existing gaps in multi-scale modeling. This new multi-university effort to predict spatio-temporal distributions of active neurons based on current densities created by multi-electrode electrical stimulation depends on having a set of core models of molecular (receptor-channel kinetics), synaptic, neuron, and multi-neuron activity. These models and their inputs and outputs must be integrated into a global model of the extracellular media/matrix including relevant multi-electrode arrays. Successful modeling at these levels will allow hypotheses about space-time patterns of electrical stimulation to produce predictions about the number and distribution of activated inputs (based on known spatial distributions of afferent axons). The linked molecular, synaptic, neuron, multi-neuron, and global model will provide the basis for emerging predictions of the spatio-temporal distribution of active neurons and thus, the spatio-temporal distributions of spike train activity that encode all information in the nervous system. Our research effort will capitalize on our accomplishments in the realm of retinal and cortical prostheses, and use these as test beds for the multiscale predictive modeling methods that we will develop within the proposed activity.