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.
The relevance of this research to the public health consists of the development of a generalizable engineering approach to the optimization of existing and proposed neural interfaces, which will produce enormous benefit to the neurologically disabled. We expect that the results of this work will profoundly affect the way we design neurostimulating electrodes and provide a deep understanding of the optimal shape and size of electrodes, waveform characteristics and timing differences between stimulating currents in adjacent electrodes, and current levels to name a few.
|Song, Dong; Chan, Rosa H M; Robinson, Brian S et al. (2015) Identification of functional synaptic plasticity from spiking activities using nonlinear dynamical modeling. J Neurosci Methods 244:123-35|
|Wang, Boshuo; Petrossians, Artin; Weiland, James D (2014) Reduction of edge effect on disk electrodes by optimized current waveform. IEEE Trans Biomed Eng 61:2254-63|
|Song, Dong; Harway, Madhuri; Marmarelis, Vasilis Z et al. (2014) Extraction and restoration of hippocampal spatial memories with non-linear dynamical modeling. Front Syst Neurosci 8:97|