Predictive modeling of bioelectric activity on mammalian multilayered neuronal st

描述(申请人提供)：这项多尺度建模研究的最终目标是弥合电和磁生物相互作用的三维、全波、宏观建模(全局建模)和细胞级别建模策略之间存在的差距。我们的研究团队由工程师、神经科学家、生物物理学家、外科医生和计算机科学家组成，他们是填补多尺度建模中现有空白所必需的所有计算和实验方面的专家。多所大学根据多电极电刺激产生的电流密度来预测活跃神经元的时空分布，这一新的努力依赖于拥有一套关于分子(受体-通道动力学)、突触、神经元和多神经元活动的核心模型。这些模型及其输入和输出必须整合到细胞外介质/基质的全球模型中，包括相关的多电极阵列。在这些水平上的成功建模将允许关于电刺激的时空模式的假设产生关于激活输入的数量和分布的预测(基于已知的传入轴突的空间分布)。连接的分子、突触、神经元、多神经元和全局模型将为新出现的预测活跃神经元的时空分布提供基础，从而为编码神经系统中所有信息的棘波活动的时空分布提供基础。我们的研究工作将 利用我们在视网膜和皮质假体领域的成就，并将这些作为我们将在拟议活动中开发的多尺度预测建模方法的试验台。

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.