Predictive modeling of bioelectric activity on mammalian multilayered neuronal st

描述（由申请人提供）：该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）与细胞级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、生物病理学家、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需的所有计算和实验方面的专家。这种新的多所大学的努力，以预测活动神经元的时空分布的基础上，由多电极电刺激产生的电流密度取决于有一组“核心模型”的分子（受体通道动力学），突触，神经元和多神经元活动。这些模型及其输入和输出必须整合到包括相关多电极阵列的细胞外介质/基质的全局模型中。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（基于传入轴突的已知空间分布）。链接的分子，突触，神经元，多神经元，和全球模型将提供基础的新兴预测的时空分布的活跃的神经元，因此，时空分布的尖峰列车活动编码的所有信息在神经系统中。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，并将其用作我们将在拟议活动中开发的多尺度预测建模方法的测试平台。

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.