PREDICTIVE MODELING OF BIOELECTRIC ACTIVITY ON MAMMALIAN MULTILAYERED NEURONAL STRUCTURES IN THE PRESENCE OF SUPRAPHYSIOLOGICAL ELECTRIC FIELDS

项目摘要 这种多尺度建模研究的最终目标是弥合现有的三维、全尺寸和全尺寸模型之间的差距。 波、电和磁生物相互作用的宏观建模(全局建模)和细胞级建模 战略。我们的研究团队由精通各方面的工程师和神经学家组成。 必要的计算和实验方面，以填补多尺度建模中的现有空白。 多所大学基于电流密度来预测活跃神经元的时空分布 由多电极电刺激产生的物质依赖于有一套分子的“核心模型” (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 必须将输出整合到细胞外介质/基质的全球模型中，包括相关的 电极阵列。在这些水平上成功的建模将允许关于时空模式的假设 电刺激以产生关于激活输入的数量和分布的预测(基于 已知的传入轴突空间分布)。链接的分子、突触、神经元、多神经元和全局 模型将为新出现的活动神经元的时空分布预测提供基础 因此，棘波的时空分布训练活动编码了神经系统中的所有信息。 此外，我们认为所提出的多尺度建模框架构成了一个能够 对导致海马区功能异常的致病机制产生了新的见解。 尽管拟议的研究集中在海马体系统上，但我们的努力将利用我们的 我们原创的多尺度建模U01在执行期间的多尺度建模成就 格兰特，在视网膜和皮质假体领域。

Project Abstract 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 and neuroscientists that are experts in all computational and experimental aspects necessary to fill the existing gaps in multi-scale modeling. This 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. Further, we believe the proposed multiscale modeling framework constitutes an ideal platform capable of generating novel insights into the pathogenic mechanisms precipitating abnormal hippocampal function. Although the proposed research is focused on the hippocampal system, our effort will capitalize on our multiscale modeling accomplishments during the performance period of our original multiscale modeling U01 grant, in the realm of both retinal and cortical prostheses.