Integrated Biophysical and Neural Model of Electrical Stimulation Effects

项目摘要 电刺激广泛用于激活和/或破坏神经元活动。尽管其关键 在实验和临床神经科学中的重要性，目前还没有有效的方法来预测 大脑的哪些神经元将被给定的刺激机制激活。根据我们的试播集 研究，我们建议在这里开发一种新的计算方法来预测特定的神经元 其将基于神经元的形状、位置、类型和 连通性。我们将使用生物物理模型来计算激活电流的空间分布， 然后将这个分布与轴突和树突的空间分布和方向进行卷积 的主要锥体和中间神经元细胞类型，以确定其发射的概率。然后我们将 通过皮层回路传播这种活动。我们将模拟不同的物种（大鼠，小鼠，人类） 和皮质区（初级感觉和联想）。我们将研究睡眠阶段的影响， 诱发丘脑皮层网络的背景活动，包括特征性睡眠节律 活动模型的预测将通过广泛的经验测量进行验证，主要是 使用先进的显微镜方法在小鼠中进行钙成像， 以高分辨率表征体积。细胞类型特异性标记和解剖重建 将允许识别不同的神经元群体并测量它们的激活概率。 这将通过电压敏感染料成像和层状电生理记录来补充， 提供时间分辨率。层流记录将在人类中重复， 术中和半慢性环境。将根据验证研究修改模型。的 综合生物物理和神经模型与文档和教程将提供在 web.

Project Abstract Electrical stimulation is widely used to activate and/or disrupt neuronal activity. Despite its critical importance in experimental and clinical neuroscience, at present, there is no validated method to predict which neural elements of the brain will be activated by a given stimulation regime. Based on our pilot studies, we propose here to develop a novel computational approach for predicting the specific neurons which will be activated by a given stimulation protocol, based on neuron shape, location, type and connectivity. We will use biophysical modeling to calculate the spatial distribution of activating currents, and then convolve this distribution with the spatial distribution and orientation of the axons and dendrites of the major pyramidal and interneuron cell types to determine their probability of firing. We will then propagate this activity through the cortical circuitry. We will model different species (rats, mice, humans) and cortical areas (primary sensory and associative). We will examine the effects of sleep stage and background activity, including characteristic sleep rhythms, on the evoked thalamocortical network activity. The predictions of the model will be validated with extensive empirical measurements, primarily calcium imaging in mice using advanced microscopy methods that allow the entire relevant cortical volume to be characterized at high resolution. Cell type specific labeling and anatomical reconstructions will permit identification of different neuronal populations and measurement of their activation probability. This will be supplemented by voltage-sensitive dye imaging and laminar electrophysiological recordings to provide temporal resolution. The laminar recordings will be repeated in humans, in both acute intraoperative and semi-chronic settings. The models will be modified in light of the validation studies. The integrated biophysical and neural model with documentation and tutorials will be made available on the web.