Integrated Biophysical and Neural Model of Electrical Stimulation Effects

电刺激效应的综合生物物理和神经模型

• 批准号: 10670301
• 负责人: MAKSIM V BAZHENOV
• 金额: $ 88.9万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10670301
• 关键词: Acute; Affect; Anatomy; Animals; Anodes; Area; Axon; Behavior; Brain; Calcium; Calcium Signaling; Cell Density; Cell model; Cells; Characteristics; Chronic; Clinical; Cortical Column; Data; Dendrites; Documentation; Electric Stimulation; Electrodes; Electrophysiology (science); Elements; Human; Image; Internet; Interneurons; Label; Light; Location; Measurement; Measures; Mental disorders; Methods; Microscopy; Modeling; Mus; Myelin Basic Proteins; Neurons; Neurosciences; Pattern; Phase; Physiologic pulse; Physiology; Pilot Projects; Population; Preparation; Probability; Property; Protocols documentation; Rattus; Resolution; Sensory; Shapes; Sleep; Sleep Stages; Somatosensory Cortex; Space Perception; Spatial Distribution; Stimulus; Surface; Synapses; Technology; Testing; Thalamic structure; Time; association cortex; awake; biophysical model; calcium indicator; cell type; experimental study; millisecond; mouse model; nervous system disorder; neural; neural model; non rapid eye movement; novel; predictive modeling; reconstruction; response; simulation; spatiotemporal; temporal measurement; two-photon; validation studies; voltage; voltage sensitive dye

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.

项目摘要 电刺激广泛用于激活和/或破坏神经元活动。尽管它很关键 在实验和临床神经科学中具有重要意义，目前还没有有效的方法来预测 大脑的哪些神经元件将被给定的刺激方案激活。根据我们的试点 研究中，我们建议开发一种新的计算方法来预测特定神经元 它将根据神经元的形状、位置、类型和给定的刺激方案来激活 连接性。我们将使用生物物理模型来计算激活电流的空间分布， 然后将该分布与轴突和树突的空间分布和方向进行卷积 主要的锥体细胞和中间神经元细胞类型，以确定它们的放电概率。我们随后将 通过皮层电路传播这种活动。我们将模拟不同的物种（大鼠、小鼠、人类） 和皮质区域（主要感觉和联想）。我们将检查睡眠阶段和 诱发丘脑皮质网络上的背景活动，包括特征性睡眠节律 活动。该模型的预测将通过广泛的经验测量来验证，主要是 使用先进的显微镜方法对小鼠进行钙成像，使整个相关的皮质 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。 这将辅以电压敏感染料成像和层流电生理记录，以 提供时间分辨率。层流记录将在人类身上重复，无论是急性还是 术中和半慢性环境。这些模型将根据验证研究进行修改。这 集成的生物物理和神经模型以及文档和教程将在 网络。

项目成果

Olfactory receptor neurons generate multiple response motifs, increasing coding space dimensionality.

• DOI: 10.7554/elife.79152
• 发表时间: 2023-01-31
• 期刊: eLife
• 影响因子: 7.7
• 作者: Kim B;Haney S;Milan AP;Joshi S;Aldworth Z;Rulkov N;Kim AT;Bazhenov M;Stopfer MA
• 通讯作者: Stopfer MA

Selective recruitment of cortical neurons by electrical stimulation.

通过电刺激选择性招募皮质神经元。

• DOI: 10.1371/journal.pcbi.1007277
• 发表时间: 2019
• 期刊: PLoS computational biology
• 影响因子: 4.3
• 作者: Komarov,Maxim;Malerba,Paola;Golden,Ryan;Nunez,Paul;Halgren,Eric;Bazhenov,Maxim
• 通讯作者: Bazhenov,Maxim