Simulations of Extracellular Action Potential

This simulations were done for my PhD thesis. The purpose was to show that different morphologies generate EAP spatial patterns that are stereotypical and can be considered as "fingerprints" which can be used to identify the different types of neurons when doing extracellular recordings with multi electrode arrays (In my experiments I used polytrodes: Poly3-25s from Neuronexus ). This fileset contains simulations of the extracellular signal induced by an action potential. The simulations are done on square grids located parallel to the plane containing the soma of the neuron (using LSA from [1]) 1-each file corresponds to a particular combination of morphology/electrophysiology. 2-each movie contains: - the waveform of the action potential recorded in front of the soma, as recorded by an electrode. - the amplitude of the EAP on a plane, displayed as heatmap. This shows were the signal is stronger: in front of the soma and thick dendrites/axons. - EAP(t), at each time step, displayed also as a heatmap. This allows to see how the dominant sources of current change during the action potential. 3- Description per File: - d153_0002_Z30: Simulation of Layer 2/3 pyramidal neuron from mouse cortex ([2], modified from [4]). The plane is 30 um away from the cell. - d154_0002_Z20: NPY interneuron layer not specified ([3], modified from [4]). The plane is 20 um away from the cell. -d151_0003_Z30: CA1 pyramidal neuron (from [1]). The plane is at 30 um from the cell. -d151_0006_Z38: CA1 pyramidal neuron (from [1]). Compare this to d151_0003_Z30 which is more electrotonically compact. On this case the amplitude of the EAP is of similar magnitude to the one recorded in front of the soma on branching points of the dendritic tree. [1] C. Koch, D. Henze, C. Gold, Using extracellular action potential recordings to constrain compartmental models, Journal of Computational Neu- roscience 23 (2007) 39–58. [2] A. Rocher, J. Crimins, M. Amatrudo, M. Kinson, M. Todd-Brown, J. Lewis, J. Luebke, Structural and functional changes in tau mutant mice neurons are not linked to the presence of nfts, Experimental Neu- rology 223 (2010) 385–393. [3] J. Goldberg, JTamas, D. Aronov, R. Yuste, Calcium microdomains in aspiny dendrites., Neuron 13 (2003) 807–821. [4] G. Ascoli, D. Donohue, M. Halavi, Neuromorpho.org: a central resource for neuronal morphologies, Journal of Neuroscience 27 (2007) 9247–51. [5] Localising and classifying neurons from high density MEA recordings. Journal of Neuroscience MEthods 233(2014), 115-128. http://www.sciencedirect.com/science/article/pii/S0165027014002052 ________________________________________ Other relevant references: [5] A. Destexhe, C. Bedard, Do neurons generate monopolar current sources?, Journal of Neurophysiology 108 (2012) 953–955. [6] J. Riera, T. Ogawa, T. Goto, A. Sumiyoshi, H. Nonaka, A. Evans, H. Miyakawa, R. Kawashima, Pitfalls in the dipolar model for the neocortical eeg sources, Journal of Neurophysiology 108 (2012) 956–975. [7] Z. Somogyv'ari, L. Zal ́anyi, I. Ulbert, P. E ́rdi, Model-based source localization of extracellular action potentials, Journal of Neuroscience Methods 147 (2005) 126–137.本系列仿真实验为作者博士学位论文相关研究内容，旨在验证不同神经元形态可生成具有典型特征的胞外动作电位（Extracellular Action Potential, EAP）空间分布模式，该模式可作为“指纹”，用于在使用多电极阵列（Multi Electrode Array, MEA）开展胞外记录时识别不同类型的神经元。本实验中使用了Neuronexus公司生产的Poly3-25s多电极探针。 本数据集包含由动作电位诱导产生的胞外信号仿真结果。仿真基于平行于神经元胞体所在平面的方形网格开展，采用文献[1]提出的线性源近似（Linear Source Approximation, LSA）方法，具体规则如下： 1. 每个文件对应一组特定的神经元形态与电生理特性组合； 2. 每个文件包含以下内容： - 电极记录得到的胞体正前方动作电位波形； - 平面上的EAP振幅热图，可直观展示信号较强的区域：即胞体与较粗壮的树突、轴突所在位置； - 各时间步下的EAP(t)热图，用于观察动作电位发生过程中主要电流源的动态变化过程。 3. 各文件详情如下： - d153_0002_Z30：小鼠大脑皮层2/3层锥体神经元仿真结果（文献[2]，经文献[4]修改），仿真平面距离胞体30 μm； - d154_0002_Z20：未明确分层的NPY中间神经元仿真结果（文献[3]，经文献[4]修改），仿真平面距离胞体20 μm； - d151_0003_Z30：CA1区锥体神经元仿真结果（来自文献[1]），仿真平面距离胞体30 μm； - d151_0006_Z38：CA1区锥体神经元仿真结果（来自文献[1]），可与d151_0003_Z30进行对比：后者电紧张特性更紧凑，本文件的EAP振幅与胞体正前方记录到的振幅相近，且可在树突分支点处观测到该信号。 ### 参考文献 [1] C. Koch, D. Henze, C. Gold. 利用胞外动作电位记录约束隔室模型. 计算神经科学杂志, 2007, 23: 39–58. [2] A. Rocher, J. Crimins, M. Amatrudo, M. Kinson, M. Todd-Brown, J. Lewis, J. Luebke. Tau突变小鼠神经元的结构与功能变化与神经原纤维缠结无关. 实验神经病学, 2010, 223: 385–393. [3] J. Goldberg, J. Tamas, D. Aronov, R. Yuste. 无棘树突中的钙微区. 神经元, 2003, 13: 807–821. [4] G. Ascoli, D. Donohue, M. Halavi. Neuromorpho.org：神经元形态学研究核心资源库. 神经科学杂志, 2007, 27: 9247–9251. [5] 基于高密度多电极阵列记录的神经元定位与分类. 神经科学方法杂志, 2014, 233: 115–128. https://www.sciencedirect.com/science/article/pii/S0165027014002052 --- ### 其他相关参考文献 [6] A. Destexhe, C. Bedard. 神经元会产生单极电流源吗？. 神经生理学杂志, 2012, 108: 953–955. [7] J. Riera, T. Ogawa, T. Goto, A. Sumiyoshi, H. Nonaka, A. Evans, H. Miyakawa, R. Kawashima. 新皮层脑电信号偶极子模型的应用误区. 神经生理学杂志, 2012, 108: 956–975. [8] Z. Somogyvári, L. Zalányi, I. Ulbert, P. Érdi. 基于模型的胞外动作电位源定位方法. 神经科学方法杂志, 2005, 147: 126–137.