Multi-scale modeling toolbox for single neuron and subcellular activity under Transcranial Magnetic Stimulation.
Multi-scale modeling toolbox for single neuron and subcellular activity under Transcranial Magnetic Stimulation.
复制标题
DOI：
10.1016/j.brs.2021.09.004
复制
发表时间：
2021-11
影响因子：
7.7
通讯作者：
Opitz A
中科院分区：
文献类型：
--
作者：
Shirinpour S;Hananeia N;Rosado J;Tran H;Galanis C;Vlachos A;Jedlicka P;Queisser G;Opitz A
经颅磁刺激（TMS）是一种广泛使用的非侵入性脑刺激方法。然而，其作用机制和对TMS的神经反应仍然知之甚少。多尺度建模可以补充实验研究，以研究TMS的亚细胞神经效应。在宏观层面上，存在复杂的数值模型来估计感应电场。然而，多尺度的计算建模方法来预测TMS细胞和亚细胞的反应，理解TMS可塑性诱导协议的关键，是迄今为止还没有。我们开发了一个开源的多尺度工具箱Neuron Modeling for TMS（NeMo-TMS）来解决这个问题。NeMo-TMS通过形态重建生成精确的神经元模型，将其耦合到TMS诱导的外部电场，并模拟单脉冲和重复TMS的细胞和亚细胞反应。我们提供了一些例子来展示工具箱的一些功能。NeMo-TMS工具箱为研究人员提供了以前无法获得的细节和精确度，以逼真地模拟TMS的物理和生理效应。
Transcranial Magnetic Stimulation (TMS) is a widely used non-invasive brain stimulation method. However, its mechanism of action and the neural response to TMS are still poorly understood. Multi-scale modeling can complement experimental research to study the subcellular neural effects of TMS. At the macroscopic level, sophisticated numerical models exist to estimate the induced electric fields. However, multi-scale computational modeling approaches to predict TMS cellular and subcellular responses, crucial to understanding TMS plasticity inducing protocols, are not available so far. We develop an open-source multi-scale toolbox Neuron Modeling for TMS (NeMo-TMS) to address this problem. NeMo-TMS generates accurate neuron models from morphological reconstructions, couples them to the external electric fields induced by TMS, and simulates the cellular and subcellular responses of single-pulse and repetitive TMS. We provide examples showing some of the capabilities of the toolbox. NeMo-TMS toolbox allows researchers a previously not available level of detail and precision in realistically modeling the physical and physiological effects of TMS.
登录
查看更多内容
影响因子：
3.2
作者：
BASSER, PJ;ROTH, BJ
通讯作者：
ROTH, BJ
影响因子：
2
作者：
Fung, P. K.;Robinson, P. A.
通讯作者：
Robinson, P. A.
影响因子：
4.6
作者：
Breit M;Kessler M;Stepniewski M;Vlachos A;Queisser G
通讯作者：
Queisser G
影响因子：
7.7
作者：
Aberra, Aman S.;Wang, Boshuo;Peterchev, Angel V.
通讯作者：
Peterchev, Angel V.
影响因子：
7.7
作者：
Beining M;Mongiat LA;Schwarzacher SW;Cuntz H;Jedlicka P
通讯作者：
Jedlicka P