NeuroSimNIBS: Integrated electric field and neuronal response modeling for transcranial electric and magnetic stimulation

非侵入性脑刺激 (NIBS) 设备越来越多地用于治疗心理健康 迹象。经颅磁刺激 (TMS) 已获得 FDA 批准用于治疗抑郁症、强迫症 强迫症和吸烟成瘾。两种形式的经颅电刺激 (TES) 获得批准 用于精神科治疗，以及：针对抑郁症和紧张症的电休克治疗 (ECT) 以及颅脑治疗 电刺激（CES）治疗焦虑和失眠。此外，其他 TES 的临床试验正在进行中 范式以及 TMS 的新适应症。然而，这些干预措施也有其局限性，包括 对 TMS 的不同反应、阈下 TES 的低效以及 ECT 的认知副作用。一个有贡献的 因素是缺乏对刺激所涉及的神经元件和群体的了解，无论是在 一般情况和个别患者内部。这妨碍了针对特定目标合理选择刺激剂量 神经元件或解释解剖学上的个体差异。例如，TMS 强度是个性化的 基于运动皮层刺激，与前额叶皮层的典型目标相关性有限。而且， ECT 和其他形式的 TES 中的电流幅度根本不是个体化的，因此存在解剖学差异 导致大脑内的不同刺激强度。这与侵入性方法形成对比，例如深度 脑刺激，其中神经目标参与的建模是手术计划的既定部分 剂量选择。该项目的目标是开发计算工具来模拟、量化和可视化 TMS 和 TES 对个体患者大脑神经元的直接影响。建模效果将包括 TMS 或 TES 电场对神经元进行阈下极化和阈上激活 （电场），它构成了随后脑回路调制的关键机制链接。目标 1 是 实现皮质神经元以及皮质和皮质下有髓轴突的高保真模型并放置 它们在单独的头部模型中。神经模型将优化形态和膜动力学 代表层和大脑区域特定的神经元，并将用现有的实验数据进行验证。自从 计算大量神经元响应的计算需求令人望而却步，目标 2 是 开发和验证计算有效的神经反应估计器以进行模拟 计算资源有限的普通用户可以使用。最后，目标 3 是进行这些模拟 通过整合神经反应，研究人员和临床医生可以广泛使用估计工具 量化到用于电场模拟的 SimNIBS 软件包中，以创建一个集成工具，称为 NeuroSimNIBS。这个用户友好的软件将使研究人员和临床医生能够开发出更好的 了解 TMS 和 TES 对个体大脑的影响。最终，NeuroSimNIBS 可用于 个性化刺激参数并合理规划实验和治疗，以获得更有效和更有效的效果 一致的神经调节。

Devices for non-invasive brain stimulation (NIBS) are increasingly used for treatment of mental health indications. Transcranial magnetic stimulation (TMS) is FDA-cleared for the treatment of depression, obsessive compulsive disorder, and smoking addiction. Two forms of transcranial electric stimulation (TES) are approved for psychiatric treatment, as well: electroconvulsive therapy (ECT) for depression and catatonia and cranial electrotherapy stimulation (CES) for anxiety and insomnia. Further, there are ongoing clinical trials of other TES paradigms, as well as new indications for TMS. However, these interventions have limitations including the variable response to TMS, low efficacy of subthreshold TES, and cognitive side-effects of ECT. A contributing factor is the lack of understanding of the neural elements and populations engaged by the stimulation, both in general and within an individual patient. This precludes rational selection of the stimulation dose to target specific neural elements or to account for individual differences in anatomy. For example, TMS intensity is individualized based on motor cortex stimulation, which has limited relevance to typical targets in prefrontal cortex. Moreover, the current amplitude in ECT and other forms of TES is not individualized at all, and anatomical differences thus result in variable stimulation strengths within the brain. This is in contrast to invasive approaches, such as deep brain stimulation, where modeling of neural target engagement is an established part of surgical planning and dose selection. The goal of this project is to develop computational tools to simulate, quantify, and visualize the direct effects of TMS and TES on neurons in the brains of individual patients. The modeled effects will include both subthreshold polarization and suprathreshold activation of neural elements by the TMS or TES electric field (E-field), which comprise the critical mechanistic link to subsequent brain circuit modulation. Aim 1 is to implement high-fidelity models of cortical neurons as well as cortical and subcortical myelinated axons and place them in individual head models. The neural models will have morphologies and membrane dynamics optimized to represent layer- and brain-region-specific neurons, and will be validated with existing experimental data. Since the computational demands to calculate the response of a large population of neurons are prohibitive, Aim 2 is to develop and validate computationally efficient estimators of the neural responses to make the simulations accessible for the average user with limited computational resources. Finally, Aim 3 is to make these simulation and estimation tools widely available to researchers and clinicians by integrating the neural response quantifications into the SimNIBS software package for E-field simulation to create an integrated tool termed NeuroSimNIBS. This user-friendly software will enable researchers and clinicians to develop a better understanding of the effect of TMS and TES on individual brains. Ultimately, NeuroSimNIBS could be used to individualize the stimulation parameters and rationally plan experiments and therapies for more effective and consistent neuromodulation.