Brain and Human Body Modeling Conference – from Fast and Accurate Computational Modeling to Clinical Practice

摘要 脑刺激疗法是治疗抑郁症和其他精神疾病的重要而有效的方法。 精神错乱。美国国家心理健康研究所(NIMH)正在支持探索如何让大脑 刺激疗法更加个性化和有效，同时减少副作用。 用于所有的大脑刺激 对于特定于患者的头部模型内的电场的计算数值模拟是 领先和最有希望的方法来开发改进的空间目标方法和定量确定 所需的刺激剂量。同样，神经生理信号分析需要大量的数值计算。 从有限的电极电压和磁强计中识别活动皮层区域的计算模型 测量。 本建议将促进快速和准确的脑和人体建模方法的发展 和技术通过大脑和人体建模的专门计算会议。与以下各项保持一致 NIMH的使命、这项提议的具体目标以及会议的主要技术重点将包括 以下内容： (I)以神经刺激为目标的脑内电场和磁场的计算模型 模式(TMS、TES、DBS)和相关的神经生理记录(EEG、iEEG、MEG)； (2)将建模技术与临床实践相结合。 这些建模技术的目的是提供更好的焦点、目标准确性和改善整体 脑刺激方法的效率。它们还将支持前景看好的组合和衍生产品 神经调节和神经生理记录，如TMS-EEG和TES-EEG。未建立 目前存在用于对这些组合的模态进行建模的计算方法。 会议将包括相关主题，这些主题共享非常相似、有时完全相同的计算方法。 和工具。我们的目标是协同共享这些计算工具，以获得最大利益并促进 跨学科的互动。

ABSTRACT Brain stimulation therapies are important and effective treatments for people with depression and other mental disorders. The National Institute of Mental Health (NIMH) is supporting studies exploring how to make brain stimulation therapies more personalized and effective while reducing side effects. For all brain stimulation modalities, computational numerical modeling of the electric fields within a patient-specific head model is the leading and most promising way to develop improved spatial targeting methods and quantitatively determine the required stimulation dose. Similarly, neurophysiological signal analyses require extensive numerical computational modeling to identify active cortical domains from limited electrode voltage and magnetometer measurements. The present proposal will facilitate development of fast and accurate brain and human body modeling methods and techniques via a dedicated computational conference on Brain and Human Body Modeling. Aligned with NIMH’s mission, the specific aims of this proposal and the major technical focus of the conference will include the following: (i) Computational modeling of electric and magnetic fields within the brain targeting neurostimulation modalities (TMS, TES, DBS) and associated neurophysiological recordings (EEG, iEEG, MEG); (ii) Integration of modeling techniques into clinical practice. These modeling techniques are aimed to provide better focality, targeting accuracy, and improve the overall efficiency of the brain stimulation methods. They will also support promising combinations and derivatives of the neuromodulation and neurophysiological recordings such as TMS-EEG and TES-EEG. No established computational methods for modeling these combined modalities currently exist. The conference will include related topics that share very similar, sometimes identical, computational methods and tools. We aim to synergistically share these computational tools for maximal benefit and to facilitate interactions across disciplines.