A tool-box to control and enhance tDCS spatial precision

为了彻底改变我们对大脑的理解，大脑计划呼吁“改进现有的非侵入性神经调节”技术。目前，经颅直流电刺激(TDC)受到了极大的关注，它具有可展开、耐受性好、具有靶向神经调节作用等优点。TDCs的计算模型预测了给定电极配置(蒙太奇)下的单个大脑电流流动，并预测优化的靶向蒙太奇可以实现更多的局灶性皮质刺激。通过三项创新，这项建议消除了现有的限制使用计算模型的障碍，这些计算模型将允许研究人员为所需的皮质目标单独定制电极蒙太奇，从而优化临床结果并解决特定的研究假设。首先，十年来在自动图像分割和高通量电流建模方面的技术创新将得到增强，并在支持云的开源中进行编码。其次，最先进的tdcs电流分布的磁共振成像将验证和改进模型方法。第三，将部署独立的、基于网络的建模客户端软件，并在服务器上实施计算要求较高的步骤。只有算法优化的结果才能将建模过程分为两个步骤：在服务器上进行基于云的计算密集型处理，然后由研究人员在传统PC上使用客户端软件进行几秒钟的模拟。这些创新导致了一个以前需要大量专业知识和劳动力、超级计算机和多次迭代的过程，而不是简化为一个步骤，在传统PC上只需几秒钟。此外，我们还将提供用于活体标测tdcs电流的MRI协议。作为一项探索性的目标，核磁共振成像将测试tdcs对深层结构靶向的建模预测。直接响应RFA，这项提议的结果是一个工具箱，用于优化tDCS空间精度，以提高旨在了解大脑和治疗疾病的tDCS研究的严谨性。我们的方法在集成可伸缩性、严格性和透明度方面是独一无二的 开源(服务器端)，使用高度可评估的图形用户界面控制软件(客户端)，同时非常健壮(如不理想的扫描质量)和灵活性(如传统焊盘或高清晰度电极)。

Aimed at revolutionizing our understanding of the brain, the BRAIN initiative calls for “improvement of existing non-invasive neuromodulation” techniques. There is presently great interest in transcranial Direct Current Stimulation (tDCS), which is deployable, well tolerated, and carries the promise of targeted neuromodulation. Computational models of tDCS predict individual brain current flow for a given electrode configuration (“montage”), and predict that optimized targeting montages can achieve more focal cortical stimulation. Through three innovations, this proposal removes existing barriers limiting access to computational models that will allow researchers to individually tailor electrode montages for desired cortical targets so as to optimize clinical outcomes and address specific research hypotheses. First, a decade of technical innovation in automated image segmentation and high- throughput current flow modeling will be enhanced and encoded in cloud-enabled open-source. Second, state-of-the-art MRI mapping of tDCS current distribution will validate and refine model methods. Third, stand-alone and web-based modeling client software will be deployed with computationally demanding steps implemented on servers. Only as a result of algorithmic optimization can the modeling process be divided into two steps: a cloud-based computationally intensive processing on servers, and then simulations taking just seconds by researchers using client software on conventional PC. These innovations result in a process that previously required extensive expertise and labor, super-computers and numerous iterations instead being reduced to a single step, requiring seconds on a conventional PC. In addition, we will supply the MRI protocol for in vivo mapping of tDCS current flow. In an exploratory aim, MRI mapping will test modeling predictions on deep structure targeting with tDCS. Directly responsive to the RFA, the outcome of this proposal is a toolbox for the optimization of tDCS spatial precision to enhance the rigor of tDCS research aimed at understanding the brain and for treating disease. Our approach is unique in integrating the scalability, rigor, and transparency of opens-source (server side) with highly assessable GUI control software (client side), while being exceptionally robust (e.g. non-ideal scan quality) and flexible (e.g. conventional pad or High-Definition electrodes).