A tool-box to control and enhance tDCS spatial precision

控制和增强 tDCS 空间精度的工具箱

• 批准号: 9357699
• 负责人: MAROM BIKSON
• 金额: $ 42.99万
• 依托单位: CITY COLLEGE OF NEW YORK
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-26 至 2020-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9357699
• 关键词: Accounting; Address; Algorithms; Anatomy; BRAIN initiative; Behavior; Behavioral; Brain; Brain region; Brain scan; Client; Clinical; Clinical Investigator; Clinical Trials; Cognition; Cognitive; Computer Simulation; Computer software; Computers; Custom; Data; Databases; Diffuse; Disease; Dose; Electrical Stimulation of the Brain; Electrodes; Elements; Human; Individual; Investments; Location; Magnetic Resonance Imaging; Maintenance; Measures; Methods; Modeling; Morphologic artifacts; Noise; Online Systems; Outcome; Paper; Patients; Physiologic pulse; Population; Positioning Attribute; Process; Property; Protocols documentation; Rehabilitation therapy; Research; Research Personnel; Resolution; Role; Scalp structure; Scanning; Side; Software Tools; Specificity; Structure; System; Technical Expertise; Techniques; Technology; Testing; Therapeutic Effect; Tissues; United States National Institutes of Health; Update; Validation; Variant; base; brain shape; clinical efficacy; cloud based; cloud platform; computer program; computing resources; design; encryption; experimental study; flexibility; imaging Segmentation; improved; in vivo; innovation; interest; magnetic field; neurophysiology; neuropsychiatry; neuroregulation; open source; response; simulation; tool

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).

旨在彻底改变我们对大脑的理解，大脑倡议要求“改善现有的非侵入性神经调节”技术。目前，人们对经颅直流电流刺激（TDC）非常感兴趣，该刺激是可部署，耐受性良好的，并带来了靶向神经调节的承诺。 TDC的计算模型预测给定电极构型（“蒙太奇”）的单个大脑电流流，并预测优化的靶向蒙太奇可以实现更具局灶性皮质刺激。通过三项创新，该提案消除了现有的障碍，限制了对计算模型的访问，这些障碍将使研究人员可以单独定制所需皮质靶标的电极单调，从而优化临床结果并解决特定的研究假设。首先，在自动化图像分段和高通量电流流程建模中的十年技术创新将在启用云的开源中增强和编码。其次，TDCS电流分布的最新MRI映射将验证和完善模型方法。第三，独立和基于Web的建模客户端软件将通过在服务器上实现的计算要求进行部署。仅由于算法优化的结果，建模过程才能分为两个步骤：在服务器上基于云的计算密集处理处理，然后在常规PC上使用客户端软件的研究人员仅使用秒数进行模拟。这些创新导致了一个以前需要广泛的专业知识和劳动力，超级计算机和大量迭代的过程，而是将其简化为一步，需要在传统的PC上进行几秒钟。此外，我们还将提供MRI协议，以用于TDCS电流流的体内映射。在探索性目的中，MRI映射将测试对用TDC进行深层结构靶向的预测。直接响应RFA，该提案的结果是优化TDCS空间精度的工具箱，以增强旨在了解大脑和治疗疾病的TDCS研究的严格性。我们的方法在整合的可伸缩性，严格性和透明度方面是独一无二的 使用高度可评估的GUI控制软件（客户端）打开源（服务器端），同时非常健壮（例如非理想扫描质量）和灵活（例如，常规垫或高清电极）。