BCI2000: Software Resource for Adaptive Neurotechnology Research

BCI2000：自适应神经技术研究软件资源

• 批准号: 10071302
• 负责人: Peter Brunner
• 金额: $ 24.37万
• 依托单位: ALBANY MEDICAL COLLEGE
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-01 至 2020-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10071302
• 关键词: BCI2000; Software; Resource; Adaptive; Neurotechnology

The central nervous system (CNS) changes throughout life, and its interactions with the world produce activity- dependent plasticity that enables it to acquire and maintain useful behaviors. Recent scientific and technical advances support the development of systems that create novel interactions with the CNS that can induce and guide beneficial plasticity. These systems, called adaptive neurotechnologies, measure signals from the CNS and concurrent behavior, derive from those signals the state of the CNS, and adaptively provide real-time feedback that can restore, replace, enhance, supplement or improve CNS functions impaired by injury or disease. Thus, they can provide important new therapies for neurological disorders. The development and use of adaptive neurotechnologies is an inherently multidisciplinary endeavor. The integration of knowledge and ideas from these diverse areas, and their implementation by highly sophisticated software/hardware systems, requires substantial time, effort, and multidisciplinary expertise. This slows progress in research and development of adaptive neurotechnologies and limits the number of groups that are successful in realizing these technologies. The present proposal seeks to address these two major problems. Over the past 18 years, we have developed and disseminated a software platform, called BCI2000, that supports interactions with the CNS and can implement a wide range of adaptive neurotechnologies. To date, we have provided it to more than 6,000 users worldwide who have used it to support experiments described in over 1,200 peer-reviewed publications. Despite this demonstrated value, BCI2000 adoption is limited by the requirements of substantial programming expertise and in-depth understanding of BCI2000 concepts needed to adapt and integrate BCI2000 into the specific experimental protocols and hardware technologies of a particular laboratory. Thus, most research groups cannot take advantage of the advantages provided by BCI2000. We propose to address this deficiency by simplifying the task of configuring BCI2000 for all major classes of adaptive neurotechnology experiments (Aim 1), and by providing a succinct introductory course and on-site training for scientists, engineers, and clinicians (Aim 2). We hypothesize that this work will greatly accelerate realization of adaptive neurotechnologies that will reduce the devastating impact of neurological disorders. Achieving these two aims will create and disseminate a major new software resource for adaptive neurotechnol- ogy research. Its unique utility should enable more scientists, engineers, and clinicians to engage in this exciting work. Furthermore, this common, interoperable, readily adopted, and easily adapted platform should foster a collaborative environment that enables diverse investigators to work together and complement each other. In sum, we expect that the work of this proposal will accelerate realization of novel adaptive neurotechnologies that will hasten scientific investigations to improve treatment for many devastating neurological disorders.

中枢神经系统（CNS）在一生中不断变化，它与世界的相互作用产生活动- 依赖可塑性，使其能够获得和保持有用的行为。最近的科学和技术 这些进展支持开发与CNS产生新的相互作用的系统， 引导贝内的可塑性。这些系统被称为自适应神经技术，测量来自CNS的信号， 并发行为，从这些信号中导出CNS的状态，并自适应地提供实时反馈 其可恢复、替代、增强、补充或改善因损伤或疾病而受损CNS功能。因此，在本发明中， 它们可以为神经系统疾病提供重要的新疗法。 自适应神经技术的开发和使用本质上是一个多学科的奋进。的 整合来自这些不同领域的知识和想法，并通过高度复杂的 软件/硬件系统，需要大量的时间，精力和多学科的专业知识。这会减缓进展 在自适应神经技术的研究和开发中，并限制了成功的小组数量 实现这些技术。本建议旨在解决这两个主要问题。 在过去的18年里，我们开发并推广了一个名为BCI 2000的软件平台， 支持与CNS的交互，并可以实现广泛的自适应神经技术。到目前为止， 我们已经向全世界6,000多名用户提供了它，他们使用它来支持所描述的实验。 发表在1,200多篇同行评议的出版物上尽管这一价值得到了证实，但BCI 2000的采用受到以下因素的限制： 需要大量的编程专业知识和对BCI 2000概念的深入理解， 调整和整合BCI 2000到特定的实验协议和硬件技术， 实验室因此，大多数研究小组不能利用BCI 2000提供的优势。我们 建议通过简化为所有主要自适应类别配置BCI 2000的任务来解决这一缺陷 神经技术实验（目标1），并通过提供一个简洁的入门课程和现场培训， 科学家、工程师和临床医生（目标2）。我们假设这项工作将大大加速实现 适应性神经技术将减少神经系统疾病的破坏性影响。 实现这两个目标将为适应性神经技术创造和传播一个重要的新软件资源， ogy研究。它的独特效用应该使更多的科学家，工程师和临床医生参与这一令人兴奋的研究。 工作此外，这一通用、可互操作、易于采用和易于调整的平台应促进 协作环境，使不同的调查人员能够一起工作，相互补充。总的来说， 我们期望这项提案的工作将加速实现新的适应性神经技术， 加速科学研究，以改善许多破坏性神经系统疾病的治疗。