BCI2000: Software Resource for Adaptive Neurotechnology Research

BCI2000：自适应神经技术研究软件资源

• 批准号: 10649719
• 负责人: Peter Brunner
• 金额: $ 56.82万
• 依托单位: WASHINGTON UNIVERSITY
• 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 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10649719
• 关键词: Acceleration; Achievement; Address; Adopted; Adoption; Area; Behavior; Biomedical Engineering; Central Nervous System; Clinical; Communication; Complement; Complex; Computer software; Consumption; Custom; Development; Diagnosis; Disease; Documentation; Educational Curriculum; Engineering; Feedback; Fostering; Funding; Impairment; Injury; Investigation; Laboratories; Life; Measures; Muscle; Nervous System; Nervous System Physiology; Neurosciences; Output; Peer Review; Persons; Process; Programming Languages; Protocols documentation; Publications; Recovery; Research; Research Personnel; Resources; Scientist; Signal Transduction; Site; Software Tools; Spinal cord injury; Stroke; System; Systems Development; Teaching Materials; Technology; Testing; Time; Training; Translations; United States National Institutes of Health; Universities; Work; collaborative environment; computer science; cost; experimental study; improved; interest; interoperability; knowledge integration; multidisciplinary; nervous system disorder; neurotechnology; novel; novel therapeutics; research and development; success; technology development; verification and validation

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）在一生中都会发生变化，它与世界的相互作用会产生活动—— 依赖可塑性，使其能够获得并维持最新的科学和技术行为。 进步支持了与中枢神经系统创造新的相互作用的系统的开发，这些相互作用可以诱导和 这些系统被称为适应性神经技术，测量来自中枢神经系统的信号，并指导有益的可塑性。 并发行为，从这些信号中得出中枢神经系统的状态，并自适应地提供实时反馈 可以恢复、替代、增强、补充或改善因损伤或疾病而受损的中枢神经系统功能。 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项多学科的努力。 来自这些不同领域的知识和想法的整合，以及通过高度复杂的实施 软件/硬件系统，需要大量的时间、精力和多学科的专业知识，这会减慢进展。 自适应神经技术的研究和开发，并限制了成功的团体数量 实现这些技术的目的是解决这两大问题。 在过去的 18 年里，我们开发并传播了一个名为 BCI2000 的软件平台， 支持与中枢神经系统的交互，并且可以实施广泛的自适应神经技术。 我们已将其提供给全球 6,000 多名用户，他们使用它来支持所述实验 尽管 BCI2000 已被证明具有价值，但其采用仍受到 1,200 多种同行评审出版物的限制。 需要大量的编程专业知识和对 BCI2000 概念的深入理解 将 BCI2000 适应并集成到特定的实验协议和硬件技术中 因此，大多数研究小组无法利用 BCI2000 提供的优势。 建议通过简化为所有主要类别的自适应配置 BCI2000 的任务来解决此缺陷 神经技术实验（目标 1），并通过提供简洁的入门课程和现场培训 科学家、工程师和退伍军人（目标 2）。 自适应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自适应神经技术创建并传播一个重要的新软件资源。 其独特的实用性应该能让更多的科学家、工程师和战士参与到这项令人兴奋的研究中。 此外，这个通用的、可互操作的、易于采用且易于调整的平台应促进 协作环境使不同的研究人员能够共同工作并相互补充。 我们期望该提案的工作将加速新型自适应神经技术的实现，这些技术将 加快科学研究以改善许多破坏性神经系统疾病的治疗。