Designing brain machine interfaces to drive plasticity and enhance recovery after brain injury

 描述（由申请人提供）：尽管接受了常规治疗，但许多脑损伤幸存者的手功能仍持续受损。 该研究项目的长期目标是增强和指导大脑的固有可塑性，以改善创伤性或缺血性脑损伤幸存者的运动功能。 脑损伤后的功能改善与大脑皮层的扩大区域相对应的改善运动（“运动地图”），但目前还不清楚是否扩大地图导致改善功能。 这个问题对于我们理解脑损伤的恢复至关重要。 脑机接口（BMI）使受试者能够使用他们的大脑信号直接控制外部设备，可以诱导大脑活动的可塑性变化。 因此，BMI可以提供一个强大的工具来驱动受伤大脑的可塑性，并测试地图放大对功能的影响。 然而，关于BMI训练的哪些方面对增强皮层可塑性至关重要，我们的知识中仍然存在重要的差距，包括1）用于控制BMI的神经信号的类型和特征，2）体感（触觉）反馈必须与运动意图同步的时间精度，以及3）运动意图的空间精度（例如，单个手指vs.整只手）用于控制BMI。 本提案的目的是确定BMI对改变运动地图最重要的方面，以及BMI驱动的运动地图扩展改善功能的程度。 通过扩展地图，对因脑损伤而瘫痪的肌肉的控制可以转移到仍然保留完整下行连接的皮层区域，从而恢复功能。 这个建议的中心假设是，最佳驾驶可塑性和运动地图的变化是严重依赖于同时激活运动意图和触觉反馈。 我们建议，高频信号将使更大的时空精度比使用的低频BMI康复。 我们将通过以下特定目的在因创伤性脑损伤而接受过半脑切除术的受试者中测试这一假设：1）确定基于高频的BMI训练驱动运动地图扩大和改善手功能的程度，以及2）确定运动意图和触觉反馈之间的同步性在驱动地图大小和手功能变化中的作用。 这项建议的创新使用头皮信号的半颅骨切除术将使我们能够记录高分辨率，高带宽的信号非侵入性和测试我们的假设。 实现我们的目标将是重要的，因为它将通过识别对可塑性增强至关重要的光谱、时间和空间特征来改进BMI训练范例的设计。 我们希望这项提案能够定义BMI在运动地图中产生变化的能力。 我们还希望它有助于定义运动地图变化和功能恢复之间的关系。 最后，它将证明在未来的研究中使用微创，基于脑损伤的BMI改善功能的潜力。

 DESCRIPTION (provided by applicant): Many survivors of brain injury have persistent impairment of hand function despite receiving conventional therapy. The long-term goal of this research project is to augment and direct the brain's inherent plasticity to improve motor function for survivors of traumatic or ischemic brain injury. Functional improvement after brain injury correlates with an enlarged area of cerebral cortex corresponding to the improved movement ("motor map"), but it is unclear if the enlarged map causes improved function. This question is of fundamental importance to our understanding of recovery from brain injuries. Brain machine interfaces (BMIs), which enable subjects to use their brain signals to directly control external devices, can induce plastic changes in the brain's activity. Thus, a BMI could provide a powerful tool to drive plasticity in injured brains and also test the effects of map enlargement on function. However, important gaps in our knowledge remain about what aspects of BMI training are critical to enhancing cortical plasticity, including 1) the types and features of neural signals used to control the BMI, 2) the temporal precision with which somatosensory (haptic) feedback must be synchronized with motor intent, and 3) the spatial precision of movement intent (e.g., individual finger vs. whole hand) used to control the BMI. The objectives of this proposal are to determine the aspects of BMIs most important to changing motor maps, and the extent to which motor map expansion driven by BMIs improves function. By expanding the map, the control of muscles that have by paralyzed by brain injury can be moved to areas of cortex that still retain intact descending connections, thus restoring function. The central hypothesis of this proposal is that optimally driving plasticity and motor map changes is critically dependent on simultaneously activating motor intent and haptic feedback. We propose that high-frequency signals will enable much greater spatiotemporal precision than the low frequencies used in BMIs for rehabilitation to date. We will test this hypothesis in subjects who have had hemicraniectomies for traumatic brain injury via these specific aims: 1) Determine the extent to which high-frequency based BMI training drives motor map enlargement and improves hand function, and 2) Determine the role of synchrony between motor intent and haptic feedback in driving changes in map size and hand function. This proposal's innovative use of scalp signals over the hemicraniectomy will enable us to record high-resolution, high-bandwidth signals non-invasively and test our hypothesis. Achieving our objectives will be significant because it will improve the design of BMI training paradigms by identifying spectral, temporal, and spatial features that are critical to plasticity enhancement. We expect this proposal to define the ability of BMIs to create changes in motor maps. We also expect it to help define the relationship between motor map changes and functional recovery. Finally, it will demonstrate the potential for functional improvement in future studies using minimally-invasive, epidural-based BMIs after brain injury.