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

 描述(申请人提供)：许多脑损伤幸存者尽管接受了传统治疗，但仍有持续性的手功能损害。该研究项目的长期目标是增强和引导大脑固有的可塑性，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与改善的运动相对应的大脑皮层面积的扩大有关，但目前尚不清楚扩大的地图是否会导致功能的改善。这个问题对于我们理解脑损伤后的康复是至关重要的。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损大脑的可塑性，也可以测试MAP扩大对功能的影响。然而，对于体重指数训练的哪些方面对于增强皮质可塑性至关重要，我们仍然知之甚少，包括1)用于控制体重指数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)用于控制体重指数的运动意图的空间精度(例如，单个手指与整个手)。本提案的目标是确定BMI对改变机动地图最重要的方面，以及由BMI驱动的机动地图扩展改善功能的程度。通过扩展地图，可以将因脑损伤而瘫痪的肌肉的控制转移到仍保留完整下行连接的皮质区域，从而恢复功能。 这一建议的中心假设是，最佳驱动可塑性和运动地图变化的关键依赖于同时激活运动意图和触觉反馈。我们认为到目前为止，高频信号将比BMI中使用的低频信号具有更高的时空精度。我们将在因创伤性脑损伤接受半开颅手术的受试者中测试这一假设，具体目的如下：1)确定高频BMI训练在多大程度上推动运动地图扩大和改善手功能，以及2)确定运动意图和触觉反馈之间的同步在驱动地图大小和手功能变化中的作用。这项提议创新地使用头皮信号进行半颅骨切除术，将使我们能够非侵入性地记录高分辨率、高带宽的信号，并检验我们的假设。实现我们的目标将是重要的，因为它将通过识别对增强可塑性至关重要的光谱、时间和空间特征来改进BMI训练范例的设计。我们预计这项提案将定义BMI在机动地图中创造变化的能力。我们还希望它有助于确定运动地图变化和功能恢复之间的关系。最后，它将在未来的研究中展示在脑损伤后使用基于硬膜外微创的BMI来改善功能的潜力。

 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.