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A Brain-Machine Interface to Facilitate Motor Recovery from Incomplete SCI

A Brain-Machine Interface to Facilitate Motor Recovery from Incomplete SCI
促进不完全脊髓损伤运动恢复的脑机接口
批准号:
8969758
负责人:
Sridhar Sunderam
金额:
$17.94万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-07-08 至 2017-06-30

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中文摘要
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英文摘要
 DESCRIPTION (provided by applicant): Recent research suggests that neuroplasticity plays a crucial role in functional recovery after neurological injury. Sensory input in the form of sustaind peripheral nerve stimulation (PNS) can up-modulate neuroplastic change and thereby accelerate recovery of motor function. Furthermore, our preliminary data demonstrate that motor function can be substantially enhanced when PNS is delivered prior to motor training. During PNS, subjects remain awake but not actively engaged in any task. The objective of this project is to test whether PNS in subjects with incomplete spinal cord injury can accelerate recovery of motor function when PNS is delivered in closed-loop: i.e., only in response to subject's volition. This brief PNS delivery will be triggered by a brain-machine interface (BMI) that detects intent-to-move from suppression of the electroencephalogram (EEG) sensorimotor ("mu") rhythm, which can occur with actual or imagined movement effort. Evidence of a beneficial effect from synchronizing PNS with intent-to-move could help optimize timing- dependent neuroplasticity, which is critical for motor learning. This proposal has the following specific aims: 1. Develop a BMI for accurately detecting intent-to-move with minimal latency from continuous EEG measurements, and briefly triggering closed-loop PNS in response to intent-to-move; and 2. Test the hypothesis that closed-loop PNS can promote motor neuroplasticity better than open-loop (pre-programmed) PNS or sham PNS, as reflected by progressive increase in motor-evoked potential amplitude and motor performance. No study to date has investigated closed-loop PNS in individuals with neurological injuries. Refinement of PNS techniques and protocols that incorporate BMIs will contribute enormously to science and clinical care and therefore have high translational potential for neurorehabilitation.
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