Denervation due to amputation is known to induce cortical reorganization in the sensorimotor cortex. Although there is evidence that reorganization does not lead to a complete loss of the representation of the phantom limb, it is unclear to what extent detailed, finger-specific activation patterns are preserved in motor cortex, an issue that is also relevant for development of brain–computer interface solutions for paralysed people. We applied machine learning to obtain a quantitative measure for the functional organization within the motor and adjacent cortices in amputees, using high resolution functional MRI and attempted hand gestures. Subjects with above-elbow arm amputation (n = 8) and non-amputated controls (n = 9) made several gestures with either their right or left hand. Amputees attempted to make gestures with their amputated hand. Images were acquired using 7 T functional MRI. The sensorimotor cortex was divided into four regions, and activity patterns were classified in individual subjects using a support vector machine. Classification scores were significantly above chance for all subjects and all hands, and were highly similar between amputees and controls in most regions. Decodability of phantom movements from primary motor cortex reached the levels of right hand movements in controls. Attempted movements were successfully decoded from primary sensory cortex in amputees, albeit lower than in controls but well above chance level despite absence of somatosensory feedback. There was no significant correlation between decodability and years since amputation, or age. The ability to decode attempted gestures demonstrates that the detailed hand representation is preserved in motor cortex and adjacent regions after denervation. This encourages targeting sensorimotor activity patterns for development of brain–computer interfaces.

中文翻译：

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保留截肢者感觉运动区域的手部运动表现

已知由于截肢导致的去神经支配导致感觉运动皮层中的皮层重组。尽管有证据表明重组不会导致幻肢的表现完全丧失，但尚不清楚运动皮层中保留了多少详细的手指特异性激活模式，这个问题也与大脑的发育有关– 瘫痪者的计算机接口解决方案。我们应用机器学习来获得截肢者运动和邻近皮质内功能组织的定量测量，使用高分辨率功能 MRI 和尝试的手势。肘上臂截肢（n = 8）和非截肢对照（n= 9) 用他们的右手或左手做了几个手势。截肢者试图用截肢的手做手势。使用 7 T 功能 MRI 获取图像。感觉运动皮层被分为四个区域，并使用支持向量机对个体受试者的活动模式进行分类。所有受试者和所有手的分类得分都显着高于机会，并且在大多数地区的截肢者和对照组之间高度相似。来自初级运动皮层的幻象运动的可解码性达到了控件中右手运动的水平。从截肢者的初级感觉皮层成功解码了尝试的运动，尽管低于对照组，但远高于机会水平，尽管没有体感反馈。可解码性与截肢后的年数或年龄之间没有显着相关性。解码尝试手势的能力表明，去神经支配后，详细的手部表征保留在运动皮层和邻近区域。这鼓励针对感觉运动活动模式来开发脑机接口。