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多模态反馈的融合增强了脑机接口控制。

Incorporating feedback from multiple sensory modalities enhances brain-machine interface control.

机构信息

Department of Organismal Biology and Anatomy, University of Chicago, Chicago, Illinois 60637, USA.

出版信息

J Neurosci. 2010 Dec 15;30(50):16777-87. doi: 10.1523/JNEUROSCI.3967-10.2010.

Abstract

The brain typically uses a rich supply of feedback from multiple sensory modalities to control movement in healthy individuals. In many individuals, these afferent pathways, as well as their efferent counterparts, are compromised by disease or injury resulting in significant impairments and reduced quality of life. Brain-machine interfaces (BMIs) offer the promise of recovered functionality to these individuals by allowing them to control a device using their thoughts. Most current BMI implementations use visual feedback for closed-loop control; however, it has been suggested that the inclusion of additional feedback modalities may lead to improvements in control. We demonstrate for the first time that kinesthetic feedback can be used together with vision to significantly improve control of a cursor driven by neural activity of the primary motor cortex (MI). Using an exoskeletal robot, the monkey's arm was moved to passively follow a cortically controlled visual cursor, thereby providing the monkey with kinesthetic information about the motion of the cursor. When visual and proprioceptive feedback were congruent, both the time to successfully reach a target decreased and the cursor paths became straighter, compared with incongruent feedback conditions. This enhanced performance was accompanied by a significant increase in the amount of movement-related information contained in the spiking activity of neurons in MI. These findings suggest that BMI control can be significantly improved in paralyzed patients with residual kinesthetic sense and provide the groundwork for augmenting cortically controlled BMIs with multiple forms of natural or surrogate sensory feedback.

摘要

大脑通常利用来自多种感觉模式的丰富反馈来控制健康个体的运动。在许多个体中,这些传入通路以及它们的传出对应物,会因疾病或损伤而受损,导致显著的障碍和生活质量下降。脑机接口 (BMI) 通过允许个体使用他们的思维来控制设备,为这些个体提供了恢复功能的希望。大多数当前的 BMI 实现都使用视觉反馈进行闭环控制;然而,有人认为包含额外的反馈模式可能会导致控制的改善。我们首次证明,运动觉反馈可以与视觉一起使用,显著改善由初级运动皮层 (MI) 的神经活动驱动的光标控制。使用外骨骼机器人,猴子的手臂被移动以被动地跟随皮质控制的视觉光标,从而为猴子提供关于光标运动的运动觉信息。当视觉和本体感觉反馈一致时,与不一致的反馈条件相比,成功到达目标的时间减少,光标路径变得更直。这种增强的性能伴随着 MI 中神经元的尖峰活动中包含的与运动相关的信息量的显著增加。这些发现表明,具有残留运动觉的瘫痪患者的 BMI 控制可以得到显著改善,并为使用多种自然或替代感觉反馈来增强皮质控制的 BMI 提供了基础。

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