Multisensory Integration in Action: a Multineuronal and Feedback-Control Approach

行动中的多感觉整合：多神经元和反馈控制方法

• 批准号: 9219134
• 负责人: Aaron Paul Batista
• 金额: $ 33.33万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-02-01 至 2022-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9219134
• 关键词: Activities of Daily Living; Address; Adopted; Affect; Animals; Architecture; Area; Basic Science; Behavior; Behavior Control; Behavioral; Brain; Cerebral cortex; Clinical; Collaborations; Computer Simulation; Data; Development; Devices; Environment; Equilibrium; Esthesia; Exhibits; Feedback; Gait; Goals; Hand; Hand functions; Human; Impairment; Knowledge; Macaca mulatta; Modality; Modeling; Monitor; Monkeys; Motor; Motor Cortex; Movement; Nervous System control; Neuraxis; Neurons; Performance; Prosthesis Design; Quality Control; Research; Research Personnel; Sensory; Signal Transduction; Somatosensory Cortex; Study models; Tactile; Task Performances; Technology; Testing; Training; V1 neuron; Visual; Walking; area striata; arm movement; base; behavioral study; brain computer interface; control theory; flexibility; grasp; improved; innovation; microstimulation; motor control; multimodality; multisensory; neuromechanism; neurophysiology; relating to nervous system; response; sensory cortex; sensory feedback; sensory integration; sensory system; somatosensory; visual feedback

Project Summary: Multisensory processing is vital for daily activities such as walking and manipulating objects, yet much remains unknown about the neural mechanisms by which sensory information is integrated in the central nervous system to influence motor control. We address this knowledge gap by analyzing behavioral and multi-neuronal multi-area recordings in the cerebral cortex of Rhesus monkeys trained to perform a prolonged motor control task (the critical stability task (CST)) that cannot be performed without continuous sensory feedback (visual and/or tactile). Rhesus monkeys will perform the CST using hand movements or a brain-computer interface (BCI) to control a cursor, while we manipulate sensory feedback. Neural activity will be recorded from primary visual (V1), somatosensory (S1) and motor cortices (M1). Our motivating hypothesis is that cortical processing is highly flexible, and can be rapidly reconfigured based on the immediate sensory and motor context. Several specific predictions flow from this perspective. First, we predict that primary motor cortex (M1) will exhibit a strong sensory response during a motor task that requires ongoing sensory feedback. Second, we hypothesize that V1 neurons adopt tactile responses, and S1 adopts visual responses, when both are relevant for ongoing motor control. Third, we expect that altering the signal quality of one sensory modality will shift their relative contribution to neural responses, consistent with Bayesian estimation. Animals will perform the CST using BCI control as a more dramatic test of cortical flexibility. During BCI control, sensory responses should be reduced in M1, since the BCI decoder cannot distinguish sensory responses from motor commands, which would diminish the quality of control. If multisensory integration is reduced in M1 under BCI control, then it must occur elsewhere. We hypothesize that there will be an enhanced cross-modal sensory representation in the primary sensory cortices under BCI control, in comparison to hand control. We approach these questions through a collaboration that combines expertise in sensorimotor neurophysiology with expertise in computational modeling of multisensory integration. The findings of this research will improve the understanding of the neural mechanisms of multimodal sensory integration during continuous motor tasks, and will have clinical implications for BCIs and advanced prostheses design.

项目摘要：多感官处理对于行走和操作等日常活动至关重要 物体，但关于整合感觉信息的神经机制仍然未知 影响中枢神经系统的运动控制。我们通过分析来解决这一知识差距 恒河猴大脑皮层的行为和多神经元多区域记录，经过训练 执行长时间的电机控制任务（关键稳定性任务（CST）），如果没有的话就无法执行 连续的感官反馈（视觉和/或触觉）。恒河猴将用手进行 CST 当我们操纵感觉反馈时，通过运动或脑机接口（BCI）来控制光标。 将从初级视觉 (V1)、体感 (S1) 和运动皮层 (M1) 记录神经活动。我们的 激励假设是皮层处理高度灵活，并且可以根据 直接的感觉和运动环境。从这个角度出发，可以得出一些具体的预测。首先，我们预测 在需要持续进行的运动任务中，初级运动皮层（M1）将表现出强烈的感觉反应 感官反馈。其次，我们假设 V1 神经元采用触觉反应，S1 神经元采用视觉反应。 当两者都与正在进行的运动控制相关时。第三，我们期望改变信号质量 一种感觉方式将改变它们对神经反应的相对贡献，这与贝叶斯一致 估计。动物将使用 BCI 控制进行 CST，作为对皮质灵活性的更戏剧性的测试。期间 BCI 控制，M1 中的感官反应应减少，因为 BCI 解码器无法区分感官反应 来自运动命令的响应，这会降低控制质量。如果多感觉统合 M1 在 BCI 控制下减少，那么它一定发生在其他地方。我们假设将会有一个增强的 与手相比，BCI 控制下初级感觉皮层的跨模式感觉表征 控制。我们通过结合感觉运动专业知识的合作来解决这些问题 神经生理学，具有多感觉整合计算建模方面的专业知识。本次调查结果 研究将提高对多模态感觉统合神经机制的理解 连续运动任务，将对脑机接口和先进假肢设计产生临床影响。