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：多感官处理对于步行和操纵等日常活动至关重要 对象，但对感官信息的神经机制仍然未知 在中枢神经系统中影响运动控制。我们通过分析来解决这个知识差距 在经过训练的恒河猴大脑皮层中的行为和多神经多区域记录 执行长时间的电机控制任务（关键稳定性任务（CST）） 连续的感觉反馈（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，动作或脑部计算机界面（BCI）控制光标。 神经活动将记录在原发性视觉（V1），体感（S1）和运动皮层（M1）中。我们的 激励假设是皮质加工具有很高的灵活性，并且可以根据 立即感官和运动环境。从这个角度来看，几个特定的​​预测流动。首先，我们预测 那个主电机皮层（M1）将在运动任务中表现出强烈的感官响应，需要持续 感觉反馈。其次，我们假设V1神经元采用触觉反应，而S1采用了视觉 响应，当两者都与持续的电动机控制有关时。第三，我们期望改变信号质量 一种感官方式将把它们的相对贡献转移到神经反应上，与贝叶斯一致 估计。动物将使用BCI控制作为皮质柔韧性的更戏剧性的测试进行CST。期间 BCI控制，M1中应减少感觉响应，因为BCI解码器无法区分感觉 电机命令的响应将降低控制质量。如果多感官集成是 在BCI控制下，在M1中减少了，然后必须发生在其他地方。我们假设将有一个增强的 与手相比 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官整合计算建模方面的专业知识。这个发现 研究将改善对多模式感觉整合的神经机制的理解 连续的运动任务，并将对BCI和高级假体设计具有临床意义。