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
基本信息
- 批准号:9219134
- 负责人:
- 金额:$ 33.33万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:Activities of Daily LivingAddressAdoptedAffectAnimalsArchitectureAreaBasic ScienceBehaviorBehavior ControlBehavioralBrainCerebral cortexClinicalCollaborationsComputer SimulationDataDevelopmentDevicesEnvironmentEquilibriumEsthesiaExhibitsFeedbackGaitGoalsHandHand functionsHumanImpairmentKnowledgeMacaca mulattaModalityModelingMonitorMonkeysMotorMotor CortexMovementNervous System controlNeuraxisNeuronsPerformanceProsthesis DesignQuality ControlResearchResearch PersonnelSensorySignal TransductionSomatosensory CortexStudy modelsTactileTask PerformancesTechnologyTestingTrainingV1 neuronVisualWalkingarea striataarm movementbasebehavioral studybrain computer interfacecontrol theoryflexibilitygraspimprovedinnovationmicrostimulationmotor controlmultimodalitymultisensoryneuromechanismneurophysiologyrelating to nervous systemresponsesensory cortexsensory feedbacksensory integrationsensory systemsomatosensoryvisual feedback
项目摘要
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:多感官处理对日常活动至关重要,如行走和操作
物体,但关于整合感觉信息的神经机制仍有许多未知之处
影响运动控制的中枢神经系统。我们通过分析来解决这一知识鸿沟
训练恒河猴大脑皮层的行为和多神经元多区域记录
执行长期的运动控制任务(临界稳定性任务(CST))
持续的感觉反馈(视觉和/或触觉)。恒河猴将用手进行CST
移动或脑机接口(BCI)来控制光标,而我们操纵感觉反馈。
神经活动将从初级视觉(V1)、躯体感觉(S1)和运动皮质(M1)记录下来。我们的
激励假设是,皮质处理是高度灵活的,可以基于
直接的感觉和运动背景。从这个角度出发,有几个具体的预测。首先,我们预测
初级运动皮质(M1)将在需要持续进行的运动任务中表现出强烈的感觉反应
感官反馈。第二,我们假设V1神经元采用触觉反应,而S1神经元采用视觉反应
反应,当两者都与正在进行的运动控制相关时。第三,我们预计改变信号质量
一种感觉通道会改变它们对神经反应的相对贡献,这与贝叶斯一致
估计。动物将使用脑机接口控制进行CST,作为对皮质灵活性的更戏剧性的测试。在.期间
BCI控制,M1中的感觉反应应该减少,因为BCI解码器不能区分感觉
来自运动指令的响应,这将降低控制质量。如果多感官整合是
在BCI控制下的M1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
脑机接口控制下初级感觉皮层的跨模式感觉表征与手部的比较
控制力。我们通过合作来解决这些问题,这些合作结合了感应器运动方面的专业知识
神经生理学,在多感官整合的计算建模方面有专长。这项研究的发现
研究将提高对多模式感觉整合的神经机制的理解
持续的运动任务,并将对脑机接口和先进的假体设计具有临床意义。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Aaron Paul Batista其他文献
Aaron Paul Batista的其他文献
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{{ truncateString('Aaron Paul Batista', 18)}}的其他基金
CRCNS Research Proposal: Collaborative Research: Neural Basis of Motor Expertise
CRCNS 研究提案:合作研究:运动专业知识的神经基础
- 批准号:
10405066 - 财政年份:2020
- 资助金额:
$ 33.33万 - 项目类别:
CRCNS Research Proposal: Collaborative Research: Neural Basis of Motor Expertise
CRCNS 研究提案:合作研究:运动专业知识的神经基础
- 批准号:
10623241 - 财政年份:2020
- 资助金额:
$ 33.33万 - 项目类别:
CRCNS: Dynamical Constraints on Neural Population Activity
CRCNS:神经群体活动的动态约束
- 批准号:
10268145 - 财政年份:2017
- 资助金额:
$ 33.33万 - 项目类别:
CRCNS: Dynamical Constraints on Neural Population Activity
CRCNS:神经群体活动的动态约束
- 批准号:
9472546 - 财政年份:2017
- 资助金额:
$ 33.33万 - 项目类别:
CRCNS: Dynamical Constraints on Neural Population Activity
CRCNS:神经群体活动的动态约束
- 批准号:
9906941 - 财政年份:2017
- 资助金额:
$ 33.33万 - 项目类别:
CRCNS:Dissecting brain-computer interfaces:a manifold & feedback-control approach
CRCNS:剖析脑机接口:流形
- 批准号:
8336883 - 财政年份:2011
- 资助金额:
$ 33.33万 - 项目类别:
Differential contributions of frontal lobe areas to eye/hand coordination
额叶区域对眼/手协调的不同贡献
- 批准号:
8685340 - 财政年份:2011
- 资助金额:
$ 33.33万 - 项目类别:
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