Neural Computations Underlying Cancellation of the Vestibular Consequences of Voluntary Movement

消除随意运动前庭后果的神经计算

基本信息

批准号：
10434677
负责人：
Kathleen E Cullen
金额：
$ 53.22万
依托单位：
JOHNS HOPKINS UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-07-01 至 2024-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10434677
关键词：
Address Aging American Behavior Brain Brain Stem Calibration Cerebellar Cortex Cerebellar Nuclei Cerebellar vermis structure Cerebellum Code Computer Models Development Diagnosis Disease Dizziness Ensure Equilibrium Esthesia Functional disorder Generations Goals Head Head Movements Impairment Knowledge Labyrinth Learning Maintenance Mediating Modeling Monkeys Motion Motivation Motor Movement Neurons Pathway interactions Patients Pattern Perception Performance Play Population Postural response Posture Purkinje Cells Quality of life Reflex action Research Research Project Grants Research Project Summaries Rewards Role Sensory Signal Transduction Source Stimulus Symptoms System Testing Update Vestibular loss Vestibular nucleus structure base behavioral study density design experimental study fall risk gaze improved insight motor control neuromechanism novel programs relating to nervous system response sensory feedback sensory input sensory stimulus spinal reflex vestibular pathway

项目摘要

Project Summary: This research program is motivated by three goals. First, we will establish the neural mechanisms that underlie the brain's ability to estimate and cancel self-generated vestibular (inner ear balance) input during active movement. Second, we will determine how the vestibular cerebellum learns to adapt to changes in the relationship between expected and actual sensory input to maintain stabile perception and accurate behavior. Third, we will assess how reward-motivation signals influence circuit performance. The brain's ability to distinguish sensory stimuli that are the result of self-generated (i.e., active) versus unexpected or externally generated (i.e., passive) stimulation is vital to ensuring perceptual stability and accurate motor control. Notably, in the vestibular system, the same central neurons that receive afferent input also send direct projections to motor centers to control balance and posture via the vestibular-spinal reflex. This reflex is essential for providing robust postural responses to unexpected vestibular stimuli, yet is counter- productive when the goal is to make active head movements. Accordingly, it is advantageous to suppress this pathway during active self-motion. Over the past two decades, we have made excellent progress toward identifying where brain makes the distinction between reafferent (i.e., active) and exafferent (i.e., passive) vestibular signals. Specifically, while the responses of vestibular afferents remain robust (and equivalent) regardless of whether stimulation is active or passive, neurons at the next stage of processing in the vestibular nuclei are significantly less responsive to active self-motion. In addition, we have shown that this suppression only occurs when sensory feedback matches that expected based on the motor command (e.g., during normal active movements). In the proposed research, we will address several fundamental questions that remain open regarding the computations that the brain performs to ensure stable perception and accurate motor control during self-motion. First, experiments in Aim 1 will investigate how the brain computes the vestibular cancellation signal that eliminates actively generated signals from early sensory processing. We predict that the cerebellar cortex plays an essential role in computing the mismatch between expected and actual vestibular input to compute a cancellation signal. Aim 2 will determine how the cerebellum learns to interpret active motion as self-generated when the relationship between the actual and expected sensory feedback is altered. These experiments will provide insight into the error-based mechanisms that ensure calibration of the vestibular reafference suppression mechanism is maintained. Finally, in Aim 3 we will determine whether and how motivation modulates cerebellum-mediated vestibular reafference suppression. Combined, these studies will (1) determine the source of the vestibular reafference cancellation signal, (2) advance our understanding of the cerebellum adapts to changes in vestibular input, and (3) clarify how neuronal mechanisms underlying reafference suppression can be leveraged by motivational influences to optimize performance.

项目摘要：该研究计划由三个目标推动。首先，我们将建立神经网络大脑评估和消除自身产生的前庭（内耳）能力的机制平衡）主动运动期间的输入。其次，我们将确定前庭小脑如何学习适应预期和实际感觉输入之间关系的变化，以保持稳定的感知和准确的行为。第三，我们将评估奖励激励信号如何影响电路性能。大脑区分自我产生（即主动）和外部感觉刺激的能力意外或外部产生的（即被动）刺激对于确保知觉稳定性和精确的电机控制。值得注意的是，在前庭系统中，接收传入输入的相同中枢神经元还向运动中心发送直接投射，以通过前庭脊髓反射控制平衡和姿势。这种反射对于对意外的前庭刺激提供强有力的姿势反应至关重要，但也是反作用的。当目标是进行积极的头部运动时，效果会更好。因此，抑制这种情况是有利的主动自我运动期间的路径。过去二十年来，我们在以下方面取得了巨大进展：识别大脑在何处区分传入（即主动）和传出（即被动）前庭信号。具体来说，虽然前庭传入神经的反应仍然强劲（且相当）无论刺激是主动还是被动，前庭神经元在下一阶段的处理过程中原子核对主动自运动的反应明显较差。此外，我们已经证明这种抑制仅当感觉反馈与基于电机命令的预期相匹配时才会发生（例如，在正常情况下）主动运动）。在拟议的研究中，我们将解决几个仍然悬而未决的基本问题关于大脑为确保稳定的感知和准确的运动控制而执行的计算自我运动过程中。首先，目标 1 中的实验将研究大脑如何计算前庭消除信号，消除早期感觉处理中主动生成的信号。我们预测小脑皮层在计算预期与实际之间的不匹配方面起着至关重要的作用前庭输入来计算取消信号。目标 2 将决定小脑如何学习解释当实际和预期的感觉反馈之间的关系为时，主动运动是自生成的改变了。这些实验将深入了解基于误差的机制，确保校准前庭再传入抑制机制得以维持。最后，在目标 3 中，我们将确定是否和动机如何调节小脑介导的前庭再传入抑制。综合起来，这些研究将（1）确定前庭再传入抵消信号的来源，（2）增进我们对小脑适应前庭输入的变化，并且（3）阐明潜在的神经元机制动机影响可以利用再传入抑制来优化绩效。