Coding and processing of error signals in inferior olivary-cerebellar networks

下橄榄小脑网络中误差信号的编码和处理

基本信息

批准号：
9432553
负责人：
JAVIER F MEDINA
金额：
$ 39.63万
依托单位：
BAYLOR COLLEGE OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-06-02 至 2021-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9432553
关键词：
Animals Area Ataxia Attention deficit hyperactivity disorder Autistic Disorder Automobile Driving Behavior Behavioral Biological Models Blinking Brain Calcium Cells Cerebellar Diseases Cerebellar Nuclei Cerebellum Code Cognition Disorders Cognitive Complex Cues Disease Dystonia Educational process of instructing Electrophysiology (science)Event Extinction (Psychology)Eyelid structure Fiber Fire - disasters Future Goals Grant Habits Head Heterogeneity Image Impairment Inferior Instruction Lead Learning Light Link Molecular Target Monitor Motor Movement Mus Neurologic Neuronal Plasticity Occupations Olives - dietary Outcome Performance Phase Play Process Purkinje Cells Research Role Schizophrenia Signal Transduction Source Specificity Stimulus Symptoms Synapses System Testing Time Update Work conditioning design expectation experience experimental study improved motor control motor disorder motor learning nervous system disorder neural circuit neuromechanism neuropsychiatric disorder neuropsychiatry neurotransmission new technology novel novel therapeutic intervention novel therapeutics optogenetics predicting response relating to nervous system response teacher theories tool treadmill two-photon

Animals Area Ataxia Attention deficit hyperactivity disorder Autistic Disorder Automobile Driving Behavior Behavioral Biological Models Blinking Brain Calcium Cells Cerebellar Diseases Cerebellar Nuclei Cerebellum Code Cognition Disorders Cognitive Complex Cues Disease Dystonia Educational process of instructing Electrophysiology (science)Event Extinction (Psychology)Eyelid structure Fiber Fire - disasters Future Goals Grant Habits Head Heterogeneity Image Impairment Inferior Instruction Lead Learning Light Link Molecular Target Monitor Motor Movement Mus Neurologic Neuronal Plasticity Occupations Olives - dietary Outcome Performance Phase Play Process Purkinje Cells Research Role Schizophrenia Signal Transduction Source Specificity Stimulus Symptoms Synapses System Testing Time Update Work conditioning design expectation experience experimental study improved motor control motor disorder motor learning nervous system disorder neural circuit neuromechanism neuropsychiatric disorder neuropsychiatry neurotransmission new technology novel novel therapeutic intervention novel therapeutics optogenetics predicting response relating to nervous system response teacher theories tool treadmill two-photon

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项目摘要

PROJECT SUMMARY The cerebellum plays a key role in motor control, particularly in motor learning. More recently, the cerebellum has also been implicated in cognitive processing. Indeed, cerebellar damage is associated with a wide range of neurological and neuropsychatric disorders, including ataxia, dystonia, schizophrenia and autism. Despite this apparent functional heterogeneity, the cerebellar microcircuit is remarkably homogeneous, both across its different regions and across different animal species. Thus, it has been suggested that the cerebellum may accomplish its job by performing one universal computation, and then sending out the results of the computation to other brain areas, both motor and non-motor. Previous work indicates that the universal computation performed by the cerebellum involves using past experience to predict future events, including those that are caused by our own movements. The long-term objective of this project is to achieve a full mechanistic understanding of how the cerebellum learns to make these predictions. The focus will be on the error signals that are critical for alerting the cerebellum that a prediction was wrong and needs to be updated. In the three aims of this proposal, we examine: 1) positive prediction errors (when something unexpected happens), 2) negative prediction errors (when something expected doesn't happen), and 3) temporal- difference prediction errors (when a stimulus predicts that something is about to happen). All experiments are done on a newly developed treadmill apparatus for eyeblink conditioning in head-fixed mice. Eyeblink conditioning was chosen as the model system because it offers a number of advantages for the project: 1) The behaviorally-relevant error signals are under experimental control and can be easily manipulated, 2) The basic conditioning task can be modified to ask questions about the role of error signals in driving both motor learning and higher-order associations, and 3) The olivo-cerebellar regions that are critical for processing error signals have been identified. By combining the elegant simplicity of eyeblink conditioning with new technologies for optogenetics, electrophysiology, and two-photon calcium imaging, the proposed experiments will record and manipulate the error-related neural signals present during the learning process with an unprecedented level of temporal and cellular specificity. This research could help develop new therapeutic approaches to treat motor and cognitive disorders associated with cerebellar dysfunction, not by targeting molecular mechanisms of neural plasticity, but the instructive error-related signals that drive them. In this regard, the specific aims of the application are designed to ask not only “what is the neural code for error signals in the cerebellum”, but also “how can we manipulate the code to enhance learning?”.

项目摘要小脑在运动控制中起着关键作用，尤其是在运动学习中。最近，小脑在认知处理中也暗示了。确实，小脑损害与广泛的神经和神经心理疾病，包括共济失调，肌张力障碍，精神分裂症和自闭症。尽管如此明显的功能异质性，小脑微电路非常均匀不同的地区以及不同的动物物种。那就是建议小脑可以通过执行一个通用计算来完成其工作，然后发送计算电动机和非运动器的其他大脑区域。以前的工作表明通用小脑执行的计算涉及使用过去的经验来预测未来事件，包括那些由我们自己的运动引起的。该项目的长期目标是实现完整的对小脑如何学会做出这些预测的机械理解。重点将放在错误信号对于警告小脑至关重要，即预测是错误的，需要更新。在该提案的三个目标中，我们研究：1）积极的预测错误（当某些意外情况时发生），2）负面预测错误（当预期的事情没有发生时），3）临时 - 差异预测错误（当刺激预测即将发生的事情时）。所有实验都是在新开发的跑步机设备上完成，用于在头部固定小鼠中进行透明调节。扬声器选择条件作为模型系统，因为它为项目提供了许多优势：1）与行为相关的错误信号处于实验控制之下，并且可以轻松操纵，2）基本可以修改调理任务以询问有关错误信号在驱动两个运动学习中的作用的问题和高阶关联，以及3）Olivo-Cerebellar区域对于处理误差信号至关重要已经确定了。通过将Eykblink调节的优雅简单与新技术相结合光遗传学，电生理学和两光子钙成像，提出的实验将记录并操纵学习过程中存在的与错误相关的神经信号，并以前所未有的水平临时和细胞特异性。这项研究可以帮助开发新的治疗运动方法和与小脑功能障碍相关的认知障碍，而不是针对分子机制神经可塑性，但引导它们的指导性错误相关的信号。在这方面，应用程序旨在不仅询问“小脑中错误信号的神经代码”，还询问 “我们如何操纵代码以增强学习？”。