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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：
10655659
负责人：
JAVIER F MEDINA
金额：
$ 50.59万
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 2027-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10655659
关键词：
Affective Afferent Pathways Animals Anterior Area Ataxia Attention Attention deficit hyperactivity disorder Behavior Blinking Brain Brain region Cell Nucleus Cells Cerebellar Cortex Cerebellar Diseases Cerebellum Cerebral cortex Code Cognition Disorders Cognitive Communication Communication impairment Conditioned Stimulus Cues Disease Dorsal Dystonia Educational process of instructing Event Fiber Future Goals Heterogeneity Individual Inferior Instruction Learning Link Machine Learning Mental Processes Molecular Target Motor Movement Mus Neurologic Neuronal Plasticity Neurons Occupations Olives - dietary Pathway interactions Play Pontine structure Prefrontal Cortex Process Protocols documentation Purkinje Cells Research Rest Role Schizophrenia Sensory Short-Term Memory Signal Transduction Somatosensory Cortex Source Specificity Stimulus Syndrome Testing Time Training Update Work autism spectrum disorder cognitive function density expectation experimental study eyeblink conditioning insight mossy fiber motor control motor learning nervous system disorder neural neuromechanism neuropsychiatric disorder novel therapeutic intervention optogenetics response supervised learning theories tool

项目摘要

PROJECT SUMMARY The cerebellum plays a key role in motor control, particularly in motor learning. However, there is increasing recognition that the cerebellum also participates in cognitive functions such as planning, set-shifting, abstract reasoning, attention and working memory. Indeed, cerebellar damage is associated with both motor and cognitive problems and has been linked to a wide range of neurological and neuropsychiatric disorders, from ataxia and dystonia to schizophrenia and autism. Despite this remarkable functional heterogeneity, the cerebellar microcircuit is remarkably homogeneous, both across its different regions and across different animal species. This has led to the theory that the cerebellum may accomplish its job by performing one universal computation, which can be applied to both motor and non-motor functional domains by connecting the cerebellum to different brain areas. Much of what we know about this universal computation comes from mechanistic studies that have revealed what the cerebellum does – and how it does it – by manipulating and recording neural activity in the cerebellum of mice and other animals performing simple sensorimotor learning tasks. Based on this previous work, a picture is emerging that the cerebellum is a ‘machine’ specialized for supervised learning, whose function can be summarized succinctly: to learn how to eliminate errors. While there is good support for this idea for learning tasks in which the error signals are low-level and conveyed directly from the sensory periphery to the cerebellum via subcortical pathways, there is almost nothing known about the function of high-level error signals originating in parts of the brain that are not directly connected to the sensory or motor periphery. The goal of this project is to start filling this gap by examining how the cerebellum operates when mice are trained in 3 new learning tasks recently developed, in which the error signals originate in the primary somatosensory cortex (aim 1), the cerebellum itself (aim 2) and the prefrontal cortex (aim 3). To assess function, the proposed experiments will record and manipulate the error signals present during the learning process with an unprecedented level of temporal and cellular specificity, using new high-density Neuropixels tools and cell-specific photostimulation with optogenetics. This research could help develop new therapeutic approaches to treat both motor as well as cognitive disorders associated with deficient connectivity between the cerebellum and the rest of the brain, not by targeting molecular mechanisms of neural plasticity, but the instructive error-related signals that drive them.

项目摘要小脑在运动控制中起着关键作用，特别是在运动学习中。然而，越来越多的认识到小脑也参与认知功能，如计划，转移，抽象推理、注意力和工作记忆。事实上，小脑损伤与运动神经和认知问题，并已与广泛的神经和神经精神疾病，从共济失调和肌张力障碍到精神分裂症和自闭症。尽管有这种显著的功能异质性，小脑的微回路是非常均匀的，在不同的区域和不同的区域都是如此。动物种类。这导致了一种理论，即小脑可能通过执行一个通用计算，它可以通过连接应用于运动和非运动功能域小脑到不同的大脑区域。我们对这种通用计算的了解大部分来自机械研究揭示了小脑的作用-以及它是如何做到这一点的-通过操纵和记录小鼠和其他进行简单感觉运动学习的动物小脑中的神经活动任务基于先前的工作，一幅图片正在出现，小脑是一台专门用于监督学习，其功能可以简单地概括为：学习如何消除错误。而对于错误信号是低水平的并且被传递的学习任务，通过皮层下通路直接从感觉外周到小脑，关于高水平错误信号的功能，这些信号起源于大脑中与大脑没有直接联系的部分，感觉或运动周边。该项目的目标是通过研究如何开始填补这一空白当老鼠在最近开发的3个新的学习任务中接受训练时，小脑会起作用，信号起源于初级躯体感觉皮层（aim 1），小脑本身（aim 2）和前额叶皮层（aim 1）。皮质（目标3）。为了评估功能，拟议的实验将记录和处理错误信号目前在学习过程中的时间和细胞特异性前所未有的水平，使用新的高密度神经像素工具和细胞特异性光刺激与光遗传学。这项研究可以帮助开发新的治疗方法来治疗运动和认知障碍，小脑和大脑其余部分之间的连接不足，而不是通过靶向分子机制神经可塑性，而是驱动它们的与错误相关的信号。