COMPUTATIONAL ANALYSIS OF CEREBELLAR MOTOR LEARNING

描述（改编自申请人摘要）：长期目标 拟议的研究是，通过使用生物详细的计算机， 模拟，以阐明运动学习的小脑机制， 足够的细节，以允许计算机模拟的关键功能 大脑结构的特性。 因为有证据表明 小脑也介导某些认知功能，这些信息可能 有助于识别认知的神经基础及其功能障碍 精神疾病 拟议研究的具体目标是使用 模拟识别信息处理机制所采用的 小脑介导的运动学习的良好表征形式。 一 许多因素使这种方法特别强大：1）行为 这些运动学习形式的特性被广泛表征; 2)小脑的突触组织和生理学（连接 图）是众所周知的;和，3）的方式，其中简单形式的电机 学习参与小脑允许输入和输出特性的 小脑的研究和建模，相对直接。 与这些 优点，可以使用生物学详细的计算机模拟 以解决关于小脑机制的特定假设， 产生目标行为。 目标行为的成功解释， 这些模拟代表了对潜在的 这是一个既量化又详细的机制。 相反，识别 模拟的局限性应该导致关键的想法，新的 理论，并应指出实验的关键进一步的进展。 具体的目标将测试一系列详细的假设， 小脑运动学习的机制是由以前的建议， 实证和模拟研究。 这些假设说明了 小脑可以学习，保留和遗忘运动，以及如何 获得运动的适当定时。 由于突触解剖学 小脑的运动区和非运动区是一致的， 识别运动学习中涉及的小脑信息处理 还将提供进入信息处理所涉及的， 认知，这可能会导致更好地了解病理 潜在的精神疾病

DESCRIPTION (Adapted from applicant's abstract): The long-term objective of the proposed studies is, through the use of biologically detailed computer simulations, to elucidate the cerebellar mechanisms of motor learning with sufficient detail to permit computer emulation of the key functional properties of this brain structure. Since evidence indicates that the human cerebellum also mediates certain cognitive functions, such information may be useful in identifying the neural basis of cognition and its malfunction in mental illness. The specific goal of the proposed studies is to use simulations to identify the information processing mechanisms employed by the cerebellum to mediate well-characterized forms of motor learning. A number of factors make this approach especially powerful: 1) the behavioral properties of these forms of motor learning are extensively characterized; 2) the synaptic organization and physiology of the cerebellum (the wiring diagram) is well known; and, 3) the way in which the simple forms of motor learning engage the cerebellum permit the input and output properties of the cerebellum to be studied, and modeled, relatively directly. With these advantages, it is possible to use biologically detailed computer simulations to address specific hypotheses regarding the cerebellar mechanisms that produce the target behaviors. Successful accounts for target behaviors by the simulations represent a level of understanding of the underlying mechanisms that is both quantitative and detailed. In contrast, identifying the limitations of the simulations should lead to crisper ideas, new theories, and should point to the experiments critical for further progress. The specific aims will test a series of detailed hypotheses regarding the mechanisms of cerebellar motor learning that are suggested by previous empirical and simulations studies. These hypotheses address how the cerebellum can learn, retain, and unlearn movements, as well as how the appropriate timing of the movements is obtained. Since the synaptic anatomy of the cerebellum is uniform across both motor and non-motor areas, identifying the cerebellar information processing involved in motor learning will also provide inroads into the information processing involved in cognition, which may lead to a better understanding of the pathologies underlying mental illness.