Mechanisms for Internal Models in a Cerebellum-like Circuit

项目摘要/摘要 预测行动的后果是神经系统的一项重要功能。假想的神经 基板是所谓的内部模型，它转换有关传出电机命令和 将当前感觉状态转化为对感觉输入的预测。这样的内部模型很可能在很大范围内是关键的 感觉、运动和认知功能以及它们的破坏被认为与神经疾病有关 比如自闭症和精神分裂症。然而，事实证明，理解内部模型是如何 是在哺乳动物大脑的神经回路中实现的。我们之前的研究成功地开发了一种 对鱼电感觉叶(ELL)神经元如何预测的详细机械理解 并抵消一个简单行为的感官后果--电子器官放电(EOD)脉冲。 然而，因为这些研究是在固定的动物中进行的，所以所研究的预测的性质 在范围和复杂性上是有限的。这一更新使用了新的神经记录方法和高分辨率 对自由游动的鱼进行行为监测，以研究更复杂的内在模型 电鱼具有显著的主动电定位能力。将使用计算建模方法 既要严格定义主动电感系统面临的问题，又要产生和测试真实感 如何解决这些问题的电路级模型。这类模型的关键组件，包括突触 轴突和树突的可塑性、经常性和前馈连接性以及生物物理区划 棘波是包括小脑、海马体和新皮质在内的许多神经系统的共同特征。因此 这些研究的洞察力预计将广泛与理解内部模型是如何 在神经系统中实现。

Project Summary/Abstract Predicting the consequences of action is a vital function of the nervous system. The hypothesized neural substrate are so-called internal models that transform information about outgoing motor commands and the current sensory state into predictions of sensory input. Such internal models are likely critical for a wide range of sensory, motor, and cognitive functions and their disruption has been implicated in neurological disorders such as autism and schizophrenia. Nevertheless, it has proven challenging to understand how internal models are implemented in neural circuits in the mammalian brain. Our prior studies were successful in developing a detailed mechanistic understanding of how neurons in the electrosensory lobe (ELL) of mormyrid fish predict and cancel out the sensory consequences of a simple behavior--the electric organ discharge (EOD) pulse. However, because these studies were performed in immobilized animals, the nature of the predictions studied was limited in scope and complexity. This renewal uses novel methods for neural recording and high-resolution behavior monitoring in freely swimming fish to study the more complex internal models underlying the remarkable active electrolocation abilities of electric fish. Computational modeling approaches will be used both to rigorously define the problem facing the active electrosensory system and to generate and test realistic circuit-level models of how they may be solved. The key components of such models, including synaptic plasticity, recurrent and feedforward connectivity, and biophysical compartmentalization of axonal and dendritic spikes, are common to many neural systems including the cerebellum, hippocampus, and neocortex. Hence insights from these studies are expected to be widely relevant to understanding how internal models are implemented in neural systems.