Learning temporal representations in cortex; mechanism and behavioral correlate

描述（由申请人提供）：这是一项研究提案的重新提交，旨在根据最近的实验和理论进展揭示大脑中时间估计的基础。这是一个实验和计算相结合的建议。 大脑完成的一项基本任务是形成适应性行为，这些适应性行为是对环境刺激之间的学习偶然性做出反应。然而，我们学习环境线索（特别是视觉线索）的行为相关性的神经过程，以及大脑基于这种视觉证据产生时间预期的机制，都是未知的。这个过程的一个例子和本文提出的工作的动机是Shelvis和Bear[1]的意外发现，即视觉刺激与延迟奖励配对会导致初级视觉皮层（V1）中奖励计时活动的出现。这一发现表明，V1并不只是作为一个被动的过滤器银行调查视觉世界，而是包含复杂的内部程序，信号的视觉事件的行为相关性，并参与计算动物的行为反应。基于这些最新的发现，我们发展了一个基于网络的皮层计时计算理论。这个理论可以解释时间是如何计算的，也可以解释时间是如何学习的。 在这个建议中，我们开发和测试这个模型来理解这个问题，提供了一系列实验上易于处理的预测，测试一个激进的概念：学习视觉提示的预期发生在初级视觉皮层（V1）局部作为一个相互作用的结果之间的冲击强化信号传达的结果与先前的突触活动的行为。我们将使用光遗传学技术测试V1中奖励信号的身份和性质，并因此测试计算是否是V1本地的。使用行为电生理学和计算技术的组合，我们将建立是否有观察到的动态V1和行为之间的关系，并操纵这种关系个体发育，并占实验观察到的标量属性的基础上观察到的生理和计算模型，我们的模型的所有标志的时间感知。 V1（更广泛地说，是皮质）表达线索奖励间隔的神经机制尚不清楚，本研究将对此进行讨论。因此，这项研究的结果将大大影响记忆和学习的神经过程，形成认知功能障碍的理解基础。

DESCRIPTION (provided by applicant): This is a resubmission of a research proposal to uncover the basis of timing estimation in the brain based on recent experimental and theoretical advances. This is a combined experimental and computational proposal. A fundamental task accomplished by the brain is the formation of adaptive behaviors generated in response to learned contingencies between environmental stimuli. Yet, the neural process by which we learn the behavioral relevance of environmental cues, specifically visual cues, and the mechanism by which brains generate temporal expectancies based on such visual evidence, is unknown. Exemplifying this process and motivating the work proposed here is the unexpected finding by Shuler and Bear[1] that pairing visual stimuli with delayed reward leads to the emergence of reward-timing activity in the primary visual cortex (V1). This finding suggests that V1 does not act simply as a passive filter bank surveying the visual world, but instead contains complex internal programs that signal the behavioral relevance of visual events, and participates in computing the animals' behavioral response. Based on these recent findings, we developed a network-based theory of timing computation in cortex. This theory can account both for how times are computed and how they are learned. In this proposal we develop and test this model for understanding this issue, proffering a series of experimentally tractable predictions that test a radical notion: Learning visually-cued expectancies occurs locally within the primary visual cortex (V1) as a result of an interaction between an impinging reinforcement signal conveying the outcome of behavior with prior synaptic activity. We will test using optogenetic techniques, the identity and nature of the reward signal in V1, and consequently also test if the computation is local to V1. Using a combination of behavioral electrophysiology and computational techniques we will establish if there is a relationship between the observed dynamics in V1 and behavior and manipulate that relationship ontogenetically, and also account for the experimentally observed scalar property in time perception on the basis of the observed physiology and the computational model, all hallmarks of our model. The neural mechanism by which V1 - and more broadly, cortex - comes to express cue-reward intervals is unknown and is addressed in this study. Consequently, the results of this study will bear greatly on neural processes of memory and learning, forming a basis of understanding for cognitive dysfunction.