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，该提案旨在揭示基于最近的实验和理论进步的大脑时间估计的基础。这是一个实验和计算相结合的方案。大脑完成的一项基本任务是形成适应行为，以对环境刺激之间的习得偶发事件做出反应。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，是未知的。Shuler和Bear[1]出人意料的发现证明了这一过程并激励了这里提出的工作，他们发现，将视觉刺激与延迟的奖励配对会导致初级视觉皮质(V1)出现奖励计时活动。这一发现表明，V1并不是简单地充当调查视觉世界的被动滤波器组，而是包含复杂的内部程序，这些程序发出视觉事件的行为相关性信号，并参与计算动物的行为反应。基于这些最新发现，我们发展了一种基于网络的大脑皮层计时计算理论。这一理论既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，我们开发和测试了这个模型来理解这个问题，提供了一系列实验上容易处理的预测，这些预测测试了一个激进的概念：学习视觉线索预期发生在初级视觉皮质(V1)内，这是传达行为结果的撞击强化信号与先前突触活动之间相互作用的结果。我们将使用光遗传技术测试V1中奖励信号的一致性和性质，因此还将测试计算是否对V1是局部的。使用行为电生理学和计算技术的组合，我们将建立V1中观察到的动力学和行为之间是否存在关系，并从本体上操纵这种关系，并根据观察到的生理学和计算模型，解释实验观察到的时间感知的标量属性，这是我们模型的所有特征。V1--更广泛地说，大脑皮层--表达线索-奖赏间隔的神经机制尚不清楚，本研究对此进行了探讨。因此，这项研究的结果将对记忆和学习的神经过程产生重大影响，形成对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.