The Mechanisms of Perceptual Learning

描述(申请人提供)：知觉学习(PL)被定义为在视觉任务中的长期增强或由于重复的视觉经验而进行的增强过程，被认为是视觉可塑性的表现。因此，对PL的研究将有助于进一步阐明视觉可塑性，而视觉可塑性是视觉科学的重要目标之一。近年来，对PL的研究有两个重要的进展。首先，强化信号在PL中起着重要作用。第二，睡眠是巩固PL的基础。然而，PL的这些方面的神经机制还没有很好地阐明。此外，这些方面都是完全分开研究的(即，彼此不相关)。此外，尽管存在(1)任务重复执行导致的任务相关延迟(TRPL)和(2)暴露于视觉特征下的任务无关延迟(TIPL)，但强化信号和睡眠巩固的作用尚未被考虑到这两种不同类型的任务相关延迟。使用对fMRI信号的解码方法，我们观察了在与PL相关的不同条件下，几个大脑区域中每个区域的“调谐曲线”如何变化(全局调谐曲线变化)。在这个提案中，我们将利用这一新技术，从相同的角度研究TRPL和TIPL中强化信号和睡眠巩固的神经机制，并旨在阐明这些机制是如何相互联系的。当前提议的目标1的目标是阐明强化信号的神经机制。虽然已经指出奖赏驱动的强化信号在PL中起着重要的作用，但奖赏如何影响PL的神经机制还不清楚。我们将通过研究带奖励的PL训练如何导致大脑区域的全局调整曲线变化来解决这个问题。目标2的目标是阐明睡眠巩固过程中神经机制的变化。虽然已有研究表明，睡眠是巩固PL的基础，但在不同类型的睡眠(非快速眼动和快速眼动)、不同类型的训练(任务相关和任务无关的PL)以及有无奖励的情况下，巩固过程中的神经机制如何变化仍不清楚。我们将通过研究在这些不同条件下的全局调谐曲线变化来解决这些问题。此外，是否共同的神经机制涉及奖赏和睡眠巩固，将通过比较这两个目标获得的全局调整曲线来检验。到目前为止，已经使用不同的范例和刺激研究了强化信号和睡眠巩固在PL中的作用。在同一框架内系统地研究增强信号和睡眠巩固的神经机制及其在TRPL和TIPL中的相互作用将使我们更好地理解潜在的、不同的研究人员对PL的神经机制。

DESCRIPTION (provided by applicant): Perceptual learning (PL) is defined as long-term enhancement in a visual task or the process for the enhancement as a result of repeated visual experience and is regarded as manifestation of visual plasticity. Thus, studying PL will lead to increased clarification of visual plasticity, which is one of the most important goals in the visual sciences. Recently, there have been two important developments in studies of PL. First, reinforcement signals play an important role in PL. Second, sleep is fundamental for consolidation of PL. However, the neural mechanisms for these aspects of PL are not well clarified. In addition, these aspects have been studied totally separately (i.e., without relating to each other). Furthermore, although there are (1) task- relevant PL (TRPL) resulting from repetitive performance of a task and (2) task-irrelevant PL (TIPL) resulting from exposure to a visual feature, the roles of reinforcement signals and sleep consolidation have yet to be examined taking these two different types of PL into consideration. Using a decoding method applied to fMRI signals, we have observed how the "tuning curve" in each of several brain areas changes (global tuning curve changes) under various conditions in association with PL. In this proposal, by taking advantage of using this new technique, we will investigate what the neural mechanisms are for reinforcement signal and sleep consolidation in TRPL and TIPL from the same viewpoint and aim to clarify how these mechanisms relate to each other. The goal of Aim 1 of current proposal is to clarify the neural mechanism for reinforcement signals. While it has been pointed out that reward-driven reinforcement signal plays an important role in PL, it remains unclear how the reward influences neural mechanisms in PL. We will address this question by examining how training of PL with reward leads to global tuning curve changes in brain areas. The goal of Aim 2 is to clarify neural mechanism changes during sleep consolidation. While it has been shown that sleep is fundamental for PL consolidation, it remains unclear how the neural mechanisms change during consolidation in different types of sleep (Non-REM and REM), different types of training (task-relevant and task-irrelevant PL), and with and without reward. We will address these questions by examining global tuning curve changes in these different conditions. Also, whether common neural mechanisms are involved in reward and sleep consolidation in PL will be examined by comparing global tuning curves obtained in these two aims. To date have examined reinforcement signals and sleep consolidation in PL using different paradigms and stimuli. Systematic investigation of the neural mechanisms for reinforcement signal and sleep consolidation and their interactions in each of TRPL and TIPL within the same framework will lead to significantly greater understanding of the underlying, different researchers neural mechanisms for PL.