Neural and Behavioral Interactions Between Attention, Perception, and Learning

描述(由申请人提供)：这项研究的主要目标是从帮助将视觉经验转化为记忆的学习机制和调节这种转变的有意机制两个方面描述感知和记忆是如何相互作用的。这一建议的具体目标是检验这样一种假设，即关于视觉统计规律的附带学习(视觉统计学习)仅限于选择性地注意视觉信息，这种行为交互作用的产生是因为选择性注意如何调节人类视觉和记忆系统之间的神经交互作用。我们提出了一个两阶段框架，在这个框架中，对高水平视觉特征/类别的选择性注意增加了代表低水平特征的枕叶皮质区域和代表所关注的特征/类别的颞叶下部(IT)区域之间的神经交互作用，进而增加了该IT区域与参与视觉学习和记忆的内侧颞叶(MTL)亚区之间的神经交互作用。除了评估基于特征的选择性注意如何在行为水平上影响学习之外，我们还将使用功能磁共振成像来评估注意力如何影响与任务相关的脑区的诱发神经反应，以及正在进行的任务背景下这些区域之间的神经相互作用。我们将开发一种创新的方法来研究神经相互作用，其中从数据中去除诱发反应和全局噪声源，并在残差中评估区域相关性。这种背景连通性方法为研究有意目标如何影响知觉和学习提供了一种新的途径。目标1检查我们框架的第一阶段，测试：选择性注意如何调节IT和枕叶皮质之间的背景连接，这种调制在视网膜视觉皮质中发生在哪里，以及这些变化是如何由额叶和顶叶皮质控制的。目的2研究我们框架的第二阶段，首先确定MTL在视觉统计学习中的作用，然后测试：选择性注意如何调节IT和MTL之间的相互作用，这种调制在MTL的皮质和海马子区域中发生在哪里，以及这些变化如何促进关于统计规律的附带学习和以后对这些知识的提取。总而言之，我们将选择性注意和学习之间的行为交互作用与代表视觉特征的机制和学习它们之间关系的机制之间的神经交互联系起来。这一建议解决了该领域的几个关键问题，包括：注意如何调节MTL，基于特征的注意是如何控制的，不同的神经机制是否支持快速和长期视觉学习，任务和目标是如何呈现的，以及注意力和记忆提取是如何相关的。这项研究将加深我们对人类如何从视觉经验中学习，以及视觉处理如何受学习影响的理解。这些进展将阐明在眼睛疾病、损伤或脑损伤后视觉功能的发育和恢复过程中发生的可塑性。

DESCRIPTION (provided by applicant): The overarching goal of this research is to characterize how perception and memory interact, in terms of both the learning mechanisms that help transform visual experience into memory, and the intentional mechanisms that regulate this transformation. The specific goal of this proposal is to test the hypothesis that incidental learning about statistical regularities in vision (visual statistical learning) is limited to selectively attend visual information, and that this behavioral interaction arises because of how selective attention modulates neural interactions between human visual and memory systems. We propose a two-stage framework in which selective attention to a high-level visual feature/category increases neural interactions between regions of occipital cortex that represent low-level features and the region of inferior temporal cortex (IT) that represents the attended feature/category, and in turn between this IT region and medial temporal lobe (MTL) sub regions involved in visual learning and memory. In addition to assessing how feature-based selective attention influences learning at a behavioral level, we will use functional magnetic resonance imaging to assess how attention influences evoked neural responses in task-relevant brain regions, as well as neural interactions between these regions in the background of ongoing tasks. We will develop an innovative approach for studying neural interactions in which evoked responses and global noise sources are scrubbed from the data and regional correlations are assessed in the residuals. This background connectivity approach provides a new way to study how intentional goals affect perception and learning. Aim 1 examines the first stage of our framework, testing: how selective attention modulates background connectivity between IT and occipital cortex, where in retinotopic visual cortex this modulation occurs, and how these changes are controlled by frontal and parietal cortex. Aim 2 examines the second stage of our framework, first establishing the role of the MTL in visual statistical learning, and then testing: how selective attention modulates interactions between IT and the MTL, where in cortical and hippocampal sub regions of the MTL this modulation occurs, and how these changes facilitate incidental learning about statistical regularities and later retrieval of this knowledge. In sum, we relate behavioral interactions between selective attention and learning to neural interactions between the mechanisms that represent visual features and those that learn about their relations. This proposal addresses several key issues in the field, including: how attention modulates the MTL, how feature-based attention is controlled, whether different neural mechanisms support rapid versus long-term visual learning, how tasks and goals are represented, and how attention and memory retrieval are related. This research will improve our understanding of how humans learn from visual experience, and how visual processing is in turn influenced by learning. These advances will shed light on the plasticity that occurs during development and during the recovery and rehabilitation of visual function following eye disease, injury, or brain damage.