Attentional Modulation of Brain Representations

描述（由申请人提供）：注意力改变了传入的感官信息的处理方式，以优化行为。确定注意力如何影响信息在整个大脑中的表现方式是感觉神经科学的核心问题。这个问题也有实际的后果，因为注意力相关的障碍会严重影响学习和行为。我们建议调查注意力如何改变整个人类大脑的结构和语义特征。为了解决这个问题，我们建议使用功能性MRI来记录血氧水平依赖（BOLD）信号，而人类搜索特定的对象或动作类别（例如，“人类”或“车辆”）在自然电影。然后，我们将使用一个创新的体素建模框架来描述注意力如何改变数百个结构和语义特征。这个框架将使我们能够分别表征注意对反应基线，反应增益和调谐的影响。该提案包括两个广泛的目标。目标1关注注意力如何改变物体和动作在大脑中的表现方式。目标2阐述了控制注意调谐变化的计算原理。这些实验将为理解大脑如何动态改变表征以优化自然视觉过程中的行为提供关键信息，并将提供第一个定量结构和语义模型，准确预测自然视觉搜索过程中的BOLD反应。

DESCRIPTION (provided by applicant): Attention alters the way that incoming sensory information is processed in order to optimize behavior. Determining how attention influences the way that information is represented throughout the brain is a core problem in sensory neuroscience. This issue has practical consequences as well, because attention-related disorders can severely affect learning and behavior. We propose to investigate how attention changes tuning for a broad range of structural and semantic features across the entire human brain. To address this issues we propose to use functional MRI to record blood-oxygen level-dependent (BOLD) signals while humans search for specific object or action categories (e.g., "Humans" or "Vehicles") in natural movies. We will then use an innovative voxel-wise modeling framework to characterize how attention changes tuning for hundreds of structural and semantic features. This framework will allow us to separately characterize attentional influences on response baseline, response gain and tuning. The proposal consists of two broad Aims. Aim 1 focuses on how attention changes the way that objects and actions are represented in the brain. Aim 2 addresses the computational principles that govern attentional tuning changes. These experiments will provide crucial information for understanding how the brain dynamically changes representations to optimize behavior during natural vision, and it will provide the first quantitative structural and semantic models that accurately predict BOLD responses during natural visual search.