How Does Normalization Regulate Visual Competition?

标准化如何规范视觉竞争？

• 批准号: 10594246
• 负责人: SAM LING
• 金额: $ 41.25万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10594246
• 关键词: Attention; Automobile Driving; Bioenergetics; Brain; Characteristics; Clinical Treatment; Code; Computer Models; Consensus; Development; Diagnostic tests; Disease; Equilibrium; Event; Foundations; Frequencies; Functional Magnetic Resonance Imaging; Funding; Goals; Human; Intervention; Knowledge; Measures; Methods; Modeling; Nature; Neurosciences; Perception; Play; Population; Population Control; Process; Property; Public Health; Regulation; Research Personnel; Role; Sensory; Shapes; Stimulus; Techniques; Testing; Vision; Visual; Visual Cortex; Visual System; Visual attention; Work; attentional modulation; cognitive process; cost; diagnostic tool; experimental study; flexibility; innovation; neural; neuroimaging; neuromechanism; neuroregulation; novel; preference; prevent; response; segregation; selective attention; signal processing; theories; tool; visual processing

PROJECT SUMMARY/ABSTRACT How does the human visual system regulate competing sensory information? Prevailing theories propose that a computation known as divisive normalization plays a key role in governing neural competition. Normalization is considered a canonical neural computation, potentially driving responses throughout the brain. Interestingly, there is evidence to suggest that normalization’s pervasive role relies on an exquisite tuning to stimulus features, such as orientation and spatial frequency, but this feature-selective nature of normalization is surprisingly understudied, particularly in humans. Our long-term goal is to understand the neural mechanisms supporting vision across the visual hierarchy in humans, and to characterize how they flexibly change with selective attention. The aim of this proposal is to employ state-of-the-art functional neuroimaging techniques and analyses to shed light on the tuning characteristics that allow normalization to control population responses within human visual cortex, and to understand how normalization can support selective attention. We approach the problem by first characterizing the selective properties of normalization within early visual cortex during normal, passive, scene viewing. We will then assess the unifying potential of models based on divisive normalization, examining the role that normalization plays in regulating competition via spatially- directed and feature-based attention. By revealing the role played by tuned normalization within human visual cortex, these studies will provide the necessary framework for the development of diagnostic tools and treatments for clinical disorders that involve deficits in central visual processing.

项目概要/摘要 人类视觉系统如何调节竞争的感官信息？流行的理论认为 称为除法归一化的计算在控制神经竞争中发挥着关键作用。正常化 被认为是一种规范的神经计算，可能驱动整个大脑的反应。有趣的是， 有证据表明，正常化的普遍作用依赖于对刺激的精确调整 特征，例如方向和空间频率，但归一化的特征选择性性质是 令人惊讶的是，人们对此的研究却很少，尤其是在人类身上。我们的长期目标是了解神经机制 支持人类整个视觉层次的视觉，并描述它们如何灵活地变化 选择性注意。该提案的目的是采用最先进的功能神经影像技术 并进行分析以阐明允许标准化控制人口的调整特征 人类视觉皮层内的反应，并了解正常化如何支持选择性注意力。 我们通过首先表征早期视觉标准化的选择性特性来解决这个问题 正常、被动、场景观看期间的皮层。然后，我们将评估模型的统一潜力 分裂标准化，通过空间检验标准化在调节竞争中所起的作用 定向和基于特征的注意力。通过揭示调整标准化在人类视觉中所扮演的角色 皮层，这些研究将为诊断工具的开发提供必要的框架 治疗涉及中枢视觉处理缺陷的临床疾病。