How Does Normalization Regulate Visual Competition?

标准化如何规范视觉竞争？

• 批准号: 10164789
• 负责人: SAM LING
• 金额: $ 39.65万
• 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 2023-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10164789
• 关键词: Attention; Automobile Driving; Awareness; Binocular Vision; Bioenergetics; Brain; Characteristics; Chronic; Clinical Treatment; Computer Models; Data; Development; Diagnostic; Diagnostic tests; Disease; Environment; Equilibrium; Event; Eye; Feedback; Foundations; Functional Magnetic Resonance Imaging; Goals; Human; Intervention; Light; Measures; Modeling; Nature; Perception; Play; Population Control; Process; Property; Public Health; Regulation; Role; Sensory; Stimulus; Systems Analysis; Techniques; Testing; Visual; Visual Cortex; Visual Perception; Visual attention; Visual system structure; Work; attentional modulation; base; cognitive system; cost; experimental study; extrastriate visual cortex; neuroimaging; neuroregulation; novel; relating to nervous system; response; selective attention; signal processing; theories; tool; visual processing

PROJECT SUMMARY/ABSTRACT How does the visual system regulate competing sensory information? Recent 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 neural and cognitive system. Interestingly, there is evidence to suggest that normalization's pervasive role relies on an exquisite tuning to stimulus features, such as orientation, but this feature-selective nature of normalization is surprisingly understudied, particularly in humans. The goal of the proposed work 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 this form of normalization can support functions as diverse as attentional selection and interocular competition. 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 of feature-tuned normalization in regulating competition in apparently unrelated settings, namely those involving selective attention and interocular competition. By revealing the properties of tuned normalization within human visual cortex, and characterizing the role of normalization in attentional feedback and competition at large, 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.

项目总结/摘要 视觉系统如何调节相互竞争的感觉信息？最近的理论认为， 被称为分裂归一化的计算在控制神经竞争中起着关键作用。归一化 被认为是一种规范的神经计算，可能会驱动整个神经和认知的反应 系统有趣的是，有证据表明，正常化的普遍作用依赖于一个精致的 调整刺激特征，如方向，但这种特征选择性的正常化是令人惊讶的 研究不足，尤其是人类。拟议工作的目标是采用最先进的功能 神经成像技术和分析，以阐明调谐特性，使正常化， 控制人类视觉皮层内的群体反应，并了解这种形式的正常化如何 支持功能多样的注意力选择和眼间竞争。我们处理这个问题的方法是 首先表征在正常，被动， 现场观看。然后，我们将评估基于分裂规范化的模型的统一潜力， 特征调整的正常化在调节明显不相关的环境中的竞争中的作用，即那些 涉及选择性注意和眼间竞争。通过揭示调谐归一化的性质， 在人类视觉皮层，并表征正常化在注意力反馈和竞争中的作用 总的来说，这些研究将为开发诊断工具提供必要的框架， 涉及中央视觉处理缺陷的临床疾病的治疗。