The neural representation and transformation of color in human visual cortex

人类视觉皮层颜色的神经表征和转换

• 批准号: 8273521
• 负责人: DAVID J HEEGER
• 金额: $ 38.5万
• 依托单位: NEW YORK UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-05-01 至 2015-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8273521
• 关键词: 3-Dimensional; Amblyopia; Appearance; Area; Behavioral; Biological Models; Brain; Cognitive; Color; Color Perception; Complex; Computer Simulation; Data Analyses; Dependence; Discrimination; Elements; Face; Functional Magnetic Resonance Imaging; Human; Illusions; Linear Regressions; Measurement; Measures; Methods; Modality; Modeling; Motion; Motor; Movement; Nature; Neurons; Pattern; Population; Positioning Attribute; Principal Component Analysis; Process; Protocols documentation; Psychophysiology; Research; Retinal; Retinal Cone; Retinal Diseases; Sensory; Series; Signal Transduction; Staging; Stimulus; Sum; Techniques; Testing; Translations; Visual; Visual Agnosias; Visual Cortex; Visual Illusions; Visual Perception; Visual impairment; Visual system structure; Weight; Work; base; color category; experience; extrastriate visual cortex; insight; neural patterning; novel; object recognition; relating to nervous system; research study; response; restoration; sensory stimulus; vector; visual information

DESCRIPTION (provided by applicant): The representation of any stimulus can be seen as a unique and distributed pattern of activity in a large population of neurons. These neural representations are thought to undergo a series of transformations across processing stages in visual cortex, and to depend on behavioral demands. The nature of these transformations reveals important insights into the computational mechanisms underlying the formation of behaviorally meaningful neural representations from incoming sensory signals. In this proposal, the focus is on measuring the neural representations and characterizing the transformations for a specific visual modality: color. The representation of color takes on many different forms. For example, humans discriminate between many thousands of hues but use only a handful of discrete color categories. This makes color an ideal candidate to investigate distributed neural representations. The novel empirical and theoretical approaches in the current proposal aim to significantly advance understanding of 1) how the human visual system represents color, 2) how this distributed neural representation is transformed across the hierarchy of visual cortical areas 3) the dependence of these representations on behavioral demands, and 4) the dependence on context. Aim 1 experiments will test the hypothesis that the neural representation of color is transformed as chromatic signals ascend the visual system. Neural color spaces will be derived from functional magnetic resonance imaging (fMRI) measurements, using novel experimental protocols and multivariate data analysis techniques. These neural color spaces will be compared with perceptual color spaces derived from psychophysical measurements of color discrimination and categorization. Aim 1 experiments will also test the hypothesis that neural representations of color depend on behavioral demands. The proposed experiments will distinguish between two specific computational hypotheses: 1) that neural color spaces change for different behavioral tasks, indicating a change in the underlying selectivity and tuning of the neurons, versus 2) a (possibly selective) increase in response gain, with no evidence for a change in the color space. Aim 2 experiments will test the hypothesize that changes in color perception, due to a dramatic visual illusion, are correlated with corresponding shifts in the underlying neural representation, and that the extent of the shift in the neural representation varies between visual areas, depending on the neural color space in each visual area. Ultimately, color provides a model for more complex neural representations (e.g., those underlying face and object recognition, control of movement, etc.) and the findings will provide general insights about distributed neural processes and representations. Consequently, the proposed research will provide information about how the brain transforms an incoming set of signals (of any modality) into a set of meaningful representations that subserve a multitude of tasks. PUBLIC HEALTH RELEVANCE: The current proposal builds on previous work to study how the brain represents visual information, the computations the brain performs to transform representations of visual information, and the relationship between neural activity and visual perception. Consequently, the outlined approach will be of great benefit in understanding amblyopia, low vision, and aperceptive visual agnosias, as the methods developed in the proposal can be used to characterize distributed neural representations of other stimulus features besides color including, for example, contrast, orientation, depth, motion, etc. In addition, these methods for characterizing large-scale, distributed neural representations, non-invasively in the human brain, will be helpful for evaluating the efficacy of any therapy for visio restoration, whether it be a therapy for cortical visual deficits in amblyopia or a retinal prostheis for degenerative retinal diseases.

描述（由申请人提供）：在大量神经元中，任何刺激的表示都可以看作是一种独特的活动模式。人们认为这些神经表示会在视觉皮层中的处理阶段进行一系列转变，并依赖行为需求。这些转换的性质揭示了对从传入的感觉信号形成具有行为意义的神经表示形成的计算机制的重要见解。在此提案中，重点是测量神经表示并表征特定视觉方式的转换：颜色。颜色的表示采用了许多不同的形式。例如，人类区分了数千种色调，但仅使用少数离散的颜色类别。这使得颜色成为研究分布式神经表示的理想候选者。 当前建议中的新型经验和理论方法旨在显着提高人们对人类视觉系统的理解，2）如何在视觉皮质区域的层次结构中转化这种分布式神经表示形式3）这些表示对行为需求的依赖性以及4）4）对上下文的依赖性。 AIM 1实验将检验以下假设，即颜色的神经表示会随着视觉系统上升而变化。神经颜色空间将使用新型的实验方案和多元数据分析技术源自功能磁共振成像（fMRI）测量。这些神经色空间将与从颜色歧视和分类的心理物理测量中得出的感知颜色空间进行比较。 AIM 1实验还将检验以下假设：颜色的神经表示取决于行为需求。提出的实验将区分两个特定的计算假设：1）不同行为任务的神经颜色空间变化，表明基本选择性的变化和调整 神经元对2）A（可能选择性）的响应增益增加，没有证据表明颜色空间发生变化。 AIM 2实验将测试以下假设，即由于剧烈的视觉幻觉而导致的颜色感知的变化与基础神经表示的相应变化相关，并且神经表示的变化程度因每个视觉区域的神经颜色空间而变化。 最终，颜色为更复杂的神经表示（例如那些基础的面部和对象识别，动作的控制等）提供了模型，这些发现将提供有关分布式神经过程和表示形式的一般见解。因此，拟议的研究将提供有关大脑如何将一组传入的信号（任何模式）转换为一组有意义的表示的信息，这些信号将予以负担。 公共卫生相关性：当前的提案基于先前的工作，以研究大脑如何代表视觉信息，大脑执行的计算以转化视觉信息的表示以及神经活动与视觉感知之间的关系。因此，概述的方法将在理解弱点，低视力和感知性的视觉敏锐度上具有很大的好处评估任何治疗疗法的疗效，无论是弱视的皮质视觉缺陷的疗法还是视网膜视网膜视网膜疾病的疗法。