Visual pattern representation in extrastriate cortex

纹外皮层的视觉模式表征

• 批准号: 8828693
• 负责人: J ANTHONY MOVSHON
• 金额: $ 38.1万
• 依托单位: NEW YORK UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-03-01 至 2016-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8828693
• 关键词: Accounting; Affect; Agnosia; Ally; Animals; Architecture; Area; Behavior; Behavioral; Biology; Blindness; Brain Injuries; Cells; Data; Disease; Dorsal; Elements; Event; Frequencies; Functional Magnetic Resonance Imaging; Goals; Health; Human; Image; Judgment; Link; Macaca; Measurement; Measures; Memory; Methods; Modeling; Motion; Motivation; Nervous system structure; Neurons; Noise; Outcome; Output; Pattern; Perception; Performance; Population; Primates; Probability; Process; Property; Psychometrics; Recovery; Research; Role; Sensory; Signal Transduction; Space Perception; Staging; Stimulus; Stream; Structure; Techniques; Texture; V1 neuron; V2 neuron; Vision; Vision Disorders; Visual; Visual Cortex; Visual Fields; Work; area MT; area V1; area V2; area striata; awake; blood oxygenation level dependent response; design; disability; experience; extrastriate visual cortex; neural circuit; neuronal circuitry; novel; operation; orientation selectivity; relating to nervous system; research study; response; spatial integration; success; tool

DESCRIPTION (provided by applicant): The goal of this research is to discover the cortical computations embodied in the responses of neurons in ventral visual area V2. Since V2 is heavily dependent on input from V1 for its visual responsiveness, we will develop a two-stage model, in which responses are constructed from a suitable combination of V1 afferents, with the design of each stage following a common canonical form. This model is intended to account for the visual response properties of neurons as economically as possible, while not necessarily reflecting the details of neuronal circuitry. This simplicity is deliberate, as it will allow the mdel to be fit to data recorded from single neurons, and, when assembled into a population, to predict perceptual capabilities. The motivation for the structure of the model, and our confidence in its success, comes from the convergence of three strands of previous work: (1) we have developed, fit, and validated a similar two-stage model for neuronal responses in area MT, a dorsal stream area which also receives primary afferent drive from area V1; (2) we have developed a two-stage model for visual texture representation that captures perceptually recognizable structures of natural images using spatial integration regions matched in size to those of V2 cells. We've shown that images synthesized to have matching model responses are indistinguishable to human observers; and (3) we've obtained preliminary data indicating that most of V2 cells respond more vigorously to synthetic texture stimuli than to spectrally matched noise stimuli, whereas V1 cells do not. The research is divided into three parts. First, we will gather electrophysiological data to dissect those model-generated features that underlie the increased responsiveness of V2 to texture stimuli. We will, in parallel, gather evidence for the increased responsiveness using fMRI, which will allow us to compare simultaneously measured responses averaged over neural populations in V1 and V2. Second, we will develop a physiologically plausible instantiation of the texture model and develop the methods to fit it to data from single neurons. Finally, we will link the novel functional response properties we have discovered to perception by simultaneously measuring neuronal responses and perceptual judgments in awake behaving macaques. To explore sensitivity to naturalistic features, we will relate psychometric and single-neuron neurometric functions, and use choice probability to link responses to behavioral performance.

描述（由申请人提供）：本研究的目标是发现腹侧视觉区V2神经元反应中包含的皮质计算。由于V2的视觉反应严重依赖于V1的输入，因此我们将开发一个两阶段模型，其中反应是由V1传入的适当组合构建的，每个阶段的设计都遵循一个共同的规范形式。该模型旨在尽可能经济地解释神经元的视觉响应特性，而不一定反映神经元回路的细节。这种简单性是故意的，因为它将允许模型拟合从单个神经元记录的数据，并且当组装成群体时，预测感知能力。该模型的结构的动机，以及我们对其成功的信心，来自于以前工作的三个方面的融合：（1）我们已经开发、拟合和验证了MT区神经元反应的类似两阶段模型，MT区是一个背流区，也接受来自V1区的初级传入驱动;（2）我们已经开发了一个两阶段的视觉纹理表示模型，该模型使用与V2细胞大小匹配的空间积分区域来捕获自然图像的感知可识别结构。我们已经证明，合成的图像具有匹配的模型响应是无法区分的人类观察者;（3）我们已经获得的初步数据表明，大多数V2细胞更积极地响应合成纹理刺激比光谱匹配的噪声刺激，而V1细胞没有。本研究分为三个部分。首先，我们将收集电生理数据来剖析那些模型生成的功能，这些功能是V2对纹理刺激的反应性增加的基础。同时，我们将利用功能磁共振成像收集反应性增加的证据，这将使我们能够比较同时测量的V1和V2神经群体的平均反应。其次，我们将开发一个生理上合理的纹理模型的实例，并开发方法来适应来自单个神经元的数据。最后，我们将链接的新的功能反应特性，我们已经发现的知觉，同时测量神经元的反应和知觉判断清醒的行为猕猴。为了探索对自然特征的敏感性，我们将把心理测量和单神经元神经测量功能联系起来，并使用选择概率将反应与行为表现联系起来。