Neural Computations in Visual Cortex

视觉皮层的神经计算

• 批准号: 8678921
• 负责人: Jonathan D Victor
• 金额: $ 38.23万
• 依托单位: WEILL MEDICAL COLL OF CORNELL UNIV
• 依托单位国家: 美国
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-07-01 至 2016-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8678921
• 关键词: Accounting; Alzheimer' s Disease; Amblyopia; Architecture; Autistic Disorder; Behavior; Brain; Characteristics; Chronic Brain Injury; Complex; Developmental Process; Diagnosis; Entropy; Feedback; Funding; Goals; Image; Individual; Laboratories; Macaca; Measures; Modeling; Morbidity - disease rate; Nature; Neurons; Noise; Pathway interactions; Pattern; Perception; Perceptual disturbance; Play; Population; Process; Recurrence; Research; Role; Shapes; Stimulus; Stroke; Structure; Testing; Texture; V1 neuron; Vision; Visual; Visual Cortex; Visual Perception; Work; area striata; base; cell assembly; cognitive function; design; insight; luminance; meetings; millimeter; network models; relating to nervous system; response; spatiotemporal; statistics; success; tool; visual information

DESCRIPTION (provided by applicant): The goal of this research is to understand the nature of the computations performed by primary visual cortex (V1), and how these calculations are carried out. Even the most basic step in interpreting the visual world -- extracting local features such as lines and edges -- is a difficult computational problem: it must be carried out in the context of cluttered, complex, natural visual scenes; it must be carried out rapidly; and it must be carried out by neural hardware. The generally accepted view is that V1 acts primarily as a feedforward bank of filters, in which feedback and gain controls play a modulatory role. However, models constructed from simple analytically-convenient stimuli provide an incomplete account of responses to natural scenes. Since natural scenes have characteristics that traditional analytic stimuli lack, this observation implies that V1 neurons are sensitive to these distinguishing characteristics, namely, high-order statistics (HOS's). Based on several lines of evidence (including work from the previous funding period and studies in other laboratories), we hypothesize that this sensitivity to HOS's indicates that V1's basic design is that of a strongly recurrent network. In particular, we hypothesize that the characteristics that distinguish a strongly recurrent architecture from a feedforward or modulatory feedback architecture account for V1's ability to extract HOS's. To test these hypotheses, we focus on analyzing V1's responses to stimuli containing HOS's -- because they distinguish among these two contrasting pictures of V1, and because HOS's are precisely the statistical feature that distinguishes natural scenes from traditional analytic stimuli. In Aim 1, we determine the extent of sensitivity of V1 neurons to HOS's, explicitly studying both artificially- constructed stimuli and stimuli derived from natural scenes. In Aim 2, we determine whether dynamic formation of neural assemblies underlies the extraction of HOS's, by analyzing the statistics of multineuronal firing patterns. If successful, this work will provide fundamental insights into the design principles of V1, including how it exploits general features of cortical architecture to carry out the calculations necessary for vision, how sparse representations arise, and the functional significance of cortical neural "noise."

描述（由申请人提供）：本研究的目的是了解初级视觉皮层（V1）进行计算的本质，以及这些计算是如何进行的。即使是解释视觉世界的最基本步骤——提取局部特征，如线条和边缘——也是一个困难的计算问题：它必须在混乱、复杂、自然的视觉场景中进行；它必须迅速执行；它必须通过神经硬件来实现。普遍接受的观点是V1主要作为一个前馈滤波器库，其中反馈和增益控制起调节作用。然而，由简单的分析方便的刺激构建的模型提供了对自然场景反应的不完整描述。由于自然场景具有传统分析刺激所缺乏的特征，这一观察表明V1神经元对这些显著特征（即高阶统计量）很敏感。基于几条证据线（包括以前资助期的工作和其他实验室的研究），我们假设这种对居屋s的敏感性表明V1的基本设计是一个强循环网络。特别是，我们假设区分强循环架构与前馈或调制反馈架构的特征解释了V1提取HOS的能力。为了验证这些假设，我们重点分析了V1对含有HOS的刺激的反应——因为它们区分了V1的两幅对比图片，而且HOS正是区分自然场景与传统分析刺激的统计特征。在Aim 1中，我们确定了V1神经元对HOS的敏感性程度，明确研究了人工构建的刺激和来自自然场景的刺激。在Aim 2中，我们通过分析多神经元放电模式的统计数据，确定神经组合的动态形成是否构成HOS提取的基础。如果成功，这项工作将为V1的设计原则提供基本的见解，包括它如何利用皮质结构的一般特征来执行视觉所需的计算，稀疏表示是如何产生的，以及皮质神经“噪声”的功能意义。

项目成果

Contextual modulation of V1 receptive fields depends on their spatial symmetry.

• DOI: 10.1007/s10827-008-0107-5
• 发表时间: 2009-04
• 期刊: JOURNAL OF COMPUTATIONAL NEUROSCIENCE
• 影响因子: 1.2
• 作者: Sharpee, Tatyana O.;Victor, Jonathan D.
• 通讯作者: Victor, Jonathan D.

Visual processing of informative multipoint correlations arises primarily in V2.

信息多点相关性的视觉处理主要出现在V2中。

• DOI: 10.7554/elife.06604
• 发表时间: 2015-04-27
• 期刊: eLife
• 影响因子: 7.7
• 作者: Yu Y;Schmid AM;Victor JD
• 通讯作者: Victor JD

Dynamic programming algorithms for comparing multineuronal spike trains via cost-based metrics and alignments.

动态编程算法，用于通过基于成本的指标和对齐来比较多神经元尖峰序列。

• DOI: 10.1016/j.jneumeth.2006.11.001
• 发表时间: 2007
• 期刊: Journal of neuroscience methods
• 影响因子: 3
• 作者: Victor,JonathanD;Goldberg,DavidH;Gardner,Daniel
• 通讯作者: Gardner,Daniel

Approaches to Information-Theoretic Analysis of Neural Activity.

• DOI: 10.1162/biot.2006.1.3.302
• 发表时间: 2006-01-01
• 期刊: Biological theory
• 作者: Victor, Jonathan D

The processing of feature discontinuities for different cue types in primary visual cortex.

初级视觉皮层中不同提示类型的特征不连续性的处理。

• DOI: 10.1016/j.brainres.2008.08.029
• 发表时间: 2008
• 期刊: Brain research
• 影响因子: 2.9
• 作者: Schmid,AnitaM