Defining the neural correlates of ensemble representation

定义集成表示的神经相关性

• 批准号: 8423082
• 负责人: Jason Marc Haberman
• 金额: $ 5.22万
• 依托单位: HARVARD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-02-01 至 2015-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8423082
• 关键词: Address; Affect; Afterimage; Agnosia; Area; Behavioral; Brain; Brain Part; Characteristics; Classification; Clinical Treatment; Code; Complex; Crowding; Data; Elements; Event; Exposure to; Face; Functional Magnetic Resonance Imaging; Human; Image; Imaging Techniques; Individual; Intuition; Lead; Left; Measures; Mediating; Motion; Nature; Pattern; Perception; Play; Positioning Attribute; Process; Property; Psychophysics; Resolution; Retina; Role; Signal Transduction; Stimulus; Techniques; Testing; Texture; Time; Vision; Visual; Visual Perception; Visual system structure; Work; abstracting; blood oxygenation level dependent response; coping mechanism; cost; design; detector; insight; neuroimaging; novel; object recognition; relating to nervous system; research study; segregation; statistics; visual information

DESCRIPTION (provided by applicant): Defining the neural correlates of ensemble representation in humans are sensitive to the summary statistics of complex scenes. The visual system readily extracts summary statistical representations across a host of visual domains, including orientation, direction of motion, size, position, and expression, and can do so efficiently and implicitly. Summary statistical extraction, or ensemble coding, operates over both space and time, and shows sensitivity to the average, the range, and even the variance of sets of objects. Despite the seeming ubiquitous and fundamental nature of ensemble representations, the precise level at which ensembles are extracted remains unknown, and there has been no examination of the neural correlates of this process. These issues will be explored using low-level behavioral psychophysics and functional neuroimaging techniques. The proposed experiments will delineate elements key to understanding the role summary statistics play in vision, including: a) does the visual system adapt to ensemble stimuli (e.g., sets of oriented gabor patches, sets of faces) in the same way that it adapts to singletons (e.g., a single oriented gabor patch, a single face)? b) What parts of the brain play a role in calculating/extracting summary statistical information? The broader objective of the proposed studies is to develop expertise in functional magnetic resonance imaging techniques, ranging from design (e.g., block, fast event-related) to analysis (e.g., deconvolution, pattern classification).

描述（由申请人提供）：定义人类对复杂场景的汇总统计敏感的集成表示的神经关联。视觉系统可以很容易地从一系列视觉域（包括方向、运动方向、大小、位置和表情）中提取汇总的统计表示，并且可以高效和隐式地完成这些工作。摘要统计提取或集成编码可以在空间和时间上操作，并显示出对对象集的平均值、范围甚至方差的敏感性。尽管集合表示似乎无处不在，具有基本的性质，但提取集合的精确水平仍然未知，并且没有对该过程的神经相关性进行检查。这些问题将探讨使用低级行为心理物理学和功能神经成像技术。拟议的实验将描述理解汇总统计在视觉中所起作用的关键要素，包括：a)视觉系统适应整体刺激（例如，一组定向gabor补丁，一组面孔）的方式是否与适应单个刺激（例如，一个定向gabor补丁，一张脸）的方式相同？b)大脑的哪些部分在计算/提取汇总统计信息中起作用？拟议研究的更广泛目标是发展功能磁共振成像技术的专业知识，范围从设计（例如，块，快速事件相关）到分析（例如，反卷积，模式分类）。