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相关概念视频

The Representativeness Heuristic02:13

The Representativeness Heuristic

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The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
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Schemata01:17

Schemata

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A schema is a mental construct that organizes related concepts, allowing the brain to process information efficiently. Upon activation, schemata facilitate assumptions about people or objects.
Two types of schemata are:
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Stereotype Content Model02:16

Stereotype Content Model

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The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
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Schemas01:42

Schemas

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A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.
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Concepts and Prototypes01:24

Concepts and Prototypes

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The human nervous system handles vast amounts of information by translating sensory stimuli into neural impulses, which the brain processes, creating thoughts expressed through language or stored as memories. The brain also synthesizes information from emotions and memories, which significantly influence thoughts and behaviors. This intricate process creates a comprehensive mental picture.
The brain organizes this information using concepts, which are mental categories grouping linguistic data,...
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Gestalt Principles of Perception01:21

Gestalt Principles of Perception

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Gestalt principles provide a framework for understanding how humans perceive objects as unified wholes within their context. These principles are essential in explaining the cognitive processes that make sense of complex visual stimuli by organizing them into coherent groups. One fundamental principle is proximity, which posits that objects located close to each other are perceived as a collective group. For instance, when dots are positioned near one another, the visual system interprets them...
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相关实验视频

Updated: Sep 11, 2025

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
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Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

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识别和描述与行为分类相关的场景表示.

Johannes J D Singer1,2, Agnessa Karapetian1,3, Martin N Hebart2,4,5

  • 1Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany.

Imaging neuroscience (Cambridge, Mass.)
|August 13, 2025
PubMed
概括
此摘要是机器生成的。

了解大脑如何识别场景是行为关键. 这项研究揭示了特定的大脑活动模式与场景识别任务有关,不同的神经表征支持不同的行为.

关键词:
解码的解码方法是功能磁力共振成像 (fMRI) 是一种感知性决策 - 感知性的决策场景感知 场景感知视觉特征 视觉特征 视觉特征 视觉特征

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Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms
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Experience is Instrumental in Tuning a Link Between Language and Cognition: Evidence from 6- to 7- Month-Old Infants' Object Categorization
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相关实验视频

Last Updated: Sep 11, 2025

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
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Creating Objects and Object Categories for Studying Perception and Perceptual Learning

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Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms
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科学领域:

  • 认知神经科学 认知神经科学
  • 神经成像是一种神经成像.
  • 视觉感知 视觉感知 视觉感知

背景情况:

  • 场景识别对于环境相互作用至关重要.
  • 人们越来越了解场景识别的神经基础,但其在任务中的行为相关性尚不清楚.

研究的目的:

  • 识别行为相关的场景表示.
  • 描述它们的视觉特征.
  • 检查这些表示的取决于任务的变化.

主要方法:

  • 在人类观看场景中的功能磁共振成像 (fMRI).
  • 从分类和歧视任务中将大脑反应与行为数据联系起来.
  • 使用深度神经网络来分析视觉特征.

主要成果:

  • 分类反应时间与不同腹部视觉流区域的特定场景大脑反应相关.
  • 中间深层神经网络层调解了场景表示与行为之间的联系.
  • 观察到相反的大脑行为相关性模式,这表明对错误对齐的任务的表示干扰.

结论:

  • 与行为相关的场景表示是依赖于任务的,并在腹部视觉流中空间分布.
  • 中级视觉特征有助于这些行为相关的表示.
  • 任务需求可以与神经表征保持一致或干扰神经表征,从而影响行为.