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Related Concept Videos

The Representativeness Heuristic02:13

The Representativeness Heuristic

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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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 categorization, a person will feel...

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Related Experiment Video

Updated: May 8, 2026

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms
07:31

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Published on: February 8, 2019

Reaction time for object categorization is predicted by representational distance.

Thomas A Carlson1, J Brendan Ritchie, Nikolaus Kriegeskorte

  • 1Macquarie University, Sydney, Australia.

Journal of Cognitive Neuroscience
|September 5, 2013
PubMed
Summary
This summary is machine-generated.

The brain

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Computational Neuroscience

Background:

  • The inferior temporal cortex (IT) holds object representations.
  • Object representations cluster by category (e.g., animate/inanimate) in IT's activation space.
  • The relationship between neural representation and decision-making is not fully understood.

Purpose of the Study:

  • To investigate if the representational boundary between object categories in IT activation space acts as a decision boundary.
  • To link neural representations of objects to behavioral categorization decisions.

Main Methods:

  • Multivariate pattern analysis (MVPA) of neural activity in the inferior temporal cortex (IT).
  • Analysis of behavioral reaction times (RTs) for object categorization tasks.
  • Modeling decision-making processes based on representational geometry.

Main Results:

  • Representational boundaries in IT activation space align with behavioral categorization.
  • Behavioral reaction times are accurately predicted by the representational geometry.
  • The formation of internal object representations is integral to categorization decisions.

Conclusions:

  • The spatial arrangement of neural representations in IT directly informs categorization decisions.
  • Decision-making models can incorporate representational structure for better predictions.
  • Neural representations are not just passive information storage but actively shape cognitive choices.