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Creating Objects and Object Categories for Studying Perception and Perceptual Learning
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Contrasting effects of feature-based statistics on the categorisation and basic-level identification of visual

Kirsten I Taylor1, Barry J Devereux, Kadia Acres

  • 1Dept. of Experimental Psychology, University of Cambridge, United Kingdom. ktaylor@uhbs.ch

Cognition
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Summary

Task demands influence conceptual processing. Distinctive features aid naming, while shared features facilitate domain decisions, unifying feature-based theories.

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Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Linguistics

Background:

  • Conceptual representations are crucial for cognition.
  • Debate exists on how concept meanings are represented (e.g., distinctive vs. shared features).
  • Feature co-occurrence also plays a role in conceptual processing.

Purpose of the Study:

  • To unify disparate theoretical positions on conceptual representation.
  • To investigate the influence of task demands on concept processing.
  • To determine how feature distinctiveness, co-occurrence, and task demands interact.

Main Methods:

  • Two experiments using large-scale regression designs with visual objects.
  • Experiment 1: Basic-level naming task (relies on distinctive features).
  • Experiment 2: Domain decision task (relies on shared features).
  • Mixed-effects models analyzed performance based on various variables.

Main Results:

  • Distinctive features and high distinctiveness correlation facilitated basic-level naming.
  • Shared features and high sharedness correlation sped up domain decisions.
  • Both feature statistics (distinctiveness, co-occurrence) and task demands impact processing.

Conclusions:

  • Task demands dynamically shape conceptual processing alongside feature statistics.
  • A unified account explains conceptual processing by integrating feature properties and task context.
  • Findings highlight the flexible nature of conceptual representation in the human mind.