Applications of Capacity Analysis into Social Cognition Domain

Alla Yankouskaya, Jie Sui, Zargol Moradi, Pia Rotshtein, Glyn Humphreys

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

We reviewed three studies where we investigated the effects of social factors (race, in-group and self-biases) on perceptual processes using capacity analysis. Specifically, we demonstrate how the utility of processing efficiency can be used to quantify the effects of social and motivational biases (i.e., race bias, in-group bias, self-bias, and monetary reward bias) on visual perception. Contrasting to previous studies where the capacity measures were employed with double factorial experimental design, these three studies in social biases provide a new application of the capacity framework by combining the divided attention task with a recently developed associative learning task. We found that social biases enhance integration of information by modulating perceptual processing, and the modulatory effects reflect increases in processing efficiency during information processing. We suggest that increasing processing efficiency can be sourced: (i) from learned configural properties of perceptual objects (such as facial configuration), (ii) stronger perceptual and conceptual representations for objects associated with self or high reward, and (iii) currently salient social categorization (e.g., team membership). Future directions in applying the capacity framework to issues in social cognition are discussed.
Original languageEnglish
Title of host publicationSystems Factorial Technology
Subtitle of host publicationA Theory Driven Methodology for the Identification of Perceptual and Cognitive Mechanisms
EditorsDaniel R. Little, Nicholas Altieri, Mario Fific, Cheng-Ta Yang
PublisherAcademic Press
Chapter18
Pages381-400
Number of pages20
ISBN (Print)978-0-12-804315-8
DOIs
Publication statusPublished - 2017

Keywords

  • capacity processing
  • own-race effect
  • self-biases
  • reward-biases
  • in-group biases

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