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Stable and variable affordances are both automatic and flexible.

Anna M Borghi1, Lucia Riggio2

  • 1Department of Psychology, University of Bologna and Institute of Cognitive Sciences and Technologies, Italian National Research Council Rome, Italy.

Frontiers in Human Neuroscience
|July 8, 2015
PubMed
Summary
This summary is machine-generated.

Object observation automatically evokes motor affordances, but this activation is flexibly modulated by task and context. Automaticity and flexibility coexist, with top-down processes selecting relevant motor information.

Keywords:
affordancesautomaticitycanonical neuronsembodied cognitiongraspinglanguage comprehensionmirror neuronstools

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Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Human-Computer Interaction

Background:

  • Object perception automatically elicits motor affordances.
  • The automaticity of this motor activation has been recently debated.
  • Evidence suggests affordance activation is modulated by task and context.

Purpose of the Study:

  • To review evidence on automaticity vs. flexibility of affordance activation.
  • To investigate how task and context influence motor information.
  • To reconcile seemingly conflicting findings on affordance processing.

Main Methods:

  • Review of recent empirical data on object affordances.
  • Analysis of studies examining task and contextual modulation.
  • Theoretical integration of automatic and flexible processing models.

Main Results:

  • Objects automatically elicit multiple affordances.
  • Top-down processes select affordances based on behavioral goals.
  • Task and context act as filters, influencing affordance selection.
  • Language processing of objects also involves affordances, with similarities and differences to visual processing.

Conclusions:

  • Automaticity and flexibility of affordances are not mutually exclusive.
  • Top-down control flexibly selects appropriate motor programs.
  • The distinction between stable and variable affordances explains these effects.
  • Understanding affordances is key to human-object interaction and language processing.