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Noise, uncertainty, and interest: Predictive coding and cognitive penetration.

Jona Vance1, Dustin Stokes2

  • 1Department of Philosophy, Northern Arizona University, USA.

Consciousness and Cognition
|June 23, 2016
PubMed
Summary
This summary is machine-generated.

This study explores how predictive coding theories explain cognitive penetration, focusing on top-down effects in perception. It critiques the idea that cognitive penetration only occurs in noisy conditions.

Keywords:
AttentionCognitionCognitive penetrationDirectnessNoisePerceptionPrediction errorPredictive codingTheoretical interestUncertainty

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Area of Science:

  • Cognitive Science
  • Neuroscience
  • Philosophy of Mind

Background:

  • Predictive coding framework offers a model for perception and cognition.
  • Cognitive penetration describes how mental states can influence perceptual experience.
  • Existing theories struggle to fully integrate these concepts.

Purpose of the Study:

  • To clarify predictive coding's explanation of cognitive penetration.
  • To refine how predictive coding accounts for direct top-down effects on perception.
  • To critically evaluate claims linking cognitive penetration to perceptual noise.

Main Methods:

  • Conceptual analysis of predictive coding theories.
  • Examination of criteria for cognitive penetration.
  • Critique of specific theoretical claims regarding perceptual noise.

Main Results:

  • Predictive coding can explain genuine top-down causal effects on perception.
  • The framework can accommodate direct cognitive influences on perceptual experience.
  • The claim that cognitive penetration requires substantial noise is challenged.

Conclusions:

  • Predictive coding offers a robust framework for understanding cognitive penetration.
  • The directness of cognitive effects on perception is a key aspect.
  • Future research should consider broader applications beyond noisy perception.