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Introduction to Cognitive Psychology01:20

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Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
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The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
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Predictive processing: Shedding light on the computational processes underlying motivated behavior.

Lieke L F van Lieshout1, Zhaoqi Zhang1, Karl J Friston2

  • 1Donders institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlandslieke.vanlieshout@donders.ru.nl claire.zhang@donders.ru.nl harold.bekkering@donders.ru.nlhttps://www.ru.nl/en/people/lieshout-l-vanhttps://www.ru.nl/en/people/zhang-z-clairehttps://www.ru.nl/en/people/bekkering-h.

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Summary
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This study integrates predictive processing with motivation, breaking down expected free energy into intrinsic (epistemic) and extrinsic (instrumental) values to explain adaptive behavior and environmental interaction.

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Area of Science:

  • Computational Neuroscience
  • Cognitive Science
  • Behavioral Economics

Background:

  • Motivation research traditionally focuses on drives and rewards.
  • Predictive processing offers a computational framework for understanding perception and action.
  • Bridging these fields can illuminate the mechanisms of motivated behavior.

Purpose of the Study:

  • To integrate the predictive processing framework with theories of motivation.
  • To computationally model motivated behavior by decomposing expected free energy.
  • To explore how intrinsic and extrinsic values guide environmental interaction.

Main Methods:

  • Decomposition of expected free energy into its constituent value components.
  • Application of predictive processing principles to motivational constructs.
  • Theoretical modeling of adaptive behavior.

Main Results:

  • Expected free energy can be meaningfully decomposed into epistemic and instrumental affordances.
  • This decomposition provides a computational basis for understanding intrinsic and extrinsic motivation.
  • The framework offers insights into how individuals adaptively interact with their environment.

Conclusions:

  • The predictive processing framework offers a powerful lens for understanding motivation.
  • Decomposing expected free energy into intrinsic and extrinsic values advances computational models of behavior.
  • This approach enhances our understanding of adaptive environmental engagement.