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Situated Neural Representations: Solving the Problems of Content.

Gualtiero Piccinini1

  • 1Department of Philosophy and Center for Neurodynamics, University of Missouri-St. Louis, St. Louis, MO, United States.

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Summary
This summary is machine-generated.

Situated cognition, emphasizing embodiment and interaction, is essential for developing neural representations. This neurocomputational account shows how situatedness is fundamental to understanding cognitive processes and building artificial intelligence.

Keywords:
affectembeddednessembodimentenactivismneural computationneural representationsemantic contentsituated cognition

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Area of Science:

  • Cognitive Science
  • Neuroscience
  • Artificial Intelligence

Background:

  • Situated approaches posit cognition as embodied, embedded, enactive, and affective.
  • These are often contrasted with computational and representational theories of cognition.
  • The relationship between situatedness and neural representation remains a key debate.

Purpose of the Study:

  • To propose a neurocomputational account of cognition integrating situatedness and neural representation.
  • To demonstrate that situatedness is not opposed to, but rather required by, neural representation.
  • To explore the implications for constructing artificial cognitive systems.

Main Methods:

  • Development of a neurocomputational model emphasizing neural representations.
  • Argumentation for the necessity of embodiment, embeddedness, enaction, and affect in constructing representations.
  • Analysis of how situated interaction shapes neural representations and computations.

Main Results:

  • Situatedness is fundamental for constructing neural representations with original semantic content.
  • Embodied and embedded systems allow for coordinated neural vehicles and content processing.
  • This framework explains how representations can be causally efficacious, determinate, represent distal stimuli, and misrepresent.

Conclusions:

  • Neural representation and situatedness are deeply intertwined, not opposing concepts.
  • A satisfactory account of neural representation requires situated cognitive systems.
  • The proposed model offers insights for developing artificial cognitive capacities.