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Connectionism and psychoanalysis

D D Olds1

  • 1Columbia College of Physicians and Surgeons, New York.

Journal of the American Psychoanalytic Association
|January 1, 1994
PubMed
Summary
This summary is machine-generated.

Connectionist models, also known as neural net systems, are reshaping cognitive science by suggesting the brain may not rely on a central processor and that mind-brain dualism might be unnecessary.

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Area of Science:

  • Cognitive Science
  • Neuroscience
  • Computational Psychology

Background:

  • Connectionist or neural net systems are increasingly influential in understanding brain function.
  • These models offer new perspectives on perception, learning, and cognition.

Purpose of the Study:

  • To explore the implications of connectionist models for psychoanalytic theory.
  • To examine how computational models of the brain challenge traditional views of cognitive processes.

Main Methods:

  • Review of current connectionist and neural network models.
  • Analysis of the theoretical shifts in cognitive science prompted by these models.
  • Exploration of the philosophical implications for mind-brain dualism.

Main Results:

Related Experiment Videos

  • Connectionist models suggest a reduced reliance on a central processor in the brain.
  • These models highlight the potential for self-organizing processes in brain function.
  • The findings challenge the necessity of mind-brain dualism.

Conclusions:

  • Connectionist models provide a framework for reconceptualizing the mind-brain relationship.
  • Psychoanalytic theory may need to integrate insights from computational neuroscience.
  • The study suggests a move towards more integrated, non-dualistic models of the mind.