Fodor and Pylyshyn’s Critique of Connectionism and the Brain as Basis of the Mind

Abstract To this day there is no satisfactory answer to the question how mental patterns correspond to physical states of our brain. For more than six decades, progress has been held up by the logjam between two traditions, one inspired by neuroscience, the other by digital computing. This logjam is well illuminated by Fodor and Pylyshyn’s article of 1988, which is mainly devoted to a critique of what they call Connectionism, but also lays bare weaknesses of the Classical approach which they defend. As recent machine learning breakthroughs may be expected to shed new light on the issue, it seems time to arrive at a synthesis of the connectionist neural approach and the classical stance based on symbol processing. I will present and discuss an attempt at such synthesis in the form of structured, self-organized neural networks.

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Publication Details

Journal
Human Arenas
Published
2024-11-05
DOI
https://doi.org/10.1007/s42087-024-00452-z
Citations
1
Primary Topic
Neural dynamics and brain function
Type
article
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0.00
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article

Fodor and Pylyshyn’s Critique of Connectionism and the Brain as Basis of the Mind

Christoph von der Malsburg
1 citations
Human Arenas
Neural dynamics and brain function
article

Fodor and Pylyshyn’s Critique of Connectionism and the Brain as Basis of the Mind

Christoph von der Malsburg
article en
1 citations

Abstract

Abstract To this day there is no satisfactory answer to the question how mental patterns correspond to physical states of our brain. For more than six decades, progress has been held up by the logjam between two traditions, one inspired by neuroscience, the other by digital computing. This logjam is well illuminated by Fodor and Pylyshyn’s article of 1988, which is mainly devoted to a critique of what they call Connectionism, but also lays bare weaknesses of the Classical approach which they defend. As recent machine learning breakthroughs may be expected to shed new light on the issue, it seems time to arrive at a synthesis of the connectionist neural approach and the classical stance based on symbol processing. I will present and discuss an attempt at such synthesis in the form of structured, self-organized neural networks.

Human ArenasVol. 8(3)
SIB Swiss Institute of Bioinformatics (CH), Frankfurt Institute for Advanced Studies (DE), Institute for Biomedical Engineering (CH)
Openalex Percentile: Top 80%
Neural dynamics and brain function
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