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Published on: August 1, 2017
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1Department of Psychology, Université du Québec à Montréal, Montréal (Québec) H3C 3P8, Canada; Department of Electronics and Computer Science, University of Southampton, SouthamptonSO17 1TW, UK. harnad@soton.ac.uk.
Neural coding is criticized for implying a homuncular decoder. However, complex causal throughput, as suggested by Turing, offers a more accurate framework for understanding neural processes, distinct from the symbol grounding problem.
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Area of Science:
- Neuroscience
- Philosophy of Mind
- Cognitive Science
Background:
- The concept of neural coding faces criticism for its homuncular implications, suggesting neural signals require a "decoder."
- This "dualistic" view implies an internal entity must interpret neural information, which is problematic.
Purpose of the Study:
- To re-evaluate the metaphor of neural coding in light of criticisms.
- To propose an alternative framework for understanding neural signal processing.
- To clarify the relationship between neural coding and the symbol grounding problem.
Main Methods:
- Philosophical analysis of the concept of neural coding.
- Examination of Alan Turing's contributions to computation and information processing.
- Distinguishing neural coding from the symbol grounding problem.
Main Results:
- The notion of neural coding, as traditionally understood, is critiqued for its homuncular assumptions.
- An alternative perspective focusing on complex, interactive causal throughput is supported.
- Turing's work provides a precedent for understanding information processing without explicit decoding.
Conclusions:
- The metaphor of neural coding may be misleading and should be reconsidered.
- Complex causal throughput offers a more robust framework for neural processing.
- Neural coding is largely irrelevant to the symbol grounding problem.

