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Are Neurocognitive Representations 'Small Cakes'?

Guest, Olivia and Martin, Andrea (2025) Are Neurocognitive Representations 'Small Cakes'? [Preprint]

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Abstract

In order to understand cognition, we often recruit analogies as building blocks of theories to aid us in this quest. One such attempt, originating in folklore and alchemy, is the homunculus: a miniature human who resides in the skull and performs cognition. Perhaps surprisingly, this appears indistinguishable from the implicit proposal of many neurocognitive theories, including that of the 'cognitive map,' which proposes a representational substrate for episodic memories and navigational capacities. In such 'small cakes' cases, neurocognitive representations are assumed to be meaningful and about the world, though it is wholly unclear who is reading them, how they are interpreted, and how they come to mean what they do. We analyze the 'small cakes' problem in neurocognitive theories (including, but not limited to, the cognitive map) and find that such an approach a) causes infinite regress in the explanatory chain, requiring a human-in-the-loop to resolve, and b) results in a computationally inert account of representation, providing neither a function nor a mechanism. We caution against a 'small cakes' theoretical practice across computational cognitive modelling, neuroscience, and artificial intelligence, wherein the scientist inserts their (or other humans') cognition into models because otherwise the models neither perform as advertised, nor mean what they are purported to, without said 'cake insertion.' We argue that the solution is to tease apart explanandum and explanans for a given scientific investigation, with an eye towards avoiding van Rooij's (formal) or Ryle's (informal) infinite regresses.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Guest, Olivia0000-0002-1891-0972
Martin, Andrea0000-0002-3395-7234
Keywords: computational neuroscience, cognitive map, concept cell, place cell
Subjects: Specific Sciences > Neuroscience > Cognitive Neuroscience
Specific Sciences > Cognitive Science
Specific Sciences > Cognitive Science > Computation
Specific Sciences > Artificial Intelligence
Specific Sciences > Cognitive Science > Concepts and Representations
Specific Sciences > Neuroscience
Depositing User: Olivia Guest
Date Deposited: 01 Mar 2025 13:17
Last Modified: 01 Mar 2025 13:17
Item ID: 24834
Subjects: Specific Sciences > Neuroscience > Cognitive Neuroscience
Specific Sciences > Cognitive Science
Specific Sciences > Cognitive Science > Computation
Specific Sciences > Artificial Intelligence
Specific Sciences > Cognitive Science > Concepts and Representations
Specific Sciences > Neuroscience
Date: 26 February 2025
URI: https://philsci-archive.pitt.edu/id/eprint/24834

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