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The best game in town: The reemergence of the language-of-thought hypothesis across the cognitive sciences

Published online by Cambridge University Press:  06 December 2022

Jake Quilty-Dunn Open the ORCID record for Jake Quilty-Dunn [Opens in a new window] ,
Nicolas Porot Open the ORCID record for Nicolas Porot [Opens in a new window]  and
Eric Mandelbaum Open the ORCID record for Eric Mandelbaum [Opens in a new window]
Jake Quilty-Dunn
Affiliation:
Department of Philosophy and Philosophy-Neuroscience-Psychology Program, Washington University in St. Louis, St. Louis, MO, USA. [email protected], sites.google.com/site/jakequiltydunn/
Nicolas Porot
Affiliation:
Africa Institute for Research in Economics and Social Sciences, Mohammed VI Polytechnic University, Rabat, Morocco. [email protected], nicolasporot.com
Eric Mandelbaum
Affiliation:
Departments of Philosophy and Psychology, The Graduate Center & Baruch College, CUNY, New York, NY, USA. [email protected], ericmandelbaum.com
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Abstract

Mental representations remain the central posits of psychology after many decades of scrutiny. However, there is no consensus about the representational format(s) of biological cognition. This paper provides a survey of evidence from computational cognitive psychology, perceptual psychology, developmental psychology, comparative psychology, and social psychology, and concludes that one type of format that routinely crops up is the language-of-thought (LoT). We outline six core properties of LoTs: (i) discrete constituents; (ii) role-filler independence; (iii) predicate–argument structure; (iv) logical operators; (v) inferential promiscuity; and (vi) abstract content. These properties cluster together throughout cognitive science. Bayesian computational modeling, compositional features of object perception, complex infant and animal reasoning, and automatic, intuitive cognition in adults all implicate LoT-like structures. Instead of regarding LoT as a relic of the previous century, researchers in cognitive science and philosophy-of-mind must take seriously the explanatory breadth of LoT-based architectures. We grant that the mind may harbor many formats and architectures, including iconic and associative structures as well as deep-neural-network-like architectures. However, as computational/representational approaches to the mind continue to advance, classical compositional symbolic structures – that is, LoTs – only prove more flexible and well-supported over time.

Keywords

animal cognitionautomaticitycognitive architecturedeep learningdual-process theoriesimplicit attitudesinfant cognitionlanguage-of-thoughtobject filesvisual cognition
Type
Target Article
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Behavioral and Brain Sciences , Volume 46 , 2023 , e261
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Copyright © The Author(s), 2022. Published by Cambridge University Press

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Footnotes

1

All authors contributed equally; authorship is in reverse alphabetical order.

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