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Formalising the role of behaviour in neuroscience.

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Title: Formalising the role of behaviour in neuroscience.
Authors: Piantadosi, Steven T. (AUTHOR), Gallistel, Charles R. (AUTHOR)
Source: European Journal of Neuroscience. Sep2024, Vol. 60 Issue 5, p4756-4770. 15p.
Subjects: Natural numbers, Systems theory, Cognition, Ants, Motivation (Psychology)
Abstract: We develop a mathematical approach to formally proving that certain neural computations and representations exist based on patterns observed in an organism's behaviour. To illustrate, we provide a simple set of conditions under which an ant's ability to determine how far it is from its nest would logically imply neural structures isomorphic to the natural numbers ℕ. We generalise these results to arbitrary behaviours and representations and show what mathematical characterisation of neural computation and representation is simplest while being maximally predictive of behaviour. We develop this framework in detail using a path integration example, where an organism's ability to search for its nest in the correct location implies representational structures isomorphic to two‐dimensional coordinates under addition. We also study a system for processing anbn strings common in comparative work. Our approach provides an objective way to determine what theory of a physical system is best, addressing a fundamental challenge in neuroscientific inference. These results motivate considering which neurobiological structures have the requisite formal structure and are otherwise physically plausible given relevant physical considerations such as generalisability, information density, thermodynamic stability and energetic cost. [ABSTRACT FROM AUTHOR]
Copyright of European Journal of Neuroscience is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Formalising the role of behaviour in neuroscience.
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  Data: <searchLink fieldCode="AR" term="%22Piantadosi%2C+Steven+T%2E%22">Piantadosi, Steven T.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gallistel%2C+Charles+R%2E%22">Gallistel, Charles R.</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22European+Journal+of+Neuroscience%22">European Journal of Neuroscience</searchLink>. Sep2024, Vol. 60 Issue 5, p4756-4770. 15p.
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  Data: We develop a mathematical approach to formally proving that certain neural computations and representations exist based on patterns observed in an organism's behaviour. To illustrate, we provide a simple set of conditions under which an ant's ability to determine how far it is from its nest would logically imply neural structures isomorphic to the natural numbers ℕ. We generalise these results to arbitrary behaviours and representations and show what mathematical characterisation of neural computation and representation is simplest while being maximally predictive of behaviour. We develop this framework in detail using a path integration example, where an organism's ability to search for its nest in the correct location implies representational structures isomorphic to two‐dimensional coordinates under addition. We also study a system for processing anbn strings common in comparative work. Our approach provides an objective way to determine what theory of a physical system is best, addressing a fundamental challenge in neuroscientific inference. These results motivate considering which neurobiological structures have the requisite formal structure and are otherwise physically plausible given relevant physical considerations such as generalisability, information density, thermodynamic stability and energetic cost. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of European Journal of Neuroscience is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/ejn.16372
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      – SubjectFull: Ants
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      – SubjectFull: Motivation (Psychology)
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              Text: Sep2024
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