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Editorial: AI and neuroscience: integrating knowledge, reasoning, and theory of mind

Darren Edwards Orcid Logo, Bochao Zou, Rob Lowe, Andrew Owens

Frontiers in Computational Neuroscience, Volume: 20

Swansea University Author: Darren Edwards Orcid Logo

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DOI (Published version): 10.3389/fncom.2026.1859797

Abstract

Artificial intelligence and neuroscience have been converging on a shared problem about how to explain and ultimately build systems (biological or synthetic) that can acquire knowledge from experience, reason under uncertainty, and coordinate perspectives from self-model representations to other min...

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Published in: Frontiers in Computational Neuroscience
ISSN: 1662-5188
Published: Frontiers Media SA 2026
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URI: https://cronfa.swan.ac.uk/Record/cronfa71947
first_indexed 2026-05-19T05:49:27Z
last_indexed 2026-06-12T13:21:18Z
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spelling 2026-06-11T12:27:30.0411057 v2 71947 2026-05-19 Editorial: AI and neuroscience: integrating knowledge, reasoning, and theory of mind bee507022c083d875238b7802b96cbeb 0000-0002-2143-1198 Darren Edwards Darren Edwards true false 2026-05-19 HSOC Artificial intelligence and neuroscience have been converging on a shared problem about how to explain and ultimately build systems (biological or synthetic) that can acquire knowledge from experience, reason under uncertainty, and coordinate perspectives from self-model representations to other minds (Hassabis et al., 2017; Langley et al., 2022; Limanowski and Blankenburg, 2013; Nawaz et al., 2025). The “AI and neuroscience: integrating knowledge, reasoning, and theory of mind” theme captures this convergence by explicitly highlighting a broad body of research linking accounts of neural information processing with computational architectures that can learn, generalize, and remain interpretable. At a broad level, the contributions in this Research Topic can be read as collectively operating across three complementary levels. First, they investigate biological substrates of computation and the representational constraints that come with real neural tissue. Second, they advance architectures and modeling frameworks that treat cognition as an evolving repertoire of learned competencies rather than a set of isolated tasks. Third, they address human–AI coupling, i.e., how AI systems can extend cognition without displacing the very internal knowledge structures that make reasoning and perspective-taking possible in the first place. Journal Article Frontiers in Computational Neuroscience 20 Frontiers Media SA 1662-5188 19 5 2026 2026-05-19 10.3389/fncom.2026.1859797 Editorial COLLEGE NANME Health and Social Care School COLLEGE CODE HSOC Swansea University Not Required 2026-06-11T12:27:30.0411057 2026-05-19T06:46:00.1683573 Faculty of Medicine, Health and Life Sciences School of Health and Social Care - Public Health Darren Edwards 0000-0002-2143-1198 1 Bochao Zou 2 Rob Lowe 3 Andrew Owens 4 71947__36931__82bb9bd257a04c81bd90cbf2d4fe6ab0.pdf 71947.VoR.pdf 2026-06-11T12:11:33.3105834 Output 116594 application/pdf Version of Record true © 2026 Edwards, Zou, Lowe and Owens. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). true eng http://creativecommons.org/licenses/by/4.0/
title Editorial: AI and neuroscience: integrating knowledge, reasoning, and theory of mind
spellingShingle Editorial: AI and neuroscience: integrating knowledge, reasoning, and theory of mind
Darren Edwards
title_short Editorial: AI and neuroscience: integrating knowledge, reasoning, and theory of mind
title_full Editorial: AI and neuroscience: integrating knowledge, reasoning, and theory of mind
title_fullStr Editorial: AI and neuroscience: integrating knowledge, reasoning, and theory of mind
title_full_unstemmed Editorial: AI and neuroscience: integrating knowledge, reasoning, and theory of mind
title_sort Editorial: AI and neuroscience: integrating knowledge, reasoning, and theory of mind
author_id_str_mv bee507022c083d875238b7802b96cbeb
author_id_fullname_str_mv bee507022c083d875238b7802b96cbeb_***_Darren Edwards
author Darren Edwards
author2 Darren Edwards
Bochao Zou
Rob Lowe
Andrew Owens
format Journal article
container_title Frontiers in Computational Neuroscience
container_volume 20
publishDate 2026
institution Swansea University
issn 1662-5188
doi_str_mv 10.3389/fncom.2026.1859797
publisher Frontiers Media SA
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str School of Health and Social Care - Public Health{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}School of Health and Social Care - Public Health
document_store_str 1
active_str 0
description Artificial intelligence and neuroscience have been converging on a shared problem about how to explain and ultimately build systems (biological or synthetic) that can acquire knowledge from experience, reason under uncertainty, and coordinate perspectives from self-model representations to other minds (Hassabis et al., 2017; Langley et al., 2022; Limanowski and Blankenburg, 2013; Nawaz et al., 2025). The “AI and neuroscience: integrating knowledge, reasoning, and theory of mind” theme captures this convergence by explicitly highlighting a broad body of research linking accounts of neural information processing with computational architectures that can learn, generalize, and remain interpretable. At a broad level, the contributions in this Research Topic can be read as collectively operating across three complementary levels. First, they investigate biological substrates of computation and the representational constraints that come with real neural tissue. Second, they advance architectures and modeling frameworks that treat cognition as an evolving repertoire of learned competencies rather than a set of isolated tasks. Third, they address human–AI coupling, i.e., how AI systems can extend cognition without displacing the very internal knowledge structures that make reasoning and perspective-taking possible in the first place.
published_date 2026-05-19T06:02:36Z
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score 11.109323

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