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We need to explain subjective experience, but its explanation may not be mechanistic

Abstract:
Models of consciousness need to explain both the objective correlates of conscious experience as well as its subjective structure. However, such an explanation would not need to entail a reduction exclusively in terms of physical or neural systems. A model that intends to avoid such reduction is integrated information theory (IIT). In this article, we discuss the explanatory rationale of IIT, its potential inconsistencies and its consequences for the neuroscience of consciousness more broadly. In particular, we identify ambiguities regarding the directionality of the explanation, i.e. important tensions between IIT’s purported ontological and epistemological primacy of experience, and its explanatory aim of accounting for consciousness in physical, operational terms. Across the text, we propose several ways to avoid these issues and eventually complement, enhance or replace the model. The main goal is to motivate clarification among IIT-proponents and inform IIT-opponents on accurate points of contention, without thereby misrepresenting the model. In our final section, we introduce alternative explanatory paths: mathematical, processual, and autonomy-based types of explanations. These novel and sound explanatory strategies may better inspire the next generation of models of consciousness.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1093/nc/niaf034

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Sub department:
Computer Science
Role:
Author
ORCID:
0000-0002-2110-7646
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Role:
Author
ORCID:
0000-0003-1890-0827


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Funder identifier:
10.13039/501100002661
Grant:
MIS/VA-F.4512.21
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Funder identifier:
https://ror.org/01kpjmx04
Grant:
CF22-1432


Publisher:
Oxford University Press
Journal:
Neuroscience of Consciousness More from this journal
Volume:
2026
Issue:
1
Article number:
niaf034
Publication date:
2026-05-09
Acceptance date:
2025-06-09
DOI:
EISSN:
2057-2107
ISSN:
2057-2107


Language:
English
Keywords:
Source identifiers:
4030076
Deposit date:
2026-05-09
ARK identifier:
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