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Anil K. Seth

Canadian Institute for Advanced Research, University of Sussex

54 papers in the library · 8,967 citations · publishing 2006-2026

Papers

Integrated information theory: the good, the bad and the misunderstood

arXiv Preprint Archive April 13, 2026 Adam B. Barrett, Borjan Milinkovic, Pedro A. M. Mediano et al.

The integrated information theory of consciousness (IIT) proposes a mathematical formula, derived from fundamental properties of conscious experience, to describe the quantity and quality of consciousness for any physical system. This article clarifies common misunderstandings. A high value of the measure Φ does not mean 'more consciousness'; Φ might be replaced with a suite of quantities for a multidimensional characterization. IIT implies a distinct panpsychism where space and time are tiled with substrates of proto-consciousness, which the authors find unproblematic. Φ is not well-defined for real physical systems and has never been computed on one; only proxies have been computed, not approximations. For IIT to align with fundamental physics, a reformulation in continuous fields would be needed.

Mapping of Subjective Accounts into Interpreted Clusters (MOSAIC): Topic Modelling and LLM applied to Stroboscopic Phenomenology

arXiv Preprint Archive February 25, 2025 Romy Beauté, David J. Schwartzman, Guillaume Dumas et al.

Stroboscopic light stimulation on closed eyes typically induces simple visual hallucinations—vivid, geometric, and colorful patterns. An analysis of 862 open-ended reports from the Dreamachine immersive experience, using large language models and topic modeling, confirmed these simple hallucinations and also revealed altered states of consciousness and complex hallucinations. This computational approach enables systematic study of subjective experiences beyond standard questionnaires, capturing subtle patterns not readily identified through closed-form questions. The findings broaden understanding of stroboscopically induced phenomena and demonstrate the potential of natural language processing in computational neurophenomenology.

On the Minimal Theory of Consciousness Implicit in Active Inference

arXiv Preprint Archive October 9, 2024 Christopher J. Whyte, Andrew W. Corcoran, Jonathan Robinson et al.

Subjective experience is multifaceted, making consciousness hard to study because traditional theories often focus on isolated aspects like perception or wakefulness and are difficult to compare. This work starts from active inference—a first-principles framework that models behavior as approximate Bayesian inference—and builds toward a minimal theory of consciousness derived from shared features of computational models under active inference. Reviewing models applied to consciousness, the authors argue that these models imply a small set of theoretical commitments pointing to a minimal, testable theory of consciousness.

A Rosetta Stone Hypothesis for Neurophenomenology: Mathematical Predictions from Predictive Processing

arXiv Preprint Archive September 30, 2024 Lancelot da Costa, Anil K. Seth, Karl Friston et al.

A Rosetta Stone hypothesis from predictive processing proposes that beliefs serve as a central hub linking phenomenology, behavior, and neural dynamics. If phenomenology is a function of beliefs, then specific predictions follow for subjective similarity judgments, cognitive metabolic cost, subjective cognitive effort, and time perception. The connection between beliefs and neural dynamics completes the generative passage for neurophenomenology, while the belief-behavior link is already well-documented. Testing these predictions will inform the validity of the central assumption and advance the neurophenomenology research program.