Solving the Hard Problem: A Formal Information-Manifold Model of Consciousness

This work introduces a substrate-independent mathematical model of consciousness based on an information manifold structure. Conscious experience is defined as a globally integrated, self-referential manifold equipped with temporally continuous evolution and dimension-reducing observational projections. Four core results are proven: (1) unity of experience, (2) privacy of qualia, (3) diachronic identity through manifold invariants, and (4) substrate independence. A minimal toy model is constructed to explicitly instantiate these properties. The resulting framework bridges phenomenology, mathematical topology, and computational modeling, providing a foundation for empirical predictions, physical grounding, and distinctions between conscious systems and mere computational aggregates.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-05
DOI
https://doi.org/10.5281/zenodo.17833579
Primary Topic
Cognitive Science and Education Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Solving the Hard Problem: A Formal Information-Manifold Model of Consciousness

Zenodo (CERN European Organization for Nuclear Research)
Cognitive Science and Education Research
article

Solving the Hard Problem: A Formal Information-Manifold Model of Consciousness

article en

Abstract

This work introduces a substrate-independent mathematical model of consciousness based on an information manifold structure. Conscious experience is defined as a globally integrated, self-referential manifold equipped with temporally continuous evolution and dimension-reducing observational projections. Four core results are proven: (1) unity of experience, (2) privacy of qualia, (3) diachronic identity through manifold invariants, and (4) substrate independence. A minimal toy model is constructed to explicitly instantiate these properties. The resulting framework bridges phenomenology, mathematical topology, and computational modeling, providing a foundation for empirical predictions, physical grounding, and distinctions between conscious systems and mere computational aggregates.

Zenodo (CERN European Organization for Nuclear Research)
Fractal Systems (Canada) (CA)
Peace, Justice and strong institutions
Openalex Percentile: Top 39%
Cognitive Science and Education Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.