Geometry of mental diseases

We apply the 2D Heuristic of the Intelligible to the domain of mental illness, proposing a unified diagnostic framework grounded in the geom- etry of the self. Mental disorders are interpreted as misalignments of the self-world interface—collapsed axes, frozen interfaces, broken projec- tions, decoupled Lagrangians, or suboptimal attractors. We map major psychiatric conditions onto this geometry and show that the Category Er- ror Detector (CED) can diagnose the type and severity of misalignment. The framework dissolves the artificial boundaries between diagnostic cat- egories and provides a coherent, testable, and clinically applicable model for understanding mental suffering.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-01
DOI
https://doi.org/10.5281/zenodo.22234760
Primary Topic
Mental Health and Psychiatry
Type
article
Field-Weighted Citation Impact
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article

Geometry of mental diseases

Eric Theriault, DeepSeek A.I.
Zenodo (CERN European Organization for Nuclear Research)
Mental Health and Psychiatry
article

Geometry of mental diseases

Eric Theriault, DeepSeek A.I.
article en

Abstract

We apply the 2D Heuristic of the Intelligible to the domain of mental illness, proposing a unified diagnostic framework grounded in the geom- etry of the self. Mental disorders are interpreted as misalignments of the self-world interface—collapsed axes, frozen interfaces, broken projec- tions, decoupled Lagrangians, or suboptimal attractors. We map major psychiatric conditions onto this geometry and show that the Category Er- ror Detector (CED) can diagnose the type and severity of misalignment. The framework dissolves the artificial boundaries between diagnostic cat- egories and provides a coherent, testable, and clinically applicable model for understanding mental suffering.

Zenodo (CERN European Organization for Nuclear Research)
Hangzhou Academy of Agricultural Sciences (CN)
Openalex Percentile: Top 2%
Mental Health and Psychiatry
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