Society & Economicspreprint2026-08-14

A Somatic Ontology for Computational Therapeutics: Formalizing Body-Based Experience for Digital Mental Health

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Abstract

The Cathexis Somatic Ontology (CSO) is a formal vocabulary and relational schema for encoding body-based therapeutic data. Its canonical name and namespace are CSO; it is registered as CXSO on NCBO BioPortal, where the acronym CSO was already taken. The two names refer to the same ontology. Digital mental health platforms increasingly incorporate body-based therapeutic approaches, yet no standardized ontology exists for representing somatic experience computationally. CSO addresses this gap. It defines entity classes for anatomical zones (29 zones, each with a clinical-significance rationale), sensation qualities (20 phenomenological descriptors), neurobiological organization patterns (16 territories derived from predictive processing, primary affect systems, and somatic marker theory), therapeutic change mechanisms (three memory-system-based pathways), and intervention architectures (seven mechanism types). Entities are organized within a Markov blanket framework of four components — internal, external, sensory, and active states — a principled computational structure derived from Friston's free energy principle. The ontology is grounded in seven major research programs: constructed emotion theory (Barrett), predictive processing (Friston), affective neuroscience (Panksepp), somatic markers (Damasio), neuropsychoanalysis (Solms), the entangled brain framework (Pessoa), and memory systems (Kandel, Nader, Schiller, Ecker). These are integrated within the Human Experience System (HES; DeGarbo, 2026), the transdisciplinary model that provides CSO's theoretical foundation, and applied clinically through the Human Experience Framework (HEF), its sixteen-territory classification layer. This record includes both the specification paper and the machine-readable ontology (OWL, Turtle, and JSON-LD), enabling programmatic consumption by clinical systems, research platforms, and AI agents. Published under CC BY 4.0 — free to use, adapt, and build on commercially with attribution. The complete framework is available free at https://cathexis.health/science

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View paper (DOI)Open access versionOpenAlexOpen MINDPublished 2026-08-14

Authors: Justin DeGarbo

Institutions: Université catholique de l'ouest