Depression as Compression-Function Arrest A Rate-Distortion Account of Depressive Mechanisms, Cognitive-Architecture-Specific Subtypes, and Optimal Intervention Matching An Application of Adaptive Compression Advantage Theory (ACAT)

Major depressive disorder remains defined by symptom checklists (DSM-5) without a unified mechanistic account. The serotonin hypothesis has been substantially weakened by recent meta-analytic evidence (Moncrieff et al., 2022), leaving a theoretical vacuum. This paper applies the Adaptive Compression Advantage Theory (ACAT; Murata, 2026) to propose that depression is compression-function arrest: a protective shutdown of the cognitive system’s gist-extraction architecture when distortion costs exceed tolerance thresholds. We formalize two distinct etiological pathways (hardware degradation vs. input-gist mismatch), derive four cognitive-architecture-specific subtypes corresponding to distinct arrest mechanisms (Ne: state-space degeneracy; Si: buffer overflow; Ni: sub-linguistic gist corruption; Se: input signal degradation), and demonstrate that each subtype predicts differential treatment response. The framework unifies the efficacy of SSRIs (compression-parameter recalibration), CBT (manual gist rewriting), exercise (safe-input reboot), and environmental change (input-source replacement) under a single equation. We further explain why interpersonal triggers dominate depressive etiology—conversational input imposes maximal buffer load due to irreducible ambiguity—and why socially extraverted, low-α individuals show paradoxical resilience alongside catastrophic vulnerability to meaning-forcing events. Nine testable predictions are generated, several immediately testable with existing clinical datasets. Keywords: depression, rate-distortion theory, compression, cognitive architecture, SSRI, CBT, MBTI, ADHD, interpersonal stress, ACAT, gist-verbatim dissociation, treatment matching