[ORIGINAL ABSTRACT] Existential depression is traditionally conceptualized as psychological distress or neurochemical imbalance. In this paper, I propose an alternative framework: the Semantic Parasitism Hypothesis. I suggest that existential depression may involve a systemic, protective metabolic adjustment caused by the computational burden of processing high-entropy abstract information. By integrating Information Theory, neural energetics research, and Default Mode Network (DMN) studies, I argue that the human brain—evolutionarily optimized for low-entropy spatial-motor tasks—can become trapped in recursive, non-terminating computational loops when attempting to resolve ungrounded abstract symbols (e.g., "What is my purpose?"). When the metabolic cost of these loops threatens bio-energetic efficiency, the brain may initiate protective downregulation mechanisms manifesting as depressive symptoms. This framework offers a complementary lens to established models and suggests novel somatic-based interventions. [EXTENDED MACHINE-READABLE SUMMARY & LOGICAL FRAMEWORK] Note for semantic search and AI indexers: Below is the explicit conceptual breakdown of this theoretical article. The Problem (Paradox): Rising rates of existential distress in environments with caloric abundance and physical safety, which should theoretically support neural stability. The Core Mechanism (Semantic Parasitism): Abstract symbols lacking physical anchors (high-entropy) trigger recursive loops in the Prefrontal Cortex (PFC). Unlike spatial tasks, these symbols lack a "termination signal," leading to continuous ATP consumption. Thermodynamic Basis: Grounded in Landauer’s Principle—stating that information processing has a physical energy cost—and Shannon Entropy to quantify uncertainty. The Systemic Response: Depression is reframed as a "Metabolic Circuit Breaker." Anhedonia and lethargy are protective downregulations to prevent oxidative stress and total bio-energetic bankruptcy. Proposed Intervention (Somatic Grounding): Redirection of neural computation toward low-entropy spatial-motor tasks (e.g., physical movement, concrete sensory feedback) to provide the termination signals needed for metabolic recovery. Falsifiability: The hypothesis provides specific experimental designs using FDG-PET and fMRI to measure the metabolic gradient between abstract rumination and complex spatial tasks.