Discipline: Biophysics / Theoretical Neurobiology / Cybernetics / Applied Data Physics Abstract. Biological neural computation operates under extreme energetic and spatial constraints, dissipating approximately 20 W of thermal power within a 1.5 kg mass while executing complex informational throughput. Classical physiological models, derived from the homeostatic paradigm of Roy and Sherrington (1890), frame cerebral perfusion through reactive negative feedback: blood flow increases secondarily in response to metabolic byproduct accumulation (lactate, H⁺, adenosine) and localized tissue hypoxia (pO₂ drop). However, the viscous hydrodynamic inertia of erythrocyte transport through capillary beds imposes a transport latency (τ_rheo ≈ 1000–2000 ms) that vastly exceeds the temporal destruction threshold of localized neuronal networks undergoing high-frequency synaptic discharge (τ_spike ≈ 10–50 ms). This paper formalizes cerebral circulation as an allostatic cybernetic control system exhibiting direct mathematical isomorphism with the Data Physics framework. We analyze the astrocytic-neuronal-vascular tripartite synapse as an anticipatory feedforward network. Upon presynaptic depolarization, astrocytic endfeet intercept neurotransmitter flux via EAAT1/2 transporters and synthesize vasoactive messengers (epoxyeicosatrienoic acids [EETs], prostaglandin E₂ [PGE₂]), dilating parenchymal arterioles 100–300 ms prior to localized tissue hypoxia or metabolic exhaustion. Furthermore, we demonstrate that neurodegenerative pathologies (Alzheimer's disease, Cerebral Amyloid Angiopathy [CAA], chronic hypertension) represent a cybernetic collapse of this feedforward network (κ_astro → 0), reducing the brain to a purely reactive, homeostatic regime characterized by chronic metabolic throttling—the biological analog of silicon DVFS clock degradation.
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Rajmund Olszewski (2026) studied this question.
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