"Dark Matter as a Bayesian Bias- A Proposed Gravitational Influence on Predictive Coding in Neural Systems"(V2)

This paper proposes a bold interdisciplinary hypothesis: that dark matter (DM) subtly influences human cognition through its gravitational effects on predictive coding in the brain. Building on the predictive coding framework in neuroscience and recent insights from quantum biology, the author models DM as a source of gravitational noise capable of biasing Bayesian priors in neural systems. The concept of Magnetic Information Density (MID) is introduced as a biological parameter that can shield against this influence, offering a novel bioelectromagnetic mechanism for cognitive stability. The work outlines testable experimental pathways—including geospatial studies, seasonal reaction time analyses, and in vitro microtubule probing—and provides a plausible estimate of DM-induced gravitational acceleration (~10⁻²⁰ m/s²). Philosophically, the paper reframes dark matter as a "cognitive perturbation field," challenging traditional separations between cosmology and consciousness. This publication is a fusion of physics, neuroscience, and philosophy, intended for researchers in theoretical physics, cognitive science, quantum biology, and systems neuroscience. It offers falsifiable predictions and opens new doors for understanding how the cosmos might quietly shape human perception. ---