This manuscript introduces the foundational architecture of Neurocognitive Reality Construction Theory, a comprehensive multi-part framework modeling how physical cognitive systems actively construct subjective reality. Grounded in active inference, predictive processing, and hierarchical Bayesian inference, Volume I establishes the core mechanisms through which biological neural networks integrate interoceptive and exteroceptive signals to maintain structural integrity and minimize free energy. By bridging computational neuroscience with the operational demands of fear-response modeling and environmental mapping, this work provides a scalable, mechanism-oriented blueprint for understanding human conscious experience. This text represents Part 1 of a multi-volume theoretical series, laying the structural and mathematical groundwork for subsequent engineering applications in autonomous computational cognitive architectures.
Aditya Rawat (Sun,) studied this question.