INNSDA: An Integrated Neurocognitive-Neuroendocrine State Dynamics Architecture

This paper proposes the Integrated Neurocognitive-Neuroendocrine State Dynamics Architecture (INNSDA), a conceptual framework for analysing how neural information processing, automatic regulation, endocrine activity, memory, prediction, reflective appraisal, behavioural selection, and contextual evaluation may interact within a human system. The framework distinguishes two analytically specified processing branches: automatic or minimally deliberative neurobiological processing, and conscious-reflective processing. These branches are treated as interacting functional descriptions, not as anatomically separate systems or an exhaustive division of all cognitive processes. A separate outcome architecture distinguishes positive, negative, and neutral or undetermined classifications. The outcome categories are further distinguished from experienced affective valence, physiological arousal, and the presence or absence of a detectable response.The framework comprises eighteen analytical layers and sixteen research domains. Its mathematical formulation includes state-space representations, individual-level parameters, physiological subsystems, prediction errors, observation models, and contextual classification functions. A primary case, termed Multisystem Cognitive State Transition (MCST), provides a common reference scenario across the architecture. A recognition-related event, such as receiving praise, is used as an illustrative special case rather than as the exclusive subject of the theory.INNSDA is presented as a testable theoretical proposal, not an empirically established universal law. In particular, the claim that a common functional architecture may operate across individuals is treated as a hypothesis requiring measurement, model me comparison, and independent replication. The paper specifies operational definitions, candidate equations, empirical predictions, boundary conditions, alternative explanations, and a research roadmap intended to make the framework falsifiable and progressively refinable.