Neuroscience of Natural Cognitive Order: Brain Optimisation — The CIA Theoretical Framework: Natural Cognitive Order and the Maladaptive Self-Model Mechanism
Zenodo (CERN European Organization for Nuclear Research) July 19, 2026 DOI: 10.5281/zenodo.21438883 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Topics | Default mode network |
| Keywords | Operationalization Cognition Mechanism biology Construct python library Falsifiability Cognitive neuroscience Computational neuroscience Natural archaeology Cognitive systems Cognitive science Cognitive psychology Component thermodynamics Artificial intelligence Predictive coding Synchronization alternating current Property philosophy |
| Key points | Proposes that the human brain's deviation from an energy-efficient baseline state is caused by a learned 'Artificial Self-Model' that generates chronic predictive error and disrupts neural integration. |
Abstract
Here is the Abstract from your uploaded paper, ready to copy and paste into the Zenodo Description field: AbstractThis paper presents Neuroscience of Natural Cognitive Order: Brain Optimisation (The CIA Theoretical Framework), a theoretical neuroscience framework proposing that the human central nervous system possesses an evolved, energy-efficient baseline operating regime termed Natural Cognitive Order (NCO). The framework's central and most specific claim is mechanistic: it proposes a single, falsifiable candidate cause for why the human brain habitually fails to default to this baseline — the maintenance of an Artificial Self-Model (denoted S_a), a class of self-referential, anthropocentric informational structures that are learned and reinforced for psychological and cultural reasons rather than for biological accuracy. We hypothesize that S_a functions as a chronic, self-generated source of top-down predictive error, elevating metabolic expenditure, disrupting large-scale neural integration, and raising autonomic stress load. We formalize this mechanism within a unified systemic cost function J(θ), operationalize sustained well-being as a Normalized Bliss Index B(θ), define NCO as the parameter configuration θ* that minimizes J(θ), and specify how the latent construct S_a can be estimated from observable indicators using Structural Equation Modeling. We situate the framework relative to the Free Energy Principle, Self-Model Theory, Integrated Information Theory, Global Neuronal Workspace Theory, and the Default Mode Network literature, and we propose a falsifiable empirical protocol using fMRI/PET, EEG, and autonomic biomarkers. The framework is offered as a hypothesis-generating theoretical model, not an established neurobiological fact.