New Framework Maps Brain Activity Across Extreme States, Revealing Limits of AI Prediction
Researchers have developed a unified mathematical model to track neural activity during anesthesia, psychosis, epilepsy, and other extreme brain states. The findings suggest current dynamical approaches work well in some contexts but fail to predict consciousness itself—a critical insight for pharmaceutical development, neurotechnology regulation, and clinical decision-making.
Originaltitel: Extreme Neurodynamic Regimes Reveal Meta–Noetic Dissociations
This work presents Noetic Diffusion Theory (NDT) as a dynamical framework for analyzing neural activity across extreme neurodynamic regimes, including anesthesia, sleep, psychedelics, epilepsy, psychosis, and neurodegeneration. Neural time series are embedded in a Meta–Noetic Phase Space (MNPS), extended via stratification and second-order flow analysis using the Meta–Noetic Jacobian (MNJ). Applying a unified pipeline to multiple EEG and fMRI datasets, the study reveals regime-specific dissociations and principled null results, highlighting both the utility and limits of dynamical state-space approaches to consciousness research.