What question did this study set out to answer?

This research aims to determine whether conscious level is more effectively described by dynamical traversability rather than neural entropy.

February 11, 2026Open Access

Manifold Traversability Dissociates Conscious Level from Neural Entropy: An Empirical Evaluation of Noetic Diffusion Theory

Key Points

This research aims to determine whether conscious level is more effectively described by dynamical traversability rather than neural entropy.
Evaluated consciousness across different states: anesthesia, sleep, epilepsy, and task engagement.
Used EEG and fMRI techniques to collect data.
Analyzed manifold geometry and second-order dynamics to assess conscious levels and entropy.
Manifold geometry effectively dissociates conscious level from entropy-like measures.
Meta-Noetic Phase Space and Jacobian-based indices better track consciousness compared to entropy metrics.
Findings support a dynamic-geometric perspective consistent with biological and computational frameworks.

Abstract

This paper evaluates whether conscious level is better captured by dynamical traversability than by neural entropy, explicitly framed against Churchland’s criteria for a mature neurocomputational theory. Using EEG and fMRI across anesthesia, sleep, epilepsy, and task engagement, we show that manifold geometry and second-order dynamics dissociate conscious level from entropy-like measures. Meta-Noetic Phase Space and Jacobian-based indices track loss and recovery of consciousness where entropy fails, supporting a dynamical–geometric account aligned with biological and computational constraints.

Manifold Traversability Dissociates Conscious Level from Neural Entropy: An Empirical Evaluation of Noetic Diffusion Theory

Key Points

Abstract

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