Simulation Data and Code for: Stochastic Dynamics of Consciousness as a Multi-Scale Regime: A Metabolic–Integrative Formulation

This dataset contains the simulation code, parameter tables, generated outputs, and figure-generation scripts supporting the manuscript:

“Stochastic Dynamics of Consciousness as a Multi-Scale Regime: A Metabolic–Integrative Formulation.”

The repository implements a stochastic multi-scale dynamical framework in which fast neural integration dynamics are coupled to slower metabolic and systemic regulatory variables. The simulations reproduce the empirically constrained organization of conscious and unconscious conditions within a joint metabolic–integrative state space and generate emergent dynamical signatures including graded regime occupancy, hysteresis, stochastic switching, and systemic-state-dependent threshold shifts.

Contents include:

Python simulation scripts implementing the stochastic dynamical model

Parameterization and calibration tables

Condition-level summary outputs

Regime-occupancy analyses

Hysteresis sweep data

Switching time-series outputs

Figure-generation scripts

Reproducibility documentation and execution requirements

The simulations are phenomenological and are constrained using empirically observed relationships between cortical metabolism (FDG-PET) and neural integration (PCI derived from TMS–EEG). No machine-learning optimization or parameter fitting procedures were performed.

All files necessary to reproduce the reported simulations, figures, and tables are included.