A Dynamical Systems Framework for Mapping Consciousness Models to Neuroelectromagnetic Field Dynamics

A multidimensional framework is introduced for comparing theories of consciousness, representing conscious states as vectors with physical (P), cognitive/computational (C), and noetic (N) components. The noetic dimension captures structured aspects of data or phenomenology not explained by current physical and cognitive models, treated as a testable latent variable. Using a linear-algebraic analogy, the framework clarifies how theories differ in explanatory assumptions and how these can be evaluated through perturbation, identifiability, and invariance criteria. It outlines mappings between neuroelectromagnetic dynamics and phenomenology, and describes empirical predictions and protocols for comparing theories based on empirical findings.

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Abstract

Abstract Contemporary consciousness science lacks a shared mathematical language for comparing theories that propose different relationships among biophysical processes, neuroelectric field dynamics, cognition, and subjective experience. Motivated by the problem of how experience relates to physical processes, we introduce a multidimensional framework in which conscious states are represented as vectors with physical (P), cognitive/computational (C), and noetic (N) components. In this framework, physical and cognitive variables are defined operationally in terms of measurable biophysical and neuroelectromagnetic dynamics, including nonlinear EEG or MEG features. The noetic component is introduced as a formal, method-relative dimension that captures structured, reproducible aspects of data or phenomenology that are not accounted for by current physical and cognitive models. It is treated as a latent, empirically testable degree of freedom inferred from structured residuals in dynamical and phenomenological data. Whether this dimension collapses into P and C or constitutes an additional explanatory axis is treated as an empirical question. Using a linear-algebraic analogy, the framework makes explicit how different theories differ in their explanatory assumptions and how these assumptions can be evaluated through perturbation, identifiability, and invariance criteria. Information links field-level organization in the cognitive domain to experiential structure, enabling testable mappings between neuroelectromagnetic dynamics and phenomenology. We outline how theoretical constructs map to measurable neuroelectric dynamical variables, describe empirical prediction classes, and outline perturbational and neurophenomenological protocols that allow competing theories of consciousness to be compared based on empirical findings rather than theoretical claims.