Critical Thalamocortical Coordination Dynamics Track Conscious State Transitions

A new theoretical framework proposes that conscious states correspond to metastable regimes of large-scale thalamocortical coordination near critical dynamical boundaries. The framework formalizes a dynamic coordination functional Φ(t), measurable from high-density EEG as a weighted combination of gamma-band power, thalamocortical coherence, and theta-gamma coupling. The thalamic reticular nucleus (TRN) is identified as the anatomical control parameter governing proximity to the critical point, grounded in a Wilson-Cowan model. Numerical simulations show power-law recovery dynamics consistent with model A universality class (exponent ν between 0.5 and 1.5). The phase space of Φ(t) separates simulated waking, anaesthetic, ictal, and minimally conscious regimes without parameter fitting. Six falsifiable predictions across five experimental domains are derived, including specific EEG scaling exponents and TRN silencing effects.

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Abstract

Abstract Despite substantial progress in identifying neural correlates of consciousness, no unified quantitative framework currently derives a formally specified order parameter for conscious-state organisation from established neurophysiological principles, or links thalamocortical coordination dynamics to measurable state transitions across pharmacological, pathological, and perturbational conditions through a single computational formalism. We propose a neurocomputational theoretical framework in which conscious states are associated with metastable regimes of large-scale thalamocortical coordination operating near critical dynamical boundaries. The framework is formalised through a dynamic coordination functional Φ(t), defined as a surface integral over the thalamocortical interface and directly operationalisable from high-density EEG as a weighted combination of gamma-band power spectral density, thalamocortical coherence, and theta-gamma phase-amplitude coupling. The thalamic reticular nucleus (TRN) is identified as the anatomical implementation of the control parameter governing proximity to the critical point, grounded in a Wilson-Cowan model of TRN inhibitory gating whose bifurcation structure is characterised computationally. Numerical simulation of the linearised field equation on the thalamocortical boundary demonstrates internal consistency: the simulated system produces power-law recovery dynamics tau_rec proportional to | θ - θ _c|^v with nu consistent with model A universality class [0.5, 1.5], and a Kuramoto mean-field derivation establishes that Φ(t) emerges as the natural order parameter of coupled thalamocortical oscillators rather than being postulated. The joint (|Φ(t)|, Var[|Φ(t)|]) phase space correctly separates simulated waking, anaesthetic, ictal, and minimally conscious regimes without parameter fitting to empirical data. All simulation code is publicly available. Six quantitatively specific, independently falsifiable predictions are derived across five experimental domains: (1) power-law Gamma Dip scaling in near-threshold EEG with a specific exponent range; (2) causal disruption of thalamocortical coherence by selective TRN silencing; (3) opposite EEG scaling exponent deviations in ASD versus schizophrenia; (4) systematic Φ_est collapse under propofol anaesthesia correlated with PCI; (5) Φ_est as a real-time consciousness biomarker in disorders of consciousness; and (6) clinical validity of Φ_est in disorders of consciousness and ictal state discrimination by the metastability index. Each prediction is stated with quantitative thresholds and a pre-specified falsification criterion. The framework provides: (1) the first anatomically specified and formally derived order parameter for conscious-state organisation directly operationalisable from passive EEG; (2) a mechanistically grounded identification of the TRN as the dynamical control parameter, testable by a single optogenetic experiment; and (3) a computationally validated, pre-registerable programme of six falsifiable predictions defining a tractable empirical agenda. Φ_est would constitute a candidate real-time consciousness biomarker if the framework's predictions are confirmed in purpose-designed experiments.