This article proposes a dynamical, neuro-complexity framework for interpreting the emergence of consciousness as a phase transition (“cognitive singularity”) rather than a mere scaling effect of neural abundance. It argues that quantitative proxies—such as total neuron count, synaptic density, or memory capacity—capture important correlates of cognition but are insufficient to explain phenomenal awareness and experiential unification. The central claim is that consciousness depends on a selective family of “valid pathways”: non-additive trajectories in neural state space shaped by constraints, re-entries, and feedback, enabling metastable coordination and regime shifts. Three conceptual pathway classes are discussed: predictive feedback loops in which prediction errors iteratively update internal models; recurrent attractor dynamics supporting continuity through transformed revisitation of states; and intermittent large-scale integration/segregation that provides temporal windows for global availability without loss of specialization. The article further outlines a reverse-engineering strategy: inferring minimal dynamical conditions for consciousness from its observable signatures, with implications for experimental and clinical neurology, particularly in dissociations between preserved responses and impaired awareness (e.g., anesthesia, coma, neglect, minimally conscious states). The proposed perspective reframes research questions from “how much” neural resource is required to “which pathways must be possible,” and suggests testable hypotheses in terms of metastability, recurrence, and integration windows.
VG ILDA (Sat,) studied this question.