Cortical neuron classes and recursive curvature collapse: a neurobiological model of conscious dynamics.
Theory in biosciences = Theorie in den Biowissenschaften June 20, 2026 Seyed Kiarash Sadat Rafiei, Mahsa Asadi Anar, AmirKasra Shahinzadeh et al.
A new theoretical framework, Recursive Informational Curvature (RIC), models conscious cognition as a stability regime of neural trajectories on a stratified informational manifold. The framework proposes that recursive gain, symbolic entropy dispersion, and loop-level timing coherence jointly determine whether neural activity remains stable or approaches collapse. RIC integrates three geometric layers: a Fisher layer for precision-weighted discriminability, a Finsler layer for direction-dependent transition cost, and a Hermitian layer for phase-coded recursive coordination. Mechanistic hypotheses link specific cortical neuronal classes to curvature control. A reduced EEG-based analysis showed that a geometry-sensitive neural state-space proxy related to moral judgment bias, but broader socially mediated outcomes were not captured by this reduced measure alone.