Attractor Dynamics in Bioelectric Networks: A Framework for Understanding Nonlinear Morphogenetic Transitions - V2

A fundamental question in developmental biology concerns how modest molecular perturbations produce organism-level morphogenetic reorganization. Linear models predict that small regulatory changes should yield proportionally small phenotypic effects, yet experimental evidence demonstrates that transient interventions can permanently reprogram body plan specification. This paper proposes that bioelectric networks—the voltage gradients and ion fluxes that encode morphogenetic information—operate as nonlinear dynamical systems near critical thresholds, enabling phase transitions between stable attractor states in response to perturbations below what linear models would predict as significant. Drawing on mathematical modeling of multicellular bioelectric dynamics (Cervera et al., 2016, 2024), empirical studies of regenerative pattern formation (Levin, 2012, 2021), and experimental demonstrations of morphogenetic reprogramming (Oviedo et al., 2010; Durant et al., 2017; Emmons-Bell et al., 2015), we develop a theoretical framework for understanding how regulatory interventions at the molecular level—including epigenetic modifications affecting ion channel expression—can flip developmental systems between discrete anatomical outcomes. The framework treats morphogenetic patterns as attractor states in a bioelectric state space, with the system's position relative to basin boundaries determining susceptibility to transition. Critically, we distinguish between deep bistable attractors (producing permanent morphogenetic changes that persist through regeneration cycles) and shallow metastable states (producing transient changes that decay toward global minima). This distinction—supported by differential outcomes across planarian species and perturbation types—provides evidence for variable basin depth as a key parameter in morphogenetic regulation. This hypothesis generates testable predictions regarding threshold identification, perturbation magnitude-response relationships, and the temporal dynamics of state transitions. Falsification criteria are specified. The framework has implications for understanding developmental disorders, regenerative medicine, and the relationship between molecular regulation and macroscopic form.