Dynamical disorders: synchronization dynamics in complex emotional conditions

Introduction Mental health conditions present a particular challenge to categorical nosology. We propose that such conditions are better understood as Dynamical Disorders, defined not only by symptom cluster profiles but by underlying disrupted patterns of coordination across bio-psycho-social scales. We present an exemplary case study of Complex Emotional Needs (CEN) presentations. Its transdiagnostic scope, process-defined clinical presentation, and 40–60% non-remission rates under current protocols reflect a mismatch between categorical nosology and the dynamic, multi-scale psycho-neurobiological processes underlying these conditions. Methods Drawing on affective neuroscience and synchronization dynamics, we propose reconceptualizing CEN as disorders of flexible functional synchronization across nested bio-psycho-social scales. Results We derive four dynamical phenotypes from the parameter space governing multi-scale synchronization and specify how to operationalize them empirically. They exhibit characteristic dynamical-landscape topologies, quantified by basin curvature, energy barrier heights, and stability exponents. Simulations of the master equation generate dynamical landscape topologies and phenotype-specific parameter regimes. Discussion This approach yields pragmatic, testable predictions of clinical dynamics and corresponding treatments. We consider the algorithmic selection of phenotype-matched modular interventions targeting specific coordination failures, along with a validation program that AI agents can eventually augment. We present falsifiable predictions for comparative trials between phenotype-matched and treatment-as-usual approaches. This framework offers a principled path toward evidence-based mental health care grounded in human synchronization dynamics.