From World-Brain Alignment to Network Dysfunction: A Spatiotemporal Framework for Precision Psychiatry

Contemporary psychiatry faces the challenge of overcoming the significant heterogeneity within existing diagnostic categories. Mechanistic, transdiagnostic models are crucial for the development of genuine precision psychiatry. This article proposes a novel, integrative multi-scale model that conceptualizes mental health and illness as the result of the brain's dynamic alignment with its environment. We argue that spatiotemporal dynamics represent the "common currency" in this world-brain relation (Northoff). The mechanism that accomplishes this alignment is Active Inference, maintained by a critical balance between a predictive, excitatory (E) and a corrective, inhibitory (I) control system (Friston, Tucker & Luu). A dysregulation of this mechanism manifests at the macroscopic level in the observable imbalances of large-scale brain networks such as the Default Mode Network (DMN). By defining pathology as a failure of spatiotemporal alignment—which manifests in rigid ("sub-critical") or chaotic ("super-critical") states—our framework provides a causal chain from the fundamental brain-environment relationship to the clinical symptom. This redefinition of pathology as a dynamic 'mal-alignment' simultaneously illuminates the path to healing: a targeted process of restoring this very alignment, leading from manifest network dysfunction back to mental health. We discuss the implications of this approach for defining transdiagnostic biotypes and developing dynamics-based therapies.