The regulatory continuum: computational mechanisms of adaptive, pathological, and therapeutic brain state transitions

Across psychiatry, neurology, and cognitive neuroscience, focus is shifting from identifying isolated functional impairments toward understanding how neural systems regulate transitions between states. Modern systems neuroscience characterizes the brain as a metastable system operating near critical boundaries, where adaptive cognition emerges from controlled transitions across hierarchical predictive models and large-scale network configurations. Converging evidence suggests that many disorders arise not from localized deficits, but from instabilities in the mechanisms that balance stability and flexibility across time. Within this framework, health and disease are understood via the navigation of "attractor landscapes." Whether through rigid attractor states, as seen in depression and compulsivity, or paroxysmal instability, seen in epilepsy, clinical vulnerability reflects a failure in the regulatory processes that support flexible yet coherent behavior. This perspective provides a unifying computational framework for understanding the continuum between adaptive cognition, pathological instability, and therapeutic plasticity.The central challenge for the next generation of computational psychiatry is to move beyond descriptive accounts of dysfunction toward mechanistic models of brain-state regulation. While we recognize that adaptive cognition and clinical vulnerability exist along a regulatory continuum, the specific computational principles governing how the brain maintains stability while permitting necessary transitions remain underdeveloped.This Research Topic aims to address this gap by gathering work that formalizes how neural systems perform inference under uncertainty and navigate state-space transitions. We seek to advance a mechanistic understanding of "state-space re-engineering", identifying how internal processes and external interventions can destabilize maladaptive configurations and facilitate transitions toward health. By integrating frameworks such as active inference, network control theory, and dynamical systems, we aim to uncover the biomarkers of regulatory failure and the mechanisms of therapeutic change. Ultimately, this collection will bridge theoretical modeling and clinical application to better understand how the brain's dynamical landscape can be navigated to restore adaptive function.We welcome theoretical, empirical, and translational contributions that utilize formal computational frameworks to investigate brain-state regulation. We particularly encourage work integrating formal modeling with behavioral, neuroimaging, or clinical data.Specific themes of interest include:- Fundamental Mechanisms: Hierarchical inference, precision regulation, and dynamical models of stability, metastability, and criticality.- Pathological Instability: Regulatory failures across psychiatric and neurological domains, including rigid attractor states (depression, Parkinson’s) and paroxysmal transitions (epilepsy, migraine).- Therapeutic Modulation: "State-space re-engineering" via interventions like psychedelic-assisted therapies, neuromodulation, and network-level reorganization.- Social & Collective Neurodynamics: Computational models of state transitions in interpersonal and group contexts.- Lifespan Trajectories: How regulatory mechanisms mature across development and adapt during aging.- Bioenergetic Constraints: The role of metabolic resource allocation in state stability and transition probability. Topic editors: STEVEN SEUNG-SUK KANG, Kyung Hee Kim Source: https://www.frontiersin.org/research-topics/84596/the-regulatory-continuum-computational-mechanisms-of-adaptive-pathological-and-therapeutic-brain-state-transitions