Dynamical system modeling in schizophrenia: a narrative review of computational psychiatry frameworks

1. Dialogues Clin Neurosci. 2026 Dec;28(1):327-342. doi:
10.1080/19585969.2026.2724875. Epub 2026 Sep 6.

Dynamical system modeling in schizophrenia: a narrative review of computational
psychiatry frameworks.

Soydemir H(1), Gauld C(2), Desroches M(3)(4), Pignon B(5), Depannemaecker D(1).

Author information:
(1)Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France.
(2)SANPSY, CNRS, UMR 6033, Service de psychopathologie du développement,
Hospices Civils de Lyon, Bordeaux, France.
(3)Inria Branch at the University of Montpellier, Montpellier, France.
(4)Basque Center for Applied Mathematics, Bilbao, Spain.
(5)APHP, Paris, France.

The temporal evolution of schizophrenia symptoms is inherently complex and
non-linear. Clinical states fluctuate between relatively stable and highly
disorganised phases. These dynamics are only partially captured by conventional
diagnostic frameworks. This limitation has motivated the development of models
that explicitly account for temporal structure and state transitions. Dynamical
systems theory provides a rigorous framework for describing non-linear
interactions and evolving symptom trajectories. Recent advances in longitudinal
data acquisition and computational analysis have enabled the identification of
informative dynamical features and the characterisation of patient-specific
trajectories. This narrative review synthesises the growing body of work
applying dynamical systems theory to schizophrenia spectrum disorders. It
distinguishes theoretical models, data-driven approaches, and frameworks
empirically evaluated against real patient data. It also examines methodological
limitations, translational challenges, and the need for further longitudinal
validation. The aim is to provide a coherent conceptual framework for
understanding schizophrenia as a dynamic process, to promote cross-disciplinary
dialogue, and to guide future research in translational computational
psychiatry.

DOI: 10.1080/19585969.2026.2724875
PMCID: PMC13552316
PMID: 42702800 [Indexed for MEDLINE]

Conflict of interest statement: No potential competing interest was reported by
the authors.

Auteurs Bordeaux Neurocampus