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This review provides a dynamical systems perspective on psychiatric symptomsand disease, and discusses its potential implications for diagnosis, prognosis,and treatment. After a brief introduction into the theory of dynamical systems,we will focus on the idea that cognitive and emotional functions areimplemented in terms of dynamical systems phenomena in the brain, a commonassumption in theoretical and computational neuroscience. Specificcomputational models, anchored in biophysics, for generating different types ofnetwork dynamics, and with a relation to psychiatric symptoms, will be brieflyreviewed, as well as methodological approaches for reconstructing the systemdynamics from observed time series (like fMRI or EEG recordings). We thenattempt to outline how psychiatric phenomena, associated with schizophrenia,depression, PTSD, ADHD, phantom pain, and others, could be understood indynamical systems terms. Most importantly, we will try to convey that thedynamical systems level may provide a central, hub-like level of convergencewhich unifies and links multiple biophysical and behavioral phenomena, in thesense that diverse biophysical changes can give rise to the same dynamicalphenomena and, vice versa, similar changes in dynamics may yield differentbehavioral symptoms depending on the brain area where these changes manifest.If this assessment is correct, it may have profound implications for thediagnosis, prognosis, and treatment of psychiatric conditions, as it puts thefocus on dynamics. We therefore argue that consideration of dynamics shouldplay an important role in the choice and target of interventions.

Psychiatric Illnesses as Disorders of Network Dynamics