Stochastic Dynamic Models for Computational Psychiatry and Computational Neurology

  • Frederike H. Petzschner
    Correspondence
    Address correspondence to Frederike H. Petzschner, Ph.D., Translational Neuromodeling Unit, Institute for Biomedical Engineering, UZH and ETH Zurich, Wilfriedstrasse 6, 8032 Zurich, Switzerland; .
    Affiliations
    Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
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      One of the central problems of modern psychiatry is its purely symptom-based nosology. Current diagnostic schemes, such as the DSM or ICD, define diseases as collections of clinical symptoms and signs; this conveys reliability to diagnoses, but also creates heterogeneous patient groups. This heterogeneity, in turn, complicates treatment predictions in clinical practice and hinders research that aims at identifying disease mechanisms in individual patients. As a consequence, the conventional disease classifications have been increasingly criticized, and the field is searching for alternatives that are grounded in a more fundamental understanding of the underlying disease processes (
      • Wang X.J.
      • Krystal J.H.
      Computational psychiatry.
      ).
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