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Wiley Interdiscip Rev Cogn Sci. 2017 May;8(3). doi: 10.1002/wcs.1420. Epub 2016 Sep 21.

Models of neuromodulation for computational psychiatry.

Author information

1
Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & Swiss Federal Institute of Technology (ETH Zurich), Zurich, Switzerland.
2
Wellcome Trust Centre for Neuroimaging, University College London, London, UK.
3
Max Planck Institute for Metabolism Research, Cologne, Germany.

Abstract

Psychiatry faces fundamental challenges: based on a syndrome-based nosology, it presently lacks clinical tests to infer on disease processes that cause symptoms of individual patients and must resort to trial-and-error treatment strategies. These challenges have fueled the recent emergence of a novel field-computational psychiatry-that strives for mathematical models of disease processes at physiological and computational (information processing) levels. This review is motivated by one particular goal of computational psychiatry: the development of 'computational assays' that can be applied to behavioral or neuroimaging data from individual patients and support differential diagnosis and guiding patient-specific treatment. Because the majority of available pharmacotherapeutic approaches in psychiatry target neuromodulatory transmitters, models that infer (patho)physiological and (patho)computational actions of different neuromodulatory transmitters are of central interest for computational psychiatry. This article reviews the (many) outstanding questions on the computational roles of neuromodulators (dopamine, acetylcholine, serotonin, and noradrenaline), outlines available evidence, and discusses promises and pitfalls in translating these findings to clinical applications. WIREs Cogn Sci 2017, 8:e1420. doi: 10.1002/wcs.1420 For further resources related to this article, please visit the WIREs website.

PMID:
27653804
DOI:
10.1002/wcs.1420
[Indexed for MEDLINE]

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