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Schizophr Res. 2016 Oct;176(2-3):83-94. doi: 10.1016/j.schres.2016.07.014. Epub 2016 Jul 20.

The dysconnection hypothesis (2016).

Author information

1
Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, UK. Electronic address: k.friston@ucl.ac.uk.
2
Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, UK; Oxford Centre for Human Brain Activity, University of Oxford, UK.
3
Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland; Department of Psychiatry, Psychotherapy and Psychosomatics, Zurich, Switzerland.
4
Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland.

Abstract

Twenty years have passed since the dysconnection hypothesis was first proposed (Friston and Frith, 1995; Weinberger, 1993). In that time, neuroscience has witnessed tremendous advances: we now live in a world of non-invasive neuroanatomy, computational neuroimaging and the Bayesian brain. The genomics era has come and gone. Connectomics and large-scale neuroinformatics initiatives are emerging everywhere. So where is the dysconnection hypothesis now? This article considers how the notion of schizophrenia as a dysconnection syndrome has developed - and how it has been enriched by recent advances in clinical neuroscience. In particular, we examine the dysconnection hypothesis in the context of (i) theoretical neurobiology and computational psychiatry; (ii) the empirical insights afforded by neuroimaging and associated connectomics - and (iii) how bottom-up (molecular biology and genetics) and top-down (systems biology) perspectives are converging on the mechanisms and nature of dysconnections in schizophrenia.

KEYWORDS:

Bayesian; Dysconnection; Neurogenetics; Neuromodulation; Predictive coding; Schizophrenia

PMID:
27450778
PMCID:
PMC5147460
DOI:
10.1016/j.schres.2016.07.014
[Indexed for MEDLINE]
Free PMC Article

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