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Schizophr Res. 2014 Sep;158(1-3):204-12. doi: 10.1016/j.schres.2014.06.011. Epub 2014 Jul 3.

The functional anatomy of schizophrenia: A dynamic causal modeling study of predictive coding.

Author information

Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel. Electronic address:
The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, UCL, London, UK.
Institute for Psychiatric Studies, Sha'ar Menashe Mental Health Center, Hadera, Israel; B Rappaport Faculty of Medicine, Technion, Haifa, Israel.
Department of Physical Education, University of A Coruña, La Coruña, Spain.
The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, UCL, London, UK. Electronic address:


This paper tests the hypothesis that patients with schizophrenia have a deficit in selectively attending to predictable events. We used dynamic causal modeling (DCM) of electrophysiological responses - to predictable and unpredictable visual targets - to quantify the effective connectivity within and between cortical sources in the visual hierarchy in 25 schizophrenia patients and 25 age-matched controls. We found evidence for marked differences between normal subjects and schizophrenia patients in the strength of extrinsic backward connections from higher hierarchical levels to lower levels within the visual system. In addition, we show that not only do schizophrenia subjects have abnormal connectivity but also that they fail to adjust or optimize this connectivity when events can be predicted. Thus, the differential intrinsic recurrent connectivity observed during processing of predictable versus unpredictable targets was markedly attenuated in schizophrenia patients compared with controls, suggesting a failure to modulate the sensitivity of neurons responsible for passing sensory information of prediction errors up the visual cortical hierarchy. The findings support the proposed role of abnormal connectivity in the neuropathology and pathophysiology of schizophrenia.


Connectivity; Dynamic causal modeling; EEG; Prediction; Schizophrenia

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