Cargando…

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

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 an...

Descripción completa

Detalles Bibliográficos
Autores principales: Fogelson, Noa, Litvak, Vladimir, Peled, Avi, Fernandez-del-Olmo, Miguel, Friston, Karl
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Science Publisher B. V 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4166404/
https://www.ncbi.nlm.nih.gov/pubmed/24998031
http://dx.doi.org/10.1016/j.schres.2014.06.011
_version_ 1782335266283847680
author Fogelson, Noa
Litvak, Vladimir
Peled, Avi
Fernandez-del-Olmo, Miguel
Friston, Karl
author_facet Fogelson, Noa
Litvak, Vladimir
Peled, Avi
Fernandez-del-Olmo, Miguel
Friston, Karl
author_sort Fogelson, Noa
collection PubMed
description 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.
format Online
Article
Text
id pubmed-4166404
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Elsevier Science Publisher B. V
record_format MEDLINE/PubMed
spelling pubmed-41664042014-09-19 The functional anatomy of schizophrenia: A dynamic causal modeling study of predictive coding Fogelson, Noa Litvak, Vladimir Peled, Avi Fernandez-del-Olmo, Miguel Friston, Karl Schizophr Res Article 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. Elsevier Science Publisher B. V 2014-09 /pmc/articles/PMC4166404/ /pubmed/24998031 http://dx.doi.org/10.1016/j.schres.2014.06.011 Text en © 2014 The Authors https://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
spellingShingle Article
Fogelson, Noa
Litvak, Vladimir
Peled, Avi
Fernandez-del-Olmo, Miguel
Friston, Karl
The functional anatomy of schizophrenia: A dynamic causal modeling study of predictive coding
title The functional anatomy of schizophrenia: A dynamic causal modeling study of predictive coding
title_full The functional anatomy of schizophrenia: A dynamic causal modeling study of predictive coding
title_fullStr The functional anatomy of schizophrenia: A dynamic causal modeling study of predictive coding
title_full_unstemmed The functional anatomy of schizophrenia: A dynamic causal modeling study of predictive coding
title_short The functional anatomy of schizophrenia: A dynamic causal modeling study of predictive coding
title_sort functional anatomy of schizophrenia: a dynamic causal modeling study of predictive coding
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4166404/
https://www.ncbi.nlm.nih.gov/pubmed/24998031
http://dx.doi.org/10.1016/j.schres.2014.06.011
work_keys_str_mv AT fogelsonnoa thefunctionalanatomyofschizophreniaadynamiccausalmodelingstudyofpredictivecoding
AT litvakvladimir thefunctionalanatomyofschizophreniaadynamiccausalmodelingstudyofpredictivecoding
AT peledavi thefunctionalanatomyofschizophreniaadynamiccausalmodelingstudyofpredictivecoding
AT fernandezdelolmomiguel thefunctionalanatomyofschizophreniaadynamiccausalmodelingstudyofpredictivecoding
AT fristonkarl thefunctionalanatomyofschizophreniaadynamiccausalmodelingstudyofpredictivecoding
AT fogelsonnoa functionalanatomyofschizophreniaadynamiccausalmodelingstudyofpredictivecoding
AT litvakvladimir functionalanatomyofschizophreniaadynamiccausalmodelingstudyofpredictivecoding
AT peledavi functionalanatomyofschizophreniaadynamiccausalmodelingstudyofpredictivecoding
AT fernandezdelolmomiguel functionalanatomyofschizophreniaadynamiccausalmodelingstudyofpredictivecoding
AT fristonkarl functionalanatomyofschizophreniaadynamiccausalmodelingstudyofpredictivecoding