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  Different shades of default mode disturbance in schizophrenia: Subnodal covariance estimation in structure and function

Lefort-Besnard, J., Bassett, D. S., Smallwood, J., Margulies, D. S., Derntl, B., Gruber, O., et al. (2018). Different shades of default mode disturbance in schizophrenia: Subnodal covariance estimation in structure and function. Human Brain Mapping, 39(2), 644-661. doi:10.1002/hbm.23870.

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https://onlinelibrary.wiley.com/doi/10.1002/hbm.23870 (Verlagsversion)
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Lefort-Besnard, Jérémy1, Autor
Bassett, Danielle S.2, 3, Autor
Smallwood, Jonathan4, Autor           
Margulies, Daniel S.5, Autor           
Derntl, Birgit1, 6, 7, Autor
Gruber, Oliver8, Autor
Aleman, Andre9, Autor
Jardri, Renaud10, Autor
Varoquaux, Gaël11, Autor
Thirion, Bertrand11, Autor
Eickhoff, Simon B.12, 13, Autor
Bzdok, Danilo1, 6, 11, Autor
Affiliations:
1Department of Psychiatry, Psychotherapy, and Psychosomatics, RWTH Aachen University, Germany, ou_persistent22              
2Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA, ou_persistent22              
3Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA, ou_persistent22              
4Department of Psychology, University of York, Heslington, United Kingdom, ou_persistent22              
5Max Planck Research Group Neuroanatomy and Connectivity, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_1356546              
6Jülich Aachen Research Alliance - JARA BRAIN, Jülich, Germany, ou_persistent22              
7Department for Psychiatry and Psychotherapy, Eberhard Karls University Tübingen, Germany, ou_persistent22              
8Department of Psychiatry, University of Heidelberg, Germany, ou_persistent22              
9University Medical Center Groningen, the Netherlands, ou_persistent22              
10Division of Psychiatry, University of Lille, France, ou_persistent22              
11Neurospin, French Alternative Energies and Atomic Energy Commission (CEA), Saclay, France, ou_persistent22              
12Institute of Systems Neuroscience, University Hospital Düsseldorf, Germany, ou_persistent22              
13Institute of Neuroscience and Medicine, Research Center Jülich, Germany, ou_persistent22              

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Schlagwörter: Default mode network proper; Functional connectivity; Machine learning; Neuroimaging; Schizophrenia; Sparse inverse covariance estimation; Structural covariance; Sparsity
 Zusammenfassung: Schizophrenia is a devastating mental disease with an apparent disruption in the highly associative default mode network (DMN). Interplay between this canonical network and others probably contributes to goal-directed behavior so its disturbance is a candidate neural fingerprint underlying schizophrenia psychopathology. Previous research has reported both hyperconnectivity and hypoconnectivity within the DMN, and both increased and decreased DMN coupling with the multimodal saliency network (SN) and dorsal attention network (DAN). This study systematically revisited network disruption in patients with schizophrenia using data-derived network atlases and multivariate pattern-learning algorithms in a multisite dataset (n = 325). Resting-state fluctuations in unconstrained brain states were used to estimate functional connectivity, and local volume differences between individuals were used to estimate structural co-occurrence within and between the DMN, SN, and DAN. In brain structure and function, sparse inverse covariance estimates of network coupling were used to characterize healthy participants and patients with schizophrenia, and to identify statistically significant group differences. Evidence did not confirm that the backbone of the DMN was the primary driver of brain dysfunction in schizophrenia. Instead, functional and structural aberrations were frequently located outside of the DMN core, such as in the anterior temporoparietal junction and precuneus. Additionally, functional covariation analyses highlighted dysfunctional DMN-DAN coupling, while structural covariation results highlighted aberrant DMN-SN coupling. Our findings reframe the role of the DMN core and its relation to canonical networks in schizophrenia. We thus underline the importance of large-scale neural interactions as effective biomarkers and indicators of how to tailor psychiatric care to single patients.

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Sprache(n): eng - English
 Datum: 2017-10-202017-09-252017-10-202017-11-032018-02
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1002/hbm.23870
PMID: 29105239
PMC: PMC5764781
Anderer: Epub 2017
 Art des Abschluß: -

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Grant ID : BZ2/2‐1 ; BZ2/3‐1 ; BZ2/4‐1
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Förderorganisation : Deutsche Forschungsgemeinschaft (DFG)
Projektname : The International Research Training Group (IRTG) / IRTG2150
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Förderorganisation : German National Merit Foundation
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Förderorganisation : Faculty of Medicine, RWTH Aachen
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Förderorganisation : John D. and Catherine T. MacArthur Foundation
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Grant ID : W911NF‐10‐2‐0022 ; W911NF‐14‐1‐0679
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Grant ID : 2R01‐DC‐009209‐11
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Förderorganisation : National Institute of Mental Health (NIMH)
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Grant ID : 1R01HD086888‐01
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Grant ID : 103817/Z/14/Z
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Förderorganisation : Welcome Trust
Projektname : Wandering Minds: Interdisciplinary Experiments on Self-Generated Thought
Grant ID : 89440 ; 89439
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Förderorganisation : Volkswagen Foundation
Projektname : Not all minds that wander are lost: A neurocognitive test of mind-wandering state’s contribution to human cognition / WANDERINGMINDS
Grant ID : 646927
Förderprogramm : Funding Programme 7
Förderorganisation : European Commission (EC)

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Titel: Human Brain Mapping
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: New York : Wiley-Liss
Seiten: - Band / Heft: 39 (2) Artikelnummer: - Start- / Endseite: 644 - 661 Identifikator: ISSN: 1065-9471
CoNE: https://pure.mpg.de/cone/journals/resource/954925601686