Characterization and prediction of clinical pathways of vulnerability to psychosis through graph signal processing

Characterization and prediction of clinical pathways of vulnerability to psychosis through graph signal processing

Causal interactions between specific psychiatric symptoms could contribute to the heterogenous clinical trajectories observed in early psychopathology. Current diagnostic approaches merge clinical manifestations that co-occur across subjects and could significantly hinder our understanding of clinic...

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Bibliographic Details
Main Authors: Corrado Sandini, Daniela Zöller, Maude Schneider, Anjali Tarun, Marco Armondo, Barnaby Nelson, Paul G Amminger, Hok Pan Yuen, Connie Markulev, Monica R Schäffer, Nilufar Mossaheb, Monika Schlögelhofer, Stefan Smesny, Ian B Hickie, Gregor Emanuel Berger, Eric YH Chen, Lieuwe de Haan, Dorien H Nieman, Merete Nordentoft, Anita Riecher-Rössler, Swapna Verma, Andrew Thompson, Alison Ruth Yung, Patrick D McGorry, Dimitri Van De Ville, Stephan Eliez
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2021-09-01
Series:eLife
Subjects:
schizophrenia
network analysis
22q11.2 deletion syndrome
affective pathway
Online Access:https://elifesciences.org/articles/59811

Internet

https://elifesciences.org/articles/59811

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