Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Zeitschriftenartikel

Modeling subjective relevance in schizophrenia and its relation to aberrant salience

MPG-Autoren
/persons/resource/persons104604

Deserno,  Lorenz
Charité University Medicine Berlin, Germany;
FU Berlin, Germany;
Humboldt University Berlin, Germany;
Berlin Institute of Health (BIH), Germany;
Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics, University of Leipzig, Germany;
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

/persons/resource/persons96505

Schlagenhauf,  Florian
Charité University Medicine Berlin, Germany;
FU Berlin, Germany;
Humboldt University Berlin, Germany;
Berlin Institute of Health (BIH), Germany;
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

Externe Ressourcen
Es sind keine externen Ressourcen hinterlegt
Volltexte (beschränkter Zugriff)
Für Ihren IP-Bereich sind aktuell keine Volltexte freigegeben.
Volltexte (frei zugänglich)

Katthagen_Mathys_2018.pdf
(Verlagsversion), 4MB

Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Katthagen, T., Mathys, C., Deserno, L., Walter, H., Kathmann, N., Heinz, A., et al. (2018). Modeling subjective relevance in schizophrenia and its relation to aberrant salience. PLoS Computational Biology, 14(8): e1006319. doi:10.1371/journal.pcbi.1006319.


Zitierlink: https://hdl.handle.net/21.11116/0000-0002-4E8D-9
Zusammenfassung
In schizophrenia, increased aberrant salience to irrelevant events and reduced learning of relevant information may relate to an underlying deficit in relevance detection. So far, subjective estimates of relevance have not been probed in schizophrenia patients. The mechanisms underlying belief formation about relevance and their translation into decisions are unclear. Using novel computational methods, we investigated relevance detection during implicit learning in 42 schizophrenia patients and 42 healthy individuals. Participants underwent functional magnetic resonance imaging while detecting the outcomes in a learning task. These were preceded by cues differing in color and shape, which were either relevant or irrelevant for outcome prediction. We provided a novel definition of relevance based on Bayesian precision and modeled reaction times as a function of relevance weighted unsigned prediction errors (UPE). For aberrant salience, we assessed responses to subjectively irrelevant cue manifestations. Participants learned the contingencies and slowed down their responses following unexpected events. Model selection revealed that individuals inferred the relevance of cue features and used it for behavioral adaption to the relevant cue feature. Relevance weighted UPEs correlated with dorsal anterior cingulate cortex activation and hippocampus deactivation. In patients, the aberrant salience bias to subjectively task-irrelevant information was increased and correlated with decreased striatal UPE activation and increased negative symptoms. This study shows that relevance estimates based on Bayesian precision can be inferred from observed behavior. This underscores the importance of relevance detection as an underlying mechanism for behavioral adaptation in complex environments and enhances the understanding of aberrant salience in schizophrenia.