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  Modeling subjective relevance in schizophrenia and its relation to aberrant salience

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.

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Katthagen, Teresa 1, 2, 3, 4, 5, Author
Mathys, Christoph 6, 7, 8, Author
Deserno, Lorenz1, 2, 3, 4, 9, 10, Author           
Walter, Henrik 1, 2, 3, 4, Author
Kathmann, Norbert 11, Author
Heinz, Andreas 1, 2, 3, 4, Author
Schlagenhauf, Florian1, 2, 3, 4, 10, Author           
1Charité University Medicine Berlin, Germany, ou_persistent22              
2FU Berlin, Germany, ou_persistent22              
3Humboldt University Berlin, Germany, ou_persistent22              
4Berlin Institute of Health (BIH), Germany, ou_persistent22              
5Berlin School of Mind and Brain, Humboldt University Berlin, Germany, ou_persistent22              
6Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste, Italy, ou_persistent22              
7Max Planck UCL Centre for Computational Psychiatry and Ageing Research, London, United Kingdom, ou_persistent22              
8Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, United Kingdom, ou_persistent22              
9Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics, University of Leipzig, Germany, ou_persistent22              
10Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
11Department of Psychology, Humboldt University Berlin, Germany, ou_persistent22              


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 Abstract: 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.


Language(s): eng - English
 Dates: 2017-10-272018-06-202018-08-10
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1371/journal.pcbi.1006319
PMID: 30096179
PMC: PMC6105009
Other: eCollection 2018
 Degree: -



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Project name : -
Grant ID : SCHL 1969/1-2 ; SCHL 1969/2-2 ; SCHL 1969/3-1 ; SCHL 1969/4-1
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Funding organization : German Research Foundation (DFG)
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Funding organization : Max Planck Society
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Funding program : Elsa Neumann Scholarship
Funding organization : Humboldt Universität zu Berlin
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Funding program : -
Funding organization : Berlin School of Mind and Brain
Project name : -
Grant ID : 01GQ0411 ; 01QG87164 ; NGFN Plus 01 GS 08152 ; 01 GS 08159
Funding program : -
Funding organization : German Federal Ministry of Education and Research (BMBF)

Source 1

Title: PLoS Computational Biology
Source Genre: Journal
Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 14 (8) Sequence Number: e1006319 Start / End Page: - Identifier: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1