001023816 001__ 1023816
001023816 005__ 20250204113811.0
001023816 0247_ $$2doi$$a10.1016/j.nicl.2024.103586
001023816 0247_ $$2datacite_doi$$a10.34734/FZJ-2024-01821
001023816 0247_ $$2pmid$$a38428325
001023816 0247_ $$2WOS$$aWOS:001218586600001
001023816 037__ $$aFZJ-2024-01821
001023816 082__ $$a610
001023816 1001_ $$0P:(DE-HGF)0$$aKoob, Janusz L$$b0$$eFirst author
001023816 245__ $$aBehavioral and neuroanatomical correlates of facial emotion processing in post-stroke depression
001023816 260__ $$a[Amsterdam u.a.]$$bElsevier$$c2024
001023816 3367_ $$2DRIVER$$aarticle
001023816 3367_ $$2DataCite$$aOutput Types/Journal article
001023816 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1709899834_2953
001023816 3367_ $$2BibTeX$$aARTICLE
001023816 3367_ $$2ORCID$$aJOURNAL_ARTICLE
001023816 3367_ $$00$$2EndNote$$aJournal Article
001023816 520__ $$aAbstractBackground: Emotion processing deficits are known to accompany depressive symptoms and are often seen in stroke patients. Little is known about the influence of post-stroke depressive (PSD) symptoms and specific brain lesions on altered emotion processing abilities and how these phenomena develop over time. This potential relationship may impact post-stroke rehabilitation of neurological and psychosocial function. To address this scientific gap, we investigated the relationship between PSD symptoms and emotion processing abilities in a longitudinal study design from the first days post-stroke into the early chronic phase.Methods: Twenty-six ischemic stroke patients performed an emotion processing task on videos with emotional faces ('happy,' 'sad,' 'anger,' 'fear,' and 'neutral') at different intensity levels (20%, 40%, 60%, 80%, 100%). Recognition accuracies and response times were measured, as well as scores of depressive symptoms (Montgomery-Åsberg Depression Rating Scale). Twenty-eight healthy participants matched in age and sex were included as a control group. Whole-brain support-vector regression lesion-symptom mapping (SVR-LSM) analyses were performed to investigate whether specific lesion locations were associated with the recognition accuracy of specific emotion categories.Results: Stroke patients performed worse in overall recognition accuracy compared to controls, specifically in the recognition of happy, sad, and fearful faces. Notably, more depressed stroke patients showed an increased processing towards specific negative emotions, as they responded significantly faster to angry faces and recognized sad faces of low intensities significantly more accurately. These effects obtained for the first days after stroke partly persisted to follow-up assessment several months later. SVR-LSM analyses revealed that inferior and middle frontal regions (IFG/MFG) and insula and putamen were associated with emotion-recognition deficits in stroke. Specifically, recognizing happy facial expressions was influenced by lesions affecting the anterior insula, putamen, IFG, MFG, orbitofrontal cortex, and rolandic operculum. Lesions in the posterior insula, rolandic operculum, and MFG were also related to reduced recognition accuracy of fearful facial expressions, whereas recognition deficits of sad faces were associated with frontal pole, IFG, and MFG damage.Conclusion: PSD symptoms facilitate processing negative emotional stimuli, specifically angry and sad facial expressions. The recognition accuracy of different emotional categories was linked to brain lesions in emotion-related processing circuits, including insula, basal ganglia, IFG, and MFG. In summary, our study provides support for psychosocial and neural factors underlying emotional processing after stroke, contributing to the pathophysiology of PSD.Keywords: Dynamic faces; Emotion processing; Longitudinal; Multivariate SVR-LSM; PSD.
001023816 536__ $$0G:(DE-HGF)POF4-5251$$a5251 - Multilevel Brain Organization and Variability (POF4-525)$$cPOF4-525$$fPOF IV$$x0
001023816 536__ $$0G:(GEPRIS)310098283$$aDFG project 310098283 - Neurale Grundlagen der Interaktion von Post-stroke Depression und motorischer Rehabilitation nach Schlaganfall (310098283)$$c310098283$$x1
001023816 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de
001023816 7001_ $$0P:(DE-HGF)0$$aGorski, Maximilian$$b1
001023816 7001_ $$0P:(DE-HGF)0$$aKrick, Sebastian$$b2
001023816 7001_ $$0P:(DE-Juel1)201297$$aMustin, Maike$$b3$$ufzj
001023816 7001_ $$0P:(DE-Juel1)131720$$aFink, Gereon R.$$b4$$ufzj
001023816 7001_ $$0P:(DE-Juel1)161406$$aGrefkes, Christian$$b5$$eCorresponding author
001023816 7001_ $$0P:(DE-Juel1)165784$$aRehme, Anne K.$$b6
001023816 773__ $$0PERI:(DE-600)2701571-3$$a10.1016/j.nicl.2024.103586$$gVol. 41, p. 103586 -$$p103586 -$$tNeuroImage: Clinical$$v41$$x2213-1582$$y2024
001023816 8564_ $$uhttps://juser.fz-juelich.de/record/1023816/files/PDF.pdf$$yOpenAccess
001023816 8564_ $$uhttps://juser.fz-juelich.de/record/1023816/files/PDF.gif?subformat=icon$$xicon$$yOpenAccess
001023816 8564_ $$uhttps://juser.fz-juelich.de/record/1023816/files/PDF.jpg?subformat=icon-1440$$xicon-1440$$yOpenAccess
001023816 8564_ $$uhttps://juser.fz-juelich.de/record/1023816/files/PDF.jpg?subformat=icon-180$$xicon-180$$yOpenAccess
001023816 8564_ $$uhttps://juser.fz-juelich.de/record/1023816/files/PDF.jpg?subformat=icon-640$$xicon-640$$yOpenAccess
001023816 909CO $$ooai:juser.fz-juelich.de:1023816$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire
001023816 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)201297$$aForschungszentrum Jülich$$b3$$kFZJ
001023816 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131720$$aForschungszentrum Jülich$$b4$$kFZJ
001023816 9131_ $$0G:(DE-HGF)POF4-525$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5251$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vDecoding Brain Organization and Dysfunction$$x0
001023816 9141_ $$y2024
001023816 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
001023816 915__ $$0LIC:(DE-HGF)CCBYNCND4$$2HGFVOC$$aCreative Commons Attribution-NonCommercial-NoDerivs CC BY-NC-ND 4.0
001023816 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2023-04-12T14:49:23Z
001023816 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2023-04-12T14:49:23Z
001023816 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Anonymous peer review$$d2023-04-12T14:49:23Z
001023816 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bNEUROIMAGE-CLIN : 2022$$d2025-01-01
001023816 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2025-01-01
001023816 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2025-01-01
001023816 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2025-01-01
001023816 915__ $$0StatID:(DE-HGF)1110$$2StatID$$aDBCoverage$$bCurrent Contents - Clinical Medicine$$d2025-01-01
001023816 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2025-01-01
001023816 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2025-01-01
001023816 920__ $$lyes
001023816 9201_ $$0I:(DE-Juel1)INM-3-20090406$$kINM-3$$lKognitive Neurowissenschaften$$x0
001023816 980__ $$ajournal
001023816 980__ $$aVDB
001023816 980__ $$aUNRESTRICTED
001023816 980__ $$aI:(DE-Juel1)INM-3-20090406
001023816 9801_ $$aFullTexts