001047331 001__ 1047331
001047331 005__ 20251023202112.0
001047331 0247_ $$2doi$$a10.1016/j.neubiorev.2025.106418
001047331 0247_ $$2ISSN$$a0149-7634
001047331 0247_ $$2ISSN$$a1873-7528
001047331 0247_ $$2datacite_doi$$a10.34734/FZJ-2025-04240
001047331 037__ $$aFZJ-2025-04240
001047331 082__ $$a610
001047331 1001_ $$0P:(DE-Juel1)188899$$aMagielse, Neville$$b0
001047331 245__ $$aA bias-accounting meta-analytic approach refines and expands the cerebellar behavioral topography
001047331 260__ $$aAmsterdam [u.a.]$$bElsevier Science$$c2025
001047331 3367_ $$2DRIVER$$aarticle
001047331 3367_ $$2DataCite$$aOutput Types/Journal article
001047331 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1761210444_10069
001047331 3367_ $$2BibTeX$$aARTICLE
001047331 3367_ $$2ORCID$$aJOURNAL_ARTICLE
001047331 3367_ $$00$$2EndNote$$aJournal Article
001047331 520__ $$aThe cerebellum plays important roles in motor, cognitive, and emotional behaviors. Previous cerebellar coordinate-based meta-analyses (CBMAs) have complemented precision-mapping and parcellation approaches by finding generalizable cerebellar activations across the largest possible set of behaviors. However, cerebellar CBMAs face challenges due to inherent methodological limitations, exacerbated by historical cerebellar neglect in neuroimaging studies. Here, we show overrepresentation of superior activations, rendering the null hypothesis of standard activation likelihood estimation (ALE) unsuitable. Our new method, cerebellum-specific ALE (C-SALE), finds behavioral convergence beyond baseline activation rates. It does this by testing experimental activations versus null models sampled from a data-driven probability distribution of finding activations at any cerebellar location. Task-specific mappings in the BrainMap meta-analytic database illustrated improved specificity of the new method. Multiple (sub)domains reached convergence in specific cerebellar subregions, supporting dual motor representations and placing cognition in posterior-lateral regions. We show our method and findings are replicable using the NeuroSynth database. Across both databases, 54/138 task domains or behavioral terms, including sustained attention, somesthesis, inference, anticipation and rhythm, reached convergence in specific cerebellar subgregions. Our meta-analyic maps largely corresponded with cerebellar atlases but also showed many complementary mappings. Repeated subsampling analysis showed that motor behaviors, and to a lesser extent language and working memory, mapped to especially consistent cerebellar subregions. Lastly, we found that cerebellar clusters were parts of brain-wide coactivation networks with cortical and subcortical regions implied in these behaviors. Together, our method further complements and expands understanding of cerebellar involvement in human behavior, highlighting regions for future investigation in both basic and clinical applications.
001047331 536__ $$0G:(DE-HGF)POF4-5251$$a5251 - Multilevel Brain Organization and Variability (POF4-525)$$cPOF4-525$$fPOF IV$$x0
001047331 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de
001047331 7001_ $$0P:(DE-HGF)0$$aManoli, Aikaterina$$b1
001047331 7001_ $$0P:(DE-Juel1)131678$$aEickhoff, Simon B.$$b2$$ufzj
001047331 7001_ $$0P:(DE-HGF)0$$aFox, Peter T.$$b3
001047331 7001_ $$0P:(DE-Juel1)190448$$aSaberi, Amin$$b4$$ufzj
001047331 7001_ $$0P:(DE-Juel1)173843$$aValk, Sofie L.$$b5$$eCorresponding author$$ufzj
001047331 773__ $$0PERI:(DE-600)1498433-7$$a10.1016/j.neubiorev.2025.106418$$gVol. 179, p. 106418 -$$p106418 -$$tNeuroscience & biobehavioral reviews$$v179$$x0149-7634$$y2025
001047331 8564_ $$uhttps://juser.fz-juelich.de/record/1047331/files/1-s2.0-S0149763425004191-main.pdf$$yOpenAccess
001047331 909CO $$ooai:juser.fz-juelich.de:1047331$$popenaire$$popen_access$$pVDB$$pdriver$$pdnbdelivery
001047331 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)188899$$aForschungszentrum Jülich$$b0$$kFZJ
001047331 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131678$$aForschungszentrum Jülich$$b2$$kFZJ
001047331 9101_ $$0I:(DE-HGF)0$$6P:(DE-Juel1)131678$$a HHU Düsseldorf$$b2
001047331 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)190448$$aForschungszentrum Jülich$$b4$$kFZJ
001047331 9101_ $$0I:(DE-HGF)0$$6P:(DE-Juel1)190448$$a Otto Hahn Cognitive Neurogenetics Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig$$b4
001047331 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)173843$$aForschungszentrum Jülich$$b5$$kFZJ
001047331 9101_ $$0I:(DE-HGF)0$$6P:(DE-Juel1)173843$$a Max Planck Institute for Human Cognitive and Brain Sciences, Dr. Sofie L. Valk, Stephanstraße 1A, Leipzig$$b5
001047331 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$$x0
001047331 9141_ $$y2025
001047331 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2024-12-18
001047331 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2024-12-18
001047331 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2024-12-18
001047331 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
001047331 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2024-12-18
001047331 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bNEUROSCI BIOBEHAV R : 2022$$d2024-12-18
001047331 915__ $$0StatID:(DE-HGF)1030$$2StatID$$aDBCoverage$$bCurrent Contents - Life Sciences$$d2024-12-18
001047331 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2024-12-18
001047331 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2024-12-18
001047331 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
001047331 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2024-12-18
001047331 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bNEUROSCI BIOBEHAV R : 2022$$d2024-12-18
001047331 915__ $$0StatID:(DE-HGF)1120$$2StatID$$aDBCoverage$$bBIOSIS Reviews Reports And Meetings$$d2024-12-18
001047331 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2024-12-18
001047331 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz$$d2024-12-18$$wger
001047331 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2024-12-18
001047331 9201_ $$0I:(DE-Juel1)INM-7-20090406$$kINM-7$$lGehirn & Verhalten$$x0
001047331 980__ $$ajournal
001047331 980__ $$aVDB
001047331 980__ $$aUNRESTRICTED
001047331 980__ $$aI:(DE-Juel1)INM-7-20090406
001047331 9801_ $$aFullTexts