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@ARTICLE{Magielse:1047331,
author = {Magielse, Neville and Manoli, Aikaterina and Eickhoff,
Simon B. and Fox, Peter T. and Saberi, Amin and Valk, Sofie
L.},
title = {{A} bias-accounting meta-analytic approach refines and
expands the cerebellar behavioral topography},
journal = {Neuroscience $\&$ biobehavioral reviews},
volume = {179},
issn = {0149-7634},
address = {Amsterdam [u.a.]},
publisher = {Elsevier Science},
reportid = {FZJ-2025-04240},
pages = {106418 -},
year = {2025},
abstract = {The 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.},
cin = {INM-7},
ddc = {610},
cid = {I:(DE-Juel1)INM-7-20090406},
pnm = {5251 - Multilevel Brain Organization and Variability
(POF4-525)},
pid = {G:(DE-HGF)POF4-5251},
typ = {PUB:(DE-HGF)16},
pubmed = {41086937},
UT = {WOS:001382263100001},
doi = {10.1016/j.neubiorev.2025.106418},
url = {https://juser.fz-juelich.de/record/1047331},
}