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@ARTICLE{Magielse:1034021,
      author       = {Magielse, Neville and Manoli, Aikaterina and Eickhoff,
                      Simon B. and Fox, Peter T. and Saberi, Amin and Valk, Sofie
                      L.},
      title        = {{B}ias-accounting meta-analyses overcome cerebellar neglect
                      to refine the cerebellar behavioral topography},
      reportid     = {FZJ-2024-06851},
      year         = {2024},
      abstract     = {The cerebellum plays important roles in motor, cognitive,
                      and emotional behaviors. Previous cerebellar
                      coordinate-based meta-analyses and mappings have attributed
                      different behaviors to cerebellar subareas, but an accurate
                      behavioral topography is lacking. Here, we show
                      overrepresentation of superior activation foci, which may be
                      exacerbated by historical cerebellar neglect. Unequal foci
                      distributions render the null hypothesis of standard
                      activation likelihood estimation unsuitable. Our new method,
                      cerebellum-specific activation-likelihood estimation
                      (C-SALE), finds behavioral convergence beyond baseline
                      activation rates. It does this by testing experimental foci
                      versus null models sampled from a data-driven, biased
                      probability distribution of finding foci at any cerebellar
                      location. Cerebellar mappings were made across five BrainMap
                      task domains and thirty-five subdomains, illustrating
                      improved specificity of the new method. Twelve of forty
                      (sub)domains reached convergence in specific cerebellar
                      subregions, supporting dual motor representations and
                      placing cognition in posterior-lateral regions. Repeated
                      subsampling revealed that whereas action, language and
                      working memory were relatively stable, other behaviors
                      produced unstable meta-analytic maps. Lastly, meta-analytic
                      connectivity modeling in the same debiased framework was
                      used to reveal coactivation networks of cerebellar
                      behavioral clusters. In sum, we created a new method for
                      cerebellar meta-analysis that accounts for data biases and
                      can be flexibly adapted to any part of the brain. Our
                      findings provide a refined understanding of cerebellar
                      involvement in human behaviors, highlighting regions for
                      future investigation in both basic and clinical
                      applications.},
      cin          = {INM-7},
      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)25},
      doi          = {10.1101/2024.10.31.621398},
      url          = {https://juser.fz-juelich.de/record/1034021},
}