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  BrainStat: A toolbox for brain-wide statistics and multimodal feature associations

Larivière, S., Bayrak, S., de Wael, R. V., Benkarim, O., Herholz, P., Rodriguez-Cruces, R., et al. (2023). BrainStat: A toolbox for brain-wide statistics and multimodal feature associations. NeuroImage, 266: 119807. doi:10.1016/j.neuroimage.2022.119807.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000C-0240-9 Version Permalink: https://hdl.handle.net/21.11116/0000-000F-86D3-B
Genre: Journal Article

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 Creators:
Larivière, Sara1, Author
Bayrak, Seyma2, Author                 
de Wael, Reinder Vos1, Author
Benkarim, Oualid1, Author
Herholz, Peer1, Author
Rodriguez-Cruces, Raul1, Author
Paquola, Casey3, Author
Hong, Seok-Jun4, 5, Author
Misic, Bratislav1, Author
Evans, Alan C.1, Author
Valk, Sofie L.2, 3, Author                 
Bernhardt, Boris C.1, Author
Affiliations:
1McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, QC, Canada, ou_persistent22              
2Otto Hahn Group Cognitive Neurogenetics, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_3222264              
3Institute of Neuroscience and Medicine, Research Center Jülich, Germany, ou_persistent22              
4Child Mind Institute, New York, NY, USA, ou_persistent22              
5Department of Biomedical Engineering, Sungkyunkwan University, Seoul, South Korea, ou_persistent22              

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Free keywords: Neuroimaging; Multivariate analysis; Univariate analysis
 Abstract: Analysis and interpretation of neuroimaging datasets has become a multidisciplinary endeavor, relying not only on statistical methods, but increasingly on associations with respect to other brain-derived features such as gene expression, histological data, and functional as well as cognitive architectures. Here, we introduce BrainStat - a toolbox for (i) univariate and multivariate linear models in volumetric and surface-based brain imaging datasets, and (ii) multidomain feature association of results with respect to spatial maps of post-mortem gene expression and histology, task-based fMRI meta-analysis, as well as resting-state fMRI motifs across several common surface templates. The combination of statistics and feature associations into a turnkey toolbox streamlines analytical processes and accelerates cross-modal research. The toolbox is implemented in both Python and MATLAB, two widely used programming languages in the neuroimaging and neuroinformatics communities. BrainStat is openly available and complemented by an expandable documentation.

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Language(s): eng - English
 Dates: 2022-11-282022-12-092022-12-102023-02-01
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1016/j.neuroimage.2022.119807
Other: epub 2022
PMID: 36513290
 Degree: -

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Project name : -
Grant ID : NIH-NIBIB P41 EB019936
Funding program : -
Funding organization : National Institutes of Health (NIH)
Project name : -
Grant ID : R01MH096906
Funding program : -
Funding organization : National Institute Of Mental Health (NIMH)
Project name : -
Grant ID : 28436
Funding program : -
Funding organization : Brain & Behavior Research Foundation (BBRF)
Project name : -
Grant ID : IBS-R15-D1
Funding program : -
Funding organization : Institute for Basic Science (IBS)
Project name : -
Grant ID : NSERC Discovery-1304413
Funding program : -
Funding organization : National Science and Engineering Research Council of Canada (NSERC)
Project name : -
Grant ID : FDN-154298, PJT174995
Funding program : -
Funding organization : Canadian Institutes of Health Research (CIHR)
Project name : -
Grant ID : NI17-039
Funding program : -
Funding organization : SickKids Foundation

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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 266 Sequence Number: 119807 Start / End Page: - Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166