Image-based meta-and mega-analysis (IBMMA): A unified framework for large-scale, multi-site, neuroimaging data analysis

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F25%3A00082399" target="_blank" >RIV/00159816:_____/25:00082399 - isvavai.cz</a>
Alternative codes found
RIV/00216224:14740/25:00142813
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S1053811925005579" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1053811925005579</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.neuroimage.2025.121554" target="_blank" >10.1016/j.neuroimage.2025.121554</a>

Result language
angličtina
Original language name
Image-based meta-and mega-analysis (IBMMA): A unified framework for large-scale, multi-site, neuroimaging data analysis
Original language description
The increasing scale and complexity of neuroimaging datasets aggregated from multiple study sites present substantial analytic challenges, as existing statistical analysis tools struggle to handle missing voxel-data, suffer from limited computational speed and inefficient memory allocation, and are restricted in the types of statistical designs they are able to model. We introduce Image-Based Meta-& Mega-Analysis (IBMMA), a novel software package implemented in R and Python that provides a unified framework for analyzing diverse neuroimaging features, efficiently handles large-scale datasets through parallel processing, offers flexible statistical modeling options, and properly manages missing voxel-data commonly encountered in multi-site studies. IBMMA successfully analyzed a large-n dataset of several thousand participants and revealed findings in brain regions that some traditional software overlooked due to missing voxel-data resulting in gaps in brain coverage. IBMMA has the potential to accelerate discoveries in neuroscience and enhance the clinical utility of neuroimaging findings.
Czech name
—
Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30103 - Neurosciences (including psychophysiology)

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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