A standardized image processing and data quality platform for rodent fMRI
Abstract Functional magnetic resonance imaging in rodents holds great potential for advancing our understanding of brain networks. Unlike the human community, there remains no standardized resource in rodents for image processing, analysis and quality control, posing significant reproducibility limi...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-08-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-50826-8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832571520733413376 |
|---|---|
| author | Gabriel Desrosiers-Grégoire Gabriel A. Devenyi Joanes Grandjean M. Mallar Chakravarty |
| author_facet | Gabriel Desrosiers-Grégoire Gabriel A. Devenyi Joanes Grandjean M. Mallar Chakravarty |
| author_sort | Gabriel Desrosiers-Grégoire |
| collection | DOAJ |
| description | Abstract Functional magnetic resonance imaging in rodents holds great potential for advancing our understanding of brain networks. Unlike the human community, there remains no standardized resource in rodents for image processing, analysis and quality control, posing significant reproducibility limitations. Our software platform, Rodent Automated Bold Improvement of EPI Sequences, is a pipeline designed to address these limitations for preprocessing, quality control, and confound correction, along with best practices for reproducibility and transparency. We demonstrate the robustness of the preprocessing workflow by validating performance across multiple acquisition sites and both mouse and rat data. Building upon a thorough investigation into data quality metrics across acquisition sites, we introduce guidelines for the quality control of network analysis and offer recommendations for addressing issues. Taken together, this software platform will allow the emerging community to adopt reproducible practices and foster progress in translational neuroscience. |
| format | Article |
| id | doaj-art-6cb5a79e9c4e4241bff2030ec42ba974 |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2024-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-6cb5a79e9c4e4241bff2030ec42ba9742025-02-02T12:30:54ZengNature PortfolioNature Communications2041-17232024-08-0115111510.1038/s41467-024-50826-8A standardized image processing and data quality platform for rodent fMRIGabriel Desrosiers-Grégoire0Gabriel A. Devenyi1Joanes Grandjean2M. Mallar Chakravarty3Computational Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University InstituteComputational Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University InstituteDonders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterComputational Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University InstituteAbstract Functional magnetic resonance imaging in rodents holds great potential for advancing our understanding of brain networks. Unlike the human community, there remains no standardized resource in rodents for image processing, analysis and quality control, posing significant reproducibility limitations. Our software platform, Rodent Automated Bold Improvement of EPI Sequences, is a pipeline designed to address these limitations for preprocessing, quality control, and confound correction, along with best practices for reproducibility and transparency. We demonstrate the robustness of the preprocessing workflow by validating performance across multiple acquisition sites and both mouse and rat data. Building upon a thorough investigation into data quality metrics across acquisition sites, we introduce guidelines for the quality control of network analysis and offer recommendations for addressing issues. Taken together, this software platform will allow the emerging community to adopt reproducible practices and foster progress in translational neuroscience.https://doi.org/10.1038/s41467-024-50826-8 |
| spellingShingle | Gabriel Desrosiers-Grégoire Gabriel A. Devenyi Joanes Grandjean M. Mallar Chakravarty A standardized image processing and data quality platform for rodent fMRI Nature Communications |
| title | A standardized image processing and data quality platform for rodent fMRI |
| title_full | A standardized image processing and data quality platform for rodent fMRI |
| title_fullStr | A standardized image processing and data quality platform for rodent fMRI |
| title_full_unstemmed | A standardized image processing and data quality platform for rodent fMRI |
| title_short | A standardized image processing and data quality platform for rodent fMRI |
| title_sort | standardized image processing and data quality platform for rodent fmri |
| url | https://doi.org/10.1038/s41467-024-50826-8 |
| work_keys_str_mv | AT gabrieldesrosiersgregoire astandardizedimageprocessinganddataqualityplatformforrodentfmri AT gabrieladevenyi astandardizedimageprocessinganddataqualityplatformforrodentfmri AT joanesgrandjean astandardizedimageprocessinganddataqualityplatformforrodentfmri AT mmallarchakravarty astandardizedimageprocessinganddataqualityplatformforrodentfmri AT gabrieldesrosiersgregoire standardizedimageprocessinganddataqualityplatformforrodentfmri AT gabrieladevenyi standardizedimageprocessinganddataqualityplatformforrodentfmri AT joanesgrandjean standardizedimageprocessinganddataqualityplatformforrodentfmri AT mmallarchakravarty standardizedimageprocessinganddataqualityplatformforrodentfmri |