A standardized image processing and data quality platform for rodent fMRI

被引:4
|
作者
Desrosiers-Gregoire, Gabriel [1 ,2 ]
Devenyi, Gabriel A. [1 ,3 ]
Grandjean, Joanes [4 ,5 ]
Chakravarty, M. Mallar [1 ,2 ,3 ,6 ]
机构
[1] Douglas Mental Hlth Univ Inst, Cerebral Imaging Ctr, Computat Brain Anat Lab, Montreal, PQ, Canada
[2] McGill Univ, Integrated Program Neurosci, Montreal, PQ, Canada
[3] McGill Univ, Dept Psychiat, Montreal, PQ, Canada
[4] Radboud Univ Nijmegen, Med Ctr, Donders Inst Brain Cognit & Behav, Nijmegen, Netherlands
[5] Radboud Univ Nijmegen, Med Ctr, Dept Med Imaging, Nijmegen, Netherlands
[6] McGill Univ, Dept Biol & Biomed Engn, Montreal, PQ, Canada
基金
加拿大健康研究院; 荷兰研究理事会;
关键词
FUNCTIONAL CONNECTIVITY; MOTION ARTIFACT; BRAIN; PROTOCOL; SEGMENTATION; NETWORKS; ATLAS;
D O I
10.1038/s41467-024-50826-8
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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. There is a need for a standardized pipeline to process rodent fMRI images. Here, the authors present a platform for preprocessing, quality control and confound correction, and demonstrate its robustness across multiple sites and both mouse and rat data.
引用
收藏
页数:15
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