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Micapipe: A pipeline for multimodal neuroimaging and connectome analysis
Raúl R Cruces1, Jessica Royer2, Peer Herholz3
1Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada.
Neuroimage
|September 7, 2022
Summary
Micapipe is an open-source pipeline for multimodal magnetic resonance imaging (MRI) data. It integrates brain microstructure, function, and connectivity across scales for robust neuroscience research.
Area of Science:
- Neuroscience
- Neuroimaging
- Computational Biology
Background:
- Multimodal magnetic resonance imaging (MRI) advances human neuroscience by enabling analysis of brain microstructure, geometry, function, and connectivity.
- Integrating complex multimodal neuroimaging data across scales requires sophisticated processing methods.
Purpose of the Study:
- To introduce micapipe, an open-source processing pipeline for multimodal MRI datasets.
- To facilitate the integration and analysis of diverse neuroimaging data for enhanced brain research.
Main Methods:
- Micapipe processes Brain Imaging Data Structure (BIDS)-conform data.
- It generates structural and functional connectomes, geodesic distance matrices, and microstructural profile covariance matrices.
- The pipeline supports multiple cortical parcellations and surface spaces, ensuring BIDS-conform outputs.
Main Results:
- Micapipe automatically generates various neuroimaging matrices across multiple parcellations and surface spaces.
- Outputs are BIDS-conform and allow for quality control at individual and group levels.
- The pipeline has been tested on multiple datasets and is publicly available.
Conclusions:
- Micapipe provides a robust and integrative framework for multimodal MRI data analysis.
- It aims to foster reproducible and comprehensive studies of human brain microstructure, morphology, function, and connectivity.
