micapipe

micapipe processes multimodal MRI datasets to extract and summarize brain microstructure, cortical geometry, functional connectivity, and structural connectivity across multiple spatial scales for human neuroimaging studies.


Key Features:

  • Integration Across Modalities: Processes MRI data conforming to the Brain Imaging Data Structure (BIDS) format to integrate multiple imaging modalities.
  • Connectome Generation: Generates structural connectomes using diffusion tractography and functional connectomes using resting-state signal correlations.
  • Geodesic Distance Matrices: Computes cortico-cortical geodesic distance matrices to quantify cortical proximity.
  • Microstructural Profile Covariance: Computes microstructural profile covariance matrices to assess inter-regional similarity in cortical myelin proxies.
  • Spatial Scale Flexibility: Supports 18 established cortical parcellations ranging from 100 to 1,000 parcels and includes subcortical and cerebellar parcellations.
  • Surface Space Representation: Represents outputs on native, conte69, and fsaverage5 surface spaces.
  • Quality Control: Provides processed outputs that can be quality controlled at individual and group levels.

Scientific Applications:

  • Integrative Multimodal Analysis: Enables combined analysis of brain microstructure, morphology, function, and connectivity using multimodal MRI data.
  • Anatomical Studies: Supports basic anatomical investigations of cortical organization and myelination patterns.
  • Network and Functional Investigations: Facilitates analyses of neural networks and their functional implications using structural and functional connectomes.

Methodology:

Processes BIDS-formatted MRI data; performs diffusion tractography for structural connectomes and resting-state correlation for functional connectomes; computes geodesic distance matrices and microstructural profile covariance matrices from cortical myelin proxies; supports 18 cortical parcellations (100–1,000 parcels) plus subcortical and cerebellar parcellations and outputs on native, conte69, and fsaverage5 surface spaces; includes individual- and group-level quality control.

Topics

Details

License:
GPL-3.0
Tool Type:
library, workflow
Programming Languages:
Shell, Python
Added:
11/10/2022
Last Updated:
11/24/2024

Operations

Publications

Cruces RR, Royer J, Herholz P, Larivière S, Vos de Wael R, Paquola C, Benkarim O, Park B, Degré-Pelletier J, Nelson MC, DeKraker J, Leppert IR, Tardif C, Poline J, Concha L, Bernhardt BC. Micapipe: A pipeline for multimodal neuroimaging and connectome analysis. NeuroImage. 2022;263:119612. doi:10.1016/j.neuroimage.2022.119612. PMID:36070839. PMCID:PMC10697132.

PMID: 36070839
Funding: - Consejo Nacional de Ciencia y Tecnología: 1782, 181508 - Ministry of Science, ICT and Future Planning: 2020-0-01389, 2022-0-00448 - National Institute of Mental Health: R01MH096906 - Inha University: RS-2022-00155915 - Natural Sciences and Engineering Research Council of Canada: Discovery-1304413 - National Research Foundation of Korea: NRF-2021R1F1A1052303, NRF-2022R1A5A7033499 - Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México: FDN-154298, IB201712, IG200117, IN204720, PJT-174995 - Institute for Basic Science: IBS-R015-D1

Documentation

Links