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Related Concept Videos

Imaging Studies IV: Magnetic Resonance Imaging01:27

Imaging Studies IV: Magnetic Resonance Imaging

Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...

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Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
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A standardized image processing and data quality platform for rodent fMRI.

Gabriel Desrosiers-Grégoire1,2, Gabriel A Devenyi3,4, Joanes Grandjean5,6

  • 1Computational Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC, Canada. gabriel.desrosiers-gregoire@mail.mcgill.ca.

Nature Communications
|August 7, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces Rodent Automated Bold Improvement of EPI Sequences (RABIES), a standardized software pipeline for rodent functional magnetic resonance imaging (fMRI) data. RABIES enhances reproducibility and quality control for brain network analysis in translational neuroscience research.

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Area of Science:

  • Neuroscience
  • Neuroimaging
  • Rodent Models

Background:

  • Functional magnetic resonance imaging (fMRI) in rodents is crucial for understanding brain networks.
  • Lack of standardized processing and quality control in rodent fMRI limits reproducibility.
  • Existing methods do not provide a unified approach for preprocessing, quality control, and confound correction.

Purpose of the Study:

  • To introduce a standardized software platform for rodent fMRI data analysis.
  • To address limitations in reproducibility and transparency in rodent brain network research.
  • To provide a robust pipeline for preprocessing, quality control, and confound correction.

Main Methods:

  • Development of the Rodent Automated Bold Improvement of EPI Sequences (RABIES) software pipeline.
  • Validation of the preprocessing workflow across multiple acquisition sites and species (mouse and rat).
  • Investigation of data quality metrics and development of quality control guidelines for network analysis.

Main Results:

  • Demonstrated robustness of the RABIES preprocessing workflow across diverse datasets.
  • Established guidelines for quality control of rodent fMRI network analysis.
  • Identified and recommended methods for addressing data quality issues.

Conclusions:

  • The RABIES platform offers a standardized solution for rodent fMRI analysis.
  • Implementation of RABIES promotes reproducible practices in translational neuroscience.
  • This tool facilitates progress in understanding rodent brain networks.