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Magnetic Resonance Imaging

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

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Updated: Feb 27, 2026

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

Building connectomes using diffusion MRI: why, how and but.

Stamatios N Sotiropoulos^1,2, Andrew Zalesky³

¹Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.

NMR in Biomedicine

|June 28, 2017

Summary

This summary is machine-generated.

Diffusion MRI is key for in vivo connectome mapping, but methods are developing. This review explores factors affecting brain connectome reconstruction and highlights current limitations.

Keywords:

brain network connections parcellation tracers tractography white matter fibers

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Area of Science:

Neuroimaging
Computational Neuroscience
Biomedical Engineering

Background:

Diffusion MRI (dMRI) is a leading technique for in vivo human connectome mapping.
Understanding the brain's structural and functional connectivity is crucial for neuroscience research.

Purpose of the Study:

To review methods for estimating macroscale brain connectomes using dMRI.
To identify factors influencing connectome reconstruction accuracy and limitations.
To discuss the current state and future directions of dMRI-based connectome mapping.

Main Methods:

Overview of key methodologies for estimating connectome nodes and edges.
Analysis of the impact of acquisition parameters and tractography algorithms.
Review of studies demonstrating microstructural and network properties from dMRI data.

Main Results:

Connectome estimation is sensitive to methodological choices in dMRI acquisition and analysis.
Current dMRI-based connectome mapping methods have inherent limitations and challenges.
Evidence exists for extracting biologically relevant microstructural and network information.

Conclusions:

dMRI-based connectome mapping is an evolving field with significant challenges.
Caution is advised against the uncritical application of tractography methods.
Future developments are needed to improve the accuracy and reliability of macroscale connectome mapping.