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Brain Imaging

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...

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Related Experiment Video

Updated: Jul 5, 2025

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

Assessing White Matter Engagement in Brain Networks through Functional and Structural Connectivity Mapping.

Muwei Li^1,2, Kurt G Schilling^1,2, Zhaohua Ding^1,3,4,5

¹Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA.

Biorxiv : the Preprint Server for Biology

|January 23, 2024

Summary

This summary is machine-generated.

This study reveals how gray matter (GM) function relates to white matter (WM) structure, using diffusion tensor imaging (DTI) to map brain connectivity. This reveals WM engagement as a potential biomarker for neurological conditions.

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Area of Science:

Neuroscience
Brain Imaging
Connectomics

Background:

Understanding the brain's gray matter (GM) and white matter (WM) interplay is key to neuroscience.
Diffusion tensor imaging (DTI) maps structural pathways, but the link between structural connectivity (SC) and functional connectivity (FC) needs more research.

Approach:

Developed a novel method to map the functional importance of inter-GM links to their WM structural counterparts.
Utilized clustering analysis on window-wise engagement maps to identify dynamic engagement modes.

Key Points:

The mapping revealed reproducible spatial distributions of WM engagement, correlating with structural, functional, and bioenergetic measures.
Identified unique, dynamic engagement modes in WM, showing significant gender and age-related differences.
Demonstrated a clear interdependence between GM function and WM characteristics.

Conclusions:

WM engagement patterns offer a nuanced view of brain activity and connectivity.
WM engagement shows potential as a biomarker for neurological and cognitive conditions.
Highlights the dynamic nature of brain connectivity and its variations across demographics.