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Related Experiment Video

Updated: Dec 14, 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

Quantifying Genetic and Environmental Influence on Gray Matter Microstructure Using Diffusion MRI.

Madhura Baxi^1,2, Maria A Di Biase², Amanda E Lyall^2,3

¹Graduate Program of Neuroscience, Boston University, Boston, MA 02118, USA.

Cerebral Cortex (New York, N.Y. : 1991)

|July 18, 2020

Summary

This summary is machine-generated.

This study reveals that advanced diffusion MRI measures, like return to origin probability (RTOP) and mean squared displacement (MSD), can reveal genetic and environmental influences on brain gray matter microstructure, complementing macrostructure findings.

Keywords:

MSD RTOP imaging genetics non-Gaussian model twin study

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Area of Science:

Neuroimaging
Genetics
Brain Microstructure

Background:

Early twin studies focused on genetic and environmental influences on gray matter macrostructure.
Understanding gray matter microstructure's genetic and environmental basis is crucial for mental disorder research.

Purpose of the Study:

To investigate genetic and environmental influences on gray matter microstructure using advanced diffusion MRI.
To compare advanced dMRI measures with conventional diffusion tensor measures for microstructure assessment.

Main Methods:

Utilized diffusion and structural MRI data from a large twin and sibling study (N=840).
Computed advanced dMRI measures: return to origin probability (RTOP) and mean squared displacement (MSD).

Main Results:

Macrostructural features like brain volume are primarily genetically influenced.
RTOP and MSD measures capture both genetic and environmental influences on gray matter microstructure.

Conclusions:

Advanced dMRI measures provide novel insights into the genetic and environmental underpinnings of brain gray matter microstructure.
These findings facilitate future research into the etiology of mental disorders.