Related Experiment Video
Updated: Feb 4, 2026

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI
Published on: November 27, 2019
Brain gray and white matter abnormalities in preterm-born adolescents: A meta-analysis of voxel-based morphometry
Le Zhou1,2, Youjin Zhao1, Xinghui Liu3
1Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China.
Insights
Preterm-born adolescents show widespread gray and white matter volume differences in key brain networks, impacting socialization and cognition. Male preterm adolescents exhibit a specific correlation between lower gray matter volume and sex.
Area of Science:
- Neuroimaging
- Developmental Neuroscience
- Brain Anatomy
Background:
- Voxel-based morphometry studies reveal inconsistent gray matter volume (GMV) and white matter volume (WMV) abnormalities in preterm-born adolescents (PBA).
- Meta-analysis is crucial for identifying consistent structural brain alterations in this population.
Purpose of the Study:
- To conduct a meta-analysis identifying consistent GMV and WMV alterations in PBA compared to healthy controls.
- To explore potential correlations between demographic factors and observed brain structure differences.
Main Methods:
- Systematic literature search identifying 9 eligible studies up to October 2017.
- Seed-based d Mapping (SDM) used for meta-analysis of GMV and WMV data.
- Meta-regression analysis to investigate correlations with PBA demographics.
Main Results:
- PBA exhibited increased GMV in specific cortical regions (left cuneus, left superior frontal gyrus, right anterior cingulate) and decreased GMV in others (bilateral inferior temporal gyrus, right caudate nucleus).
- WMV alterations in PBA included increased volume in the right fusiform gyrus and precuneus, and decreased volume in bilateral inferior temporal gyrus and right inferior frontal gyrus.
- Meta-regression revealed a negative correlation between the percentage of male PBA and decreased GMV in the bilateral inferior temporal gyrus.
Conclusions:
- PBA demonstrate widespread GMV and WMV alterations within the default mode, visual recognition, and salience networks.
- These structural changes are potentially linked to observed socialization difficulties and cognitive impairments in PBA.
- Meta-regression findings suggest a structural basis for sex-related cognitive differences in preterm-born individuals.
Introduction:
Studies using voxel-based morphometry report variable and inconsistent abnormalities of gray matter volume (GMV) and white matter volume (WMV) in brains of preterm-born adolescents (PBA). In such circumstances a meta-analysis can help identify the most prominent and consistent abnormalities.
Method:
We identified 9 eligible studies by systematic search of the literature up to October 2017. We used Seed-based d Mapping to analyze GMV and WMV alterations between PBA and healthy controls.
Results:
In the GMV meta-analysis, PBA compared to healthy controls showed: increased GMV in left cuneus cortex, left superior frontal gyrus, and right anterior cingulate cortex; decreased GMV in bilateral inferior temporal gyrus (ITG), left superior frontal gyrus, and right caudate nucleus. In the WMV meta-analysis, PBA showed: increased WMV in right fusiform gyrus and precuneus; decreased WMV in bilateral ITG, and right inferior frontal gyrus. In meta-regression analysis, the percentage of male PBA negatively correlated with decreased GMV of bilateral ITG.
Interpretation:
PBA show widespread GMV and WMV alterations in the default mode network, visual recognition network, and salience network. These changes may be causally relevant to socialization difficulties and cognitive impairments. The meta-regression results perhaps reveal the structural underpinning of the cognition-related sex differences in PBA.
More Related Videos
11:50A Standardized Pipeline for Examining Human Cerebellar Grey Matter Morphometry using Structural Magnetic Resonance Imaging
Published on: February 4, 2022
08:36A Versatile Murine Model of Subcortical White Matter Stroke for the Study of Axonal Degeneration and White Matter Neurobiology
Published on: March 17, 2016
Related Concept Videos
The Born-Haber Cycle
Classifying Matter by State
Classifying Matter by Composition
According to its composition, the matter can be classified into two broad categories — pure substances and mixtures.
A pure substance is a form of matter that has a constant composition throughout with uniform properties. For example, any sample of sucrose has the same composition and same physical properties, such as melting point, color, and sweetness, regardless of the source from which it is isolated.
A mixture is composed of two or...
Abnormal Proliferation
The Atomic Theory of Matter
Physical and Chemical Properties of Matter