Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Impact of an online-guided physical activity intervention on cognition, resting-state brain connectivity, and the gut microbiome in healthy older adults-a randomized controlled trial.

GeroScience·2026
Same author

Biomedical open source software: Crucial packages and hidden heroes.

PLoS computational biology·2026
Same author

Multiscale characterization of cortical signatures in positive and negative schizotypy: a worldwide ENIGMA study.

Molecular psychiatry·2026
Same author

Stages of objective memory impairment are associated with accelerated brain aging.

Scientific reports·2026
Same author

Factors Contributing to Short-Term Structural Variability in a Longitudinal MRI Dataset.

Human brain mapping·2026
Same author

Changes in voxel-wise gray matter asymmetry over time.

Frontiers in neuroscience·2025
Same journal

Predicting vasovagal syncope during head-up tilt test: three machine learning approaches.

Frontiers in neuroinformatics·2026
Same journal

Decoding basal ganglia motor circuit dysfunction from handwriting: a physics-informed neural signal interpretation framework for Parkinson's disease screening.

Frontiers in neuroinformatics·2026
Same journal

FUSION-AD: interpretable AI framework for risk assessment and subgroup discovery in Alzheimer's disease.

Frontiers in neuroinformatics·2026
Same journal

A 3D-printed phantom to validate subject orientation in 3D imaging and recordings.

Frontiers in neuroinformatics·2026
Same journal

IntegriLAB: a blockchain-enabled electronic lab notebook for reproducible neuroimaging research.

Frontiers in neuroinformatics·2026
Same journal

Long-range correlations in alpha-band of electroencephalogram: a nonlinear embedding and detrended fluctuation analysis.

Frontiers in neuroinformatics·2026
See all related articles

Related Experiment Video

Updated: Dec 22, 2025

Three-Dimensional Shape Modeling and Analysis of Brain Structures
05:33

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

7.5K

Computational morphometry for detecting changes in brain structure due to development, aging, learning, disease and

Daniel Mietchen1, Christian Gaser

  • 1Structural Brain Mapping Group, Department of Psychiatry, University of Jena D - 07743 Jena, Germany.

Frontiers in Neuroinformatics
|August 27, 2009
PubMed
Summary
This summary is machine-generated.

Brain structure changes are detectable with advanced neuroimaging and computational morphometry. Magnetic Resonance imaging reveals brain alterations over various timescales, from short-term to evolutionary.

Keywords:
MRIagingbrain diseasebrain morphometrydevelopmentevolutiongyrificationlearning

More Related Videos

Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI—Application in Premanifest Huntington's Disease
09:06

Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI—Application in Premanifest Huntington's Disease

Published on: June 9, 2018

12.5K
3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse
15:26

3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse

Published on: May 19, 2015

14.6K

Related Experiment Videos

Last Updated: Dec 22, 2025

Three-Dimensional Shape Modeling and Analysis of Brain Structures
05:33

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

7.5K
Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI—Application in Premanifest Huntington's Disease
09:06

Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI—Application in Premanifest Huntington's Disease

Published on: June 9, 2018

12.5K
3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse
15:26

3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse

Published on: May 19, 2015

14.6K

Area of Science:

  • Neuroscience
  • Computational Biology
  • Medical Imaging

Background:

  • The brain exhibits continuous structural and functional changes influenced by genetics and environment.
  • Neuroimaging techniques are increasingly capable of detecting these dynamic brain alterations.
  • Computational morphometry using Magnetic Resonance (MR) imaging is a key tool for studying macroscopic brain changes.

Purpose of the Study:

  • To highlight the advancements in detecting brain structure changes using computational morphometry.
  • To discuss the potential of MR imaging in studying brain changes across diverse populations and timescales.
  • To underscore the role of neuroinformatics in understanding lifelong and evolutionary brain modifications.

Main Methods:

  • Utilizing computational morphometry on Magnetic Resonance (MR) images.
  • Employing advanced computational techniques and sophisticated study designs.
  • Analyzing large datasets of MR images from diverse brain populations.

Main Results:

  • Significant reductions in the minimal detectable extent and duration of brain changes have been achieved.
  • Increased availability of diverse MR image data enables inferences about long-term and evolutionary brain changes.
  • New avenues for studying brain structure and function over extended periods are opening.

Conclusions:

  • Computational morphometry and MR imaging are powerful tools for understanding brain plasticity.
  • Neuroinformatics is crucial for interpreting complex, large-scale brain data.
  • Research is advancing our understanding of how the brain changes throughout life and evolution.