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

Air pollution is linked to divergent cortical thickness patterns in brain regions vulnerable to Alzheimer's disease.

Neurotoxicology·2026
Same author

FEMA-Long: Modeling unstructured covariances for discovery of time-dependent effects in large-scale longitudinal datasets.

PLoS genetics·2026
Same author

Strategies for collection, management, and release of data for multi-site longitudinal studies: Lessons from the ABCD Data Analysis, Informatics, & Resource Center.

Developmental cognitive neuroscience·2026
Same author

Association of C-reactive protein with brain micro- and macro-structure among older adult men.

Brain, behavior, and immunity·2026
Same author

Design of the FRESH-A study: A randomized controlled trial evaluating telehealth parent-only treatment for autistic youth with overweight/obesity.

Contemporary clinical trials·2026
Same author

Impact of anti-peptic ulcer disease (PUD) medications on hyperlipidemia risk in patients with PUD: a population-based retrospective cohort study.

Therapeutic advances in endocrinology and metabolism·2026

Related Experiment Video

Updated: Oct 2, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.8K

Do aggregate, multimodal structural neuroimaging measures replicate regional developmental differences observed in

Donald J Hagler1, Wesley K Thompson2, Chi-Hua Chen1

  • 1Department of Radiology, University of California, San Diego, United States; Center for Multimodal Imaging and Genetics, University of California, San Diego, United States.

Developmental Cognitive Neuroscience
|February 27, 2022
PubMed
Summary

Neuroimaging reveals regional differences in brain development. Prefrontal cortex shows prolonged changes compared to sensory areas, highlighting complexities in mapping maturation across the cortex.

Keywords:
CorticalDevelopmentMultimodalNeuroimagingPING

More Related Videos

Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

17.0K
Whole-Brain Single-Cell Imaging and Analysis of Intact Neonatal Mouse Brains Using MRI, Tissue Clearing, and Light-Sheet Microscopy
08:49

Whole-Brain Single-Cell Imaging and Analysis of Intact Neonatal Mouse Brains Using MRI, Tissue Clearing, and Light-Sheet Microscopy

Published on: August 1, 2022

3.8K

Related Experiment Videos

Last Updated: Oct 2, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.8K
Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

17.0K
Whole-Brain Single-Cell Imaging and Analysis of Intact Neonatal Mouse Brains Using MRI, Tissue Clearing, and Light-Sheet Microscopy
08:49

Whole-Brain Single-Cell Imaging and Analysis of Intact Neonatal Mouse Brains Using MRI, Tissue Clearing, and Light-Sheet Microscopy

Published on: August 1, 2022

3.8K

Area of Science:

  • Neuroscience
  • Developmental Neuroscience
  • Neuroimaging

Background:

  • Postmortem studies identified regional differences in human brain tissue properties during early development.
  • Large-scale neuroimaging offers denser sampling for age-related trajectories but differs from histological measures.

Purpose of the Study:

  • To characterize cortical regional variability in developmental trajectories using multimodal brain imaging data.
  • To replicate histological findings of delayed synapse elimination in prefrontal cortex compared to sensory areas.

Main Methods:

  • Utilized data from 951 participants (ages 3-21) from the Pediatric Imaging, Neurocognition, and Genetics (PING) study.
  • Integrated morphometric and microstructural cortical surface measures using multivariate analyses.
  • Conducted whole-cortex analysis to identify regions with distinct developmental trajectories.

Main Results:

  • Prefrontal regions exhibited a more protracted period of developmental change compared to sensory cortical regions.
  • Multivariate analyses revealed significant interregional variability in developmental trajectories.
  • Identified cortical parcellations with maximally divergent developmental trajectories.

Conclusions:

  • Neuroimaging findings support postmortem analyses suggesting prolonged development in prefrontal regions.
  • Results underscore the challenges in precisely determining relative maturational phases across different brain regions using current imaging techniques.