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

Adaptive Riemannian optimization for multi-scale diffeomorphic matching.

Nature communications·2026
Same author

Clinicoanatomic localization of iron-rich gliosis in aphasic presentations of globular glial tauopathy.

Brain communications·2026
Same author

Deep Computational Anatomy via Latent-Aligned Multiview Normalizing Flows.

bioRxiv : the preprint server for biology·2026
Same author

Contusions bias cortical thickness estimates after traumatic brain injury: A TRACK-TBI study.

NeuroImage. Clinical·2026
Same author

Text-Image Co-Alignment for Weakly Supervised Polyp Segmentation.

IEEE transactions on medical imaging·2026
Same author

Hepatic and abdominal adiposity in type 2 diabetes as assessed with machine learning on computed tomography scans.

Diabetes, obesity & metabolism·2026
Same journal

LiftReg: Limited Angle 2D/3D Deformable Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

Inverse Consistency by Construction for Multistep Deep Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

Can Crowdsourced Annotations Improve AI-based Congestion Scoring For Bedside Lung Ultrasound?

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

Equivariant Filters for Efficient Tracking in 3D Imaging.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

Lobar Lung Density Embeddings with a Transformer encoder (LobTe) to predict emphysema progression in COPD.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

uniGradICON: A Foundation Model for Medical Image Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
See all related articles

Related Experiment Video

Updated: Jun 8, 2026

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
09:01

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

Relating structural and functional connectivity to performance in a communication task.

Jeffrey T Duda1, Corey McMillan, Murray Grossman

  • 1Department of Bioengineering, University of Pennsylvania, USA. jtduda@seas.upenn.edu

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|October 1, 2010
PubMed
Summary
This summary is machine-generated.

This study reveals that both brain network structure and function are crucial for language processing. Combining these measures enhances our understanding of the neurobiology underlying cognitive tasks.

More Related Videos

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
17:06

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

Related Experiment Videos

Last Updated: Jun 8, 2026

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
09:01

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
17:06

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

Area of Science:

  • Neuroscience
  • Cognitive Science
  • Neuroimaging

Background:

  • Understanding the neurobiological basis of language and cognitive processing is complex.
  • Investigating both functional and structural brain connectivity offers a more comprehensive approach.

Purpose of the Study:

  • To test if functional and structural connectivity provide independent and complementary information.
  • To identify network components critical for language and cognitive processing.

Main Methods:

  • Event-related functional MRI (fMRI) and diffusion tensor imaging (DTI) tractography were employed.
  • Structural connectivity was assessed using fractional anisotropy (FA) in white matter tracts.
  • Cognitive performance on a language-based decision-making task was measured.

Main Results:

  • Fractional anisotropy in the uncinate fasciculus predicted decision-making performance.
  • Functional synchronization between frontal and temporal regions also predicted performance.
  • Combined functional and structural connectivity measures significantly improved prediction of performance.

Conclusions:

  • Both functional and structural brain connectivity are vital for language and cognitive functions.
  • Integrating multimodal neuroimaging data enhances the identification of critical neural network components.
  • This combined approach offers a more robust understanding of the neural underpinnings of cognition.