Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

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

Feynman Kac Reweighted Schrödinger Bridge Matching for Surface-Based Tau PET Harmonization.

ArXiv·2026

Same author

GPR107 promotes autophagy secretion in psoriatic keratinocytes by inhibiting BECN1 K48-linked ubiquitination.

Cell death & disease·2026

Same author

Estimating time of day from fingertip blood samples using RNA molecules with diurnal oscillating expression: a proof-of-principle study.

International journal of legal medicine·2026

Same author

An in silico evaluation of tri-allelic SNPs from 1kGP Phase IV data for distant kinship identification and mixture analysis.

Forensic science international. Genetics·2026

Same author

Evaluating the accuracy of sex estimation from human tooth volume: leveraging automated AI segmentation and comparative analysis of machine learning algorithms.

Head & face medicine·2026

Same author

Influence of Gypsum Type on Early Hydration Kinetics and Autogenous Shrinkage of Supersulfated Cement-Based UHPC Matrix.

Materials (Basel, Switzerland)·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

Search research articles

Related Experiment Video

Updated: Feb 20, 2026

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

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

Kernel-Regularized ICA for Computing Functional Topography from Resting-state fMRI.

Junyan Wang¹, Yonggang Shi¹

¹Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033, USA.

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention

|October 27, 2017

Summary

This summary is machine-generated.

This study introduces a new method using structural connectivity to improve the topographic regularity of functional connectivity maps derived from resting-state fMRI (rfMRI). The novel approach enhances reproducibility and captures brain

More Related Videos

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Published on: January 5, 2024

Related Experiment Videos

Last Updated: Feb 20, 2026

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

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

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Published on: January 5, 2024

Area of Science:

Neuroimaging
Computational Neuroscience
Brain Connectivity

Background:

Topographic regularity is crucial for understanding brain connectivity.
Resting-state fMRI (rfMRI) is a valuable tool for large-scale brain studies due to its accessibility.
Conventional group Independent Component Analysis (ICA) methods may not fully capture the topographical organization of functional connectivity.

Purpose of the Study:

To develop a novel method for studying topographic regularity in functional connectivity using rfMRI.
To incorporate topographically regular structural connectivity into ICA for improved functional topography extraction.
To enhance the reproducibility and accuracy of functional connectivity mapping.

Main Methods:

Developed a kernel-regularized ICA method integrating structural connectivity information.
Utilized advanced tractography and tract filtering algorithms to generate organized fiber bundles.
Applied the method to rfMRI data from 35 Human Connectome Project (HCP) subjects, focusing on motor cortex functional topography.

Main Results:

The proposed method generated functional connectivity maps with superior topographic regularity compared to conventional group ICA.
Extracted components effectively captured motor cortex co-activation patterns respecting hemispheric topography.
Demonstrated improved reproducibility of functional topography analysis using the novel method.

Conclusions:

The kernel-regularized ICA method successfully enhances topographic regularity in rfMRI-based functional connectivity.
Incorporating structural connectivity information improves the capture of organized functional patterns, particularly in areas like the motor cortex.
This novel approach offers a more reproducible and accurate way to study brain functional topography.