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

Functional properties of the handwriting brain network: Effects of motor sequence and spatial adaptation constraints.

Cortex; a journal devoted to the study of the nervous system and behavior·2026
Same author

Mapping Human Proprioceptive Projections of Upper Limb Muscles Through Spinal Cord fMRI.

Human brain mapping·2025
Same author

Shared phonological networks in frontal and temporal cortex for language production and comprehension.

Cerebral cortex (New York, N.Y. : 1991)·2025
Same author

Atypical hemispheric re-organization of the reading network in high-functioning adults with dyslexia: Evidence from representational similarity analysis.

Imaging neuroscience (Cambridge, Mass.)·2025
Same author

Revealing the co-existence of written and spoken language coding neural populations in the visual word form area.

Imaging neuroscience (Cambridge, Mass.)·2025
Same author

Neural Networks for Semantic and Syntactic Prediction and Visual-Motor Statistical Learning in Adult Readers With and Without Dyslexia.

Neurobiology of language (Cambridge, Mass.)·2025

Related Experiment Video

Updated: Jul 16, 2026

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
11:28

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Published on: June 30, 2018

Anatomically informed convolution kernels for the projection of fMRI data on the cortical surface.

Grégory Operto1, Rémy Bulot, Jean-Luc Anton

  • 1Laboratoire LSIS, UMR 6168, CNRS, Marseille, France.

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|March 16, 2007
PubMed
Summary

This study introduces a novel projection method to map functional magnetic resonance imaging (fMRI) data onto the brain's cortical surface. This technique enables advanced cortical-based functional analysis.

More Related Videos

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
10:06

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Published on: May 10, 2012

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: Jul 16, 2026

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
11:28

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Published on: June 30, 2018

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
10:06

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Published on: May 10, 2012

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:

  • Neuroimaging
  • Computational Neuroscience
  • Medical Image Analysis

Background:

  • Functional magnetic resonance imaging (fMRI) generates volumetric data of brain activity.
  • Analyzing fMRI data directly on the cortical surface is crucial for understanding localized brain function.
  • Current methods may lack precision in mapping volumetric data to the complex cortical geometry.

Purpose of the Study:

  • To develop a robust method for projecting functional brain data from fMRI volumes onto the cortical surface.
  • To create anatomically informed representations for enhanced cortical-based functional analysis.
  • To establish a versatile projection technique applicable to various registered functional datasets.

Main Methods:

  • A novel projection technique utilizing convolution kernels defined around nodes of the grey/white matter interface mesh.
  • Kernel shape and distribution are determined by local anatomical geometry.
  • Computation of a set of convolution kernels specific to a given anatomy for projecting registered functional data.

Main Results:

  • The proposed method successfully generates surface-based representations of functional brain data.
  • Experiments with synthetic data demonstrate the method's accuracy.
  • Validation using real statistical t-maps confirms its applicability to actual neuroimaging data.

Conclusions:

  • The developed projection method provides accurate and anatomically relevant surface representations of fMRI data.
  • This technique facilitates more sophisticated cortical-based functional analyses.
  • The method offers a valuable tool for neuroimaging research requiring precise mapping of brain activity onto the cortex.