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 Experiment Videos

Surface visualization of electromagnetic brain activity.

Alexandra Badea1, George K Kostopoulos, Andreas A Ioannides

  • 1Department of Physiology, Medical School, University of Patras, Panepistimioupolis, 26500 Rio-Patras, Greece.

Journal of Neuroscience Methods
|August 9, 2003
PubMed
Summary
This summary is machine-generated.

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

Exercise mitigates high-fat diet-induced cardiac dysfunction via APOE genotype- and immune-dependent mechanisms: A photon-counting CT study in adult mice.

PloS one·2025
Same author

Photon-Counting Micro-CT for Bone Morphometry in Murine Models.

Tomography (Ann Arbor, Mich.)·2025
Same author

Olfactory-Guided Behavior Uncovers Imaging and Molecular Signatures of Alzheimer's Disease Risk.

Brain sciences·2025
Same author

Development of anatomically variable digital Wistar rat phantoms for small animal imaging research.

Medical physics·2025
Same author

Feature attention graph neural network for estimating brain age and identifying important neural connections in mouse models of genetic risk for Alzheimer's disease.

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

Network biomarkers of Alzheimer's disease risk derived from joint volume and texture covariance patterns in mouse models.

PloS one·2025
Same journal

Time as the language of Behavior: events, sequences, patterns and meanings.

Journal of neuroscience methods·2026
Same journal

Detection of cochlear microphonic for differential diagnosis between auditory neuropathy mice and noise-induced sensorineural hearing loss mice.

Journal of neuroscience methods·2026
Same journal

Assessment metrics for pain control in rats: A methodological commentary.

Journal of neuroscience methods·2026
Same journal

Infant EEG preprocessing pipelines: A capability framework and current gaps in practice.

Journal of neuroscience methods·2026
Same journal

Methods for measuring neural activity during voluntary wheel running.

Journal of neuroscience methods·2026
Same journal

Serotype-dependent differences in AAV cellular transduction rates in the hypothalamus of Arctic ground squirrels.

Journal of neuroscience methods·2026
See all related articles

New methods visualize brain activity by integrating electrophysiology with anatomy. This allows detailed mapping of neural electrical activity and its relationship to brain structure for better understanding of brain function.

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Biophysics

Background:

  • Non-invasive techniques now enable brain activity reconstruction from electrophysiological measurements.
  • Visualizing anatomical detail alongside functional data enhances understanding of brain activity.
  • Existing software often focuses on scalar measures (e.g., fMRI hemodynamics), not the vector properties of electrical activity.

Purpose of the Study:

  • To develop and present methods for segmenting and visualizing spatio-temporal brain activity.
  • To integrate anatomical structure with both scalar and vector properties of current density.
  • To demonstrate the utility of these methods using real neuroimaging data.

Main Methods:

  • Developed novel segmentation and visualization techniques for spatio-temporal brain activity.

Related Experiment Videos

  • Represented the interplay between cortical geometry and current density (scalar and vector properties).
  • Utilized magnetoencephalography (MEG) data for tomographic reconstructions of sensory processing.

    • Main Results:

    • Demonstrated visualization of early sensory processing in somatosensory and visual modalities using MEG data.
    • Enabled observation of activation courses as current density or statistical maps.
    • Successfully visualized simultaneous MEG and functional magnetic resonance imaging (fMRI) activations.

    Conclusions:

    • Integrated visualization of complementary functional data (MEG, fMRI) aids analysis.
    • The developed methods enhance the understanding of structure-function relationships in the brain.
    • This approach is valuable for studying both normal and diseased brain states.