Surface visualization of electromagnetic brain activity.

Journal Article (Journal Article)

Advances in hardware and software have made possible the reconstruction of brain activity from non-invasive electrophysiological measurements over a large part of the brain. The appreciation of the information content in the data is enhanced when relevant anatomical detail is also available for visualization. Different neuroscientific questions give rise to different requirements for optimal superposition of structure and function. Most available software deal with scalar measures of activity, especially hemodynamic changes. In contrast, the electrophysiological observables are generated by electrical activity, which depends on the synchrony of neuronal assemblies and the geometry of the local cortical surface. We describe methods for segmentation and visualization of spatio-temporal brain activity, which allow the interplay of geometry and scalar as well as vector properties of the current density directly in the representations. The utility of these methods is demonstrated through displays of tomographic reconstructions of early sensory processing in the somatosensory and visual modality extracted from magnetoencephalography (MEG) data. The activation course characteristic to a specific area could be observed as current density or statistical maps independently and/or contrasted to the activity in other areas or the whole brain. MEG and functional magnetic resonance imaging (fMRI) activations were simultaneously visualized. Integrating and visualizing complementary functional data into a single environment helps evaluating analysis and understanding structure/function relationships in normal and diseased brain.

Full Text

Duke Authors

Cited Authors

  • Badea, A; Kostopoulos, GK; Ioannides, AA

Published Date

  • August 15, 2003

Published In

Volume / Issue

  • 127 / 2

Start / End Page

  • 137 - 147

PubMed ID

  • 12906943

Pubmed Central ID

  • 12906943

International Standard Serial Number (ISSN)

  • 0165-0270

Digital Object Identifier (DOI)

  • 10.1016/s0165-0270(03)00100-6


  • eng

Conference Location

  • Netherlands