Spatial MEG Laterality maps for language: Clinical applications in epilepsy

Ryan C.N. D'Arcy, Timothy Bardouille, Aaron J. Newman, Sean R. Mcwhinney, Drew Debay, R. Mark Sadler, David B. Clarke, Michael J. Esser

Résultat de recherche: Articleexamen par les pairs

12 Citations (Scopus)

Résumé

Functional imaging is increasingly being used to provide a noninvasive alternative to intracarotid sodium amobarbitol testing (i.e., the Wada test). Although magnetoencephalography (MEG) has shown significant potential in this regard, the resultant output is often reduced to a simplified estimate of laterality. Such estimates belie the richness of functional imaging data and consequently limit the potential value. We present a novel approach that utilizes MEG data to compute "complex laterality vectors" and consequently "laterality maps" for a given function. Language function was examined in healthy controls and in people with epilepsy. When compared with traditional laterality index (LI) approaches, the resultant maps provided critical information about the magnitude and spatial characteristics of lateralized function. Specifically, it was possible to more clearly define low LI scores resulting from strong bilateral activation, high LI scores resulting from weak unilateral activation, and most importantly, the spatial distribution of lateralized activation. We argue that the laterality concept is better presented with the inherent spatial sensitivity of activation maps, rather than being collapsed into a one-dimensional index. Hum Brain Mapp, 2013.

Langue d'origineEnglish
Pages (de-à)1749-1760
Nombre de pages12
JournalHuman Brain Mapping
Volume34
Numéro de publication8
DOI
Statut de publicationPublished - août 2013

ASJC Scopus Subject Areas

  • Anatomy
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't

Empreinte numérique

Plonger dans les sujets de recherche 'Spatial MEG Laterality maps for language: Clinical applications in epilepsy'. Ensemble, ils forment une empreinte numérique unique.

Citer