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Spatial MEG laterality maps for language: clinical applications in epilepsy.


ABSTRACT: 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.

SUBMITTER: D'Arcy RC 

PROVIDER: S-EPMC6870167 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature

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Spatial MEG laterality maps for language: clinical applications in epilepsy.

D'Arcy Ryan C N RC   Bardouille Timothy T   Newman Aaron J AJ   McWhinney Sean R SR   Debay Drew D   Sadler R Mark RM   Clarke David B DB   Esser Michael J MJ  

Human brain mapping 20120315 8


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  ...[more]

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