Predicting language lateralization from gray matter.
Details
Serval ID
serval:BIB_2BADEE12AD0A
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Predicting language lateralization from gray matter.
Journal
Journal of Neuroscience
ISSN
1529-2401 (Electronic)
ISSN-L
0270-6474
Publication state
Published
Issued date
2009
Volume
29
Number
43
Pages
13516-13523
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov'tPublication Status: ppublish
Abstract
It has long been predicted that the degree to which language is lateralized to the left or right hemisphere might be reflected in the underlying brain anatomy. We investigated this relationship on a voxel-by-voxel basis across the whole brain using structural and functional magnetic resonance images from 86 healthy participants. Structural images were converted to gray matter probability images, and language activation was assessed during naming and semantic decision. All images were spatially normalized to the same symmetrical template, and lateralization images were generated by subtracting right from left hemisphere signal at each voxel. We show that the degree to which language was left or right lateralized was positively correlated with the degree to which gray matter density was lateralized. Post hoc analyses revealed a general relationship between gray matter probability and blood oxygenation level-dependent signal. This is the first demonstration that structural brain scans can be used to predict language lateralization on a voxel-by-voxel basis in the normal healthy brain.
Keywords
Brain/anatomy & histology, Brain/blood supply, Brain Mapping, Cell Count, Cerebrovascular Circulation, Female, Functional Laterality, Humans, Image Processing, Computer-Assisted, Language, Language Tests, Magnetic Resonance Imaging, Male, Names, Nerve Fibers, Unmyelinated/physiology, Oxygen/blood, Probability, Reading, Semantics
Pubmed
Web of science
Open Access
Yes
Create date
22/01/2013 14:39
Last modification date
20/08/2019 13:11