Literature DB >> 29274747

More highly myelinated white matter tracts are associated with faster processing speed in healthy adults.

Sidhant Chopra1, Marnie Shaw2, Thomas Shaw3, Perminder S Sachdev4, Kaarin J Anstey5, Nicolas Cherbuin6.   

Abstract

The objective of this study was to investigate whether the estimated myelin content of white matter tracts is predictive of cognitive processing speed and whether such associations are modulated by age. Associations between estimated myelin content and processing speed were assessed in 570 community-living individuals (277 middle-age, 293 older-age). Myelin content was estimated in-vivo using the mean T1w/T2w magnetic resonance ratio, in six white matter tracts (anterior corona radiata, superior corona radiata, pontine crossing tract, anterior limb of the internal capsule, genu of the corpus callosum, and splenium of the corpus callosum). Processing speed was estimated by extracting a principal component from 5 separate tests of processing speed. It was found that estimated myelin content of the bilateral anterior limb of the internal capsule and left splenium of the corpus callosum were significant predictors of processing speed, even after controlling for socio-demographic, health and genetic variables and correcting for multiple comparisons. One SD higher in the estimated myelin content of the anterior limb of the internal capsule was associated with 2.53% faster processing speed and within the left splenium of the corpus callosum with 2.20% faster processing speed. In addition, significant differences in estimated myelin content between middle-age and older participants were found in all six white matter tracts. The present results indicate that myelin content, estimated in vivo using a neuroimaging approach in healthy older adults, is sufficiently precise to predict variability in processing speed in behavioural measures.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Ageing; Myelin; Processing speed; T1w/T2w; White matter

Mesh:

Year:  2017        PMID: 29274747     DOI: 10.1016/j.neuroimage.2017.12.069

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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