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Neural systems predicting long-term outcome in dyslexia.

Authors :
Hoeft, Fumiko
McCandliss, Bruce D.
Black, Jessica M.
Gantman, Alexander
Zakerani, Nahal
Hulme, Charles
Lyytinen, Heikki
Whitfield-Gabrieli, Susan
Glover, Gary H.
Reiss, Allan L.
Gabrieli, John D. E.
Source :
Proceedings of the National Academy of Sciences of the United States of America. 1/4/2011, Vol. 108 Issue 1, p361-366. 6p. 1 Color Photograph, 3 Graphs.
Publication Year :
2011

Abstract

Individuals with developmental dyslexia vary in their ability to improve reading skills, but the brain basis for improvement remains largely unknown. We performed a prospective, longitudinal study over 2.5 y in children with dyslexia (n = 25) or without dyslexia (n = 20) to discover whether initial behavioral or brain measures, including functional MRI (fMRI) and diffusion tensor imaging (DTI), can predict future long-term reading gains in dyslexia. No behavioral measure, including widely used and standardized reading and language tests, reliably predicted future reading gains in dyslexia. Greater right prefrontal activation during a reading task that demanded phonological awareness and right superior longitudinal fasciculus (including arcuate fasciculus) white-matter organization significantly predicted future reading gains in dyslexia. Multivariate pattern analysis (MVPA) of these two brain measures, using linear support vector machine (SVM) and cross-validation, predicted significantly above chance (72% accuracy) which particular child would or would not improve reading skills (behavioral measures were at chance). MVPA of whole-brain activation pattern during phonological processing predicted which children with dyslexia would improve reading skills 2.5 y later with >90% accuracy. These findings identify right prefrontal brain mechanisms that may be critical for reading improvement in dyslexia and that may differ from typical reading development. Brain measures that predict future behavioral outcomes (neuroprognosis) may be more accurate, in some cases, than available behavioral measures. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00278424
Volume :
108
Issue :
1
Database :
Academic Search Index
Journal :
Proceedings of the National Academy of Sciences of the United States of America
Publication Type :
Academic Journal
Accession number :
58666899
Full Text :
https://doi.org/10.1073/pnas.1008950108