Neural systems predicting long-term outcome in dyslexia

被引:335
作者
Hoeft, Fumiko [1 ,2 ]
McCandliss, Bruce D. [3 ]
Black, Jessica M. [1 ,4 ]
Gantman, Alexander [1 ]
Zakerani, Nahal [1 ]
Hulme, Charles [5 ]
Lyytinen, Heikki [6 ]
Whitfield-Gabrieli, Susan [7 ]
Glover, Gary H. [8 ]
Reiss, Allan L. [1 ,2 ,8 ]
Gabrieli, John D. E. [8 ]
机构
[1] Stanford Univ, Sch Med, Ctr Interdisciplinary Brain Sci Res, Stanford, CA 94129 USA
[2] Stanford Univ, Sch Med, Dept Psychiat & Behav Sci, Stanford, CA 94129 USA
[3] Vanderbilt Univ, Dept Psychol & Human Dev, Nashville, TN 37203 USA
[4] Boston Coll, Grad Sch Social Work, Chestnut Hill, MA 02467 USA
[5] Univ York, Dept Psychol, York YO10 5DD, N Yorkshire, England
[6] Univ Jyvaskyla, Dept Psychol, SF-40351 Jyvaskyla, Finland
[7] MIT, Dept Brain & Cognit Sci, Cambridge, MA 02139 USA
[8] Stanford Univ, Dept Radiol, Sch Med, Stanford, CA 94305 USA
基金
美国安德鲁·梅隆基金会;
关键词
inferior frontal gyrus; prediction; compensation; fractional anisotropy; rhyming; WHITE-MATTER; DEVELOPMENTAL DYSLEXIA; READING-ABILITY; INDIVIDUAL-DIFFERENCES; BRAIN CONNECTIVITY; MAJOR DEPRESSION; SPATIAL-PATTERNS; MENTAL STATES; CHILDREN; FMRI;
D O I
10.1073/pnas.1008950108
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页码:361 / 366
页数:6
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