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Brain Struct Funct. 2016 Apr;221(3):1337-51. doi: 10.1007/s00429-014-0975-6. Epub 2015 Jan 21.

Plasticity of left perisylvian white-matter tracts is associated with individual differences in math learning.

Author information

1
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 1070 Arastradero Road, Suite 220, Palo Alto, CA, 94304, USA. d.d.jolles@fsw.leidenuniv.nl.
2
Department of Education and Child Studies, Leiden University, Wassenaarseweg 52, 2333 AK, Leiden, The Netherlands. d.d.jolles@fsw.leidenuniv.nl.
3
Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Cambridge, MA, USA.
4
Athena EPI, INRIA Sophia Antipolis - Méditerranée, 2004 route des Lucioles, 06902, Sophia Antipolis, France.
5
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 1070 Arastradero Road, Suite 220, Palo Alto, CA, 94304, USA.
6
Department of Radiology, Center for Quantitative Neuroimaging, Stanford University School of Medicine, Stanford, CA, USA.
7
Department of Special Education, Vanderbilt University, Nashville, TN, USA.
8
Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA.
9
Program in Neuroscience, Stanford University School of Medicine, Stanford, CA, USA.
10
Symbolic Systems Program, Stanford University School of Medicine, Stanford, CA, USA.

Abstract

Plasticity of white matter tracts is thought to be essential for cognitive development and academic skill acquisition in children. However, a dearth of high-quality diffusion tensor imaging (DTI) data measuring longitudinal changes with learning, as well as methodological difficulties in multi-time point tract identification have limited our ability to investigate plasticity of specific white matter tracts. Here, we examine learning-related changes of white matter tracts innervating inferior parietal, prefrontal and temporal regions following an intense 2-month math tutoring program. DTI data were acquired from 18 third grade children, both before and after tutoring. A novel fiber tracking algorithm based on a White Matter Query Language (WMQL) was used to identify three sections of the superior longitudinal fasciculus (SLF) linking frontal and parietal (SLF-FP), parietal and temporal (SLF-PT) and frontal and temporal (SLF-FT) cortices, from which we created child-specific probabilistic maps. The SLF-FP, SLF-FT, and SLF-PT tracts identified with the WMQL method were highly reliable across the two time points and showed close correspondence to tracts previously described in adults. Notably, individual differences in behavioral gains after 2 months of tutoring were specifically correlated with plasticity in the left SLF-FT tract. Our results extend previous findings of individual differences in white matter integrity, and provide important new insights into white matter plasticity related to math learning in childhood. More generally, our quantitative approach will be useful for future studies examining longitudinal changes in white matter integrity associated with cognitive skill development.

KEYWORDS:

Academic; Arithmetic; Diffusion tensor imaging (DTI); Learning; Plasticity; Superior longitudinal fasciculus

PMID:
25604464
PMCID:
PMC4819785
DOI:
10.1007/s00429-014-0975-6
[Indexed for MEDLINE]
Free PMC Article

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