COMPARATIVE STUDY
JOURNAL ARTICLE
RESEARCH SUPPORT, NON-U.S. GOV'T
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Disentangling the relation between left temporoparietal white matter and reading: A spherical deconvolution tractography study.

Diffusion tensor imaging (DTI) studies have shown that left temporoparietal white matter is related to phonological aspects of reading. However, DTI lacks the sensitivity to disentangle whether phonological processing is sustained by intrahemispheric connections, interhemispheric connections, or projection tracts. Spherical deconvolution (SD) is a nontensor model which enables a more accurate estimation of multiple fiber directions in crossing fiber regions. Hence, this study is the first to investigate whether the observed relation with reading aspects in left temporoparietal white matter is sustained by a particular pathway by applying a nontensor model. Second, measures of degree of diffusion anisotropy, which indirectly informs about white matter organization, were compared between DTI and SD tractography. In this study, 71 children (5-6 years old) participated. Intrahemispheric, interhemispheric, and projection pathways were delineated using DTI and SD tractography. Anisotropy indices were extracted, that is, fractional anisotropy (FA) in DTI and quantitative hindrance modulated orientational anisotropy (HMOA) in SD. DTI results show that diffusion anisotropy in both the intrahemispheric and projection tracts was positively correlated to phonological awareness; however, the effect was confounded by subjects' motion. In SD, the relation was restricted to the left intrahemispheric connections. A model comparison suggested that FA was, relatively to HMOA, more confounded by fiber crossings; however, anisotropy indices were highly related. In sum, this study shows the potential of SD to quantify white matter microstructure in regions containing crossing fibers. More specifically, SD analyses show that phonological awareness is sustained by left intrahemispheric connections and not interhemispheric or projection tracts.

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