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The disruption of specific white\u2010matter (WM) tracts\/regions has been observed in dyslexic children. However, it remains unknown if developmental dyslexia affects the human brain WM in a multidimensional manner. Being a natural tool for evaluating this hypothesis, the multivariate machine learning approach was applied in this study to compare 28 school\u2010aged dyslexic children with 33 age\u2010matched controls. Structural magnetic resonance imaging (MRI) and diffusion tensor imaging were acquired to extract five multitype WM features at a regional level: white matter volume, fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. A linear support vector machine (LSVM) classifier achieved an accuracy of 83.61% using these MRI features to distinguish dyslexic children from controls. Notably, the most discriminative features that contributed to the classification were primarily associated with WM regions within the putative reading network\/system (e.g., the superior longitudinal fasciculus, inferior fronto\u2010occipital fasciculus, thalamocortical projections, and corpus callosum), the limbic system (e.g., the cingulum and fornix), and the motor system (e.g., the cerebellar peduncle, corona radiata, and corticospinal tract). These results were well replicated using a logistic regression classifier. These findings provided direct evidence supporting a multidimensional effect of developmental dyslexia on WM connectivity of human brain, and highlighted the involvement of WM tracts\/regions beyond the well\u2010recognized reading system in dyslexia. Finally, the discriminating results demonstrated a potential of WM neuroimaging features as imaging markers for identifying dyslexic individuals.\n                    <jats:italic>Hum Brain Mapp 37:1443\u20101458, 2016<\/jats:italic>\n                    . \u00a9 2016 Wiley Periodicals, Inc.\n                  <\/jats:p>","DOI":"10.1002\/hbm.23112","type":"journal-article","created":{"date-parts":[[2016,1,20]],"date-time":"2016-01-20T01:26:46Z","timestamp":1453253206000},"page":"1443-1458","source":"Crossref","is-referenced-by-count":175,"title":["Disrupted white matter connectivity underlying developmental dyslexia: A machine learning approach"],"prefix":"10.1002","volume":"37","author":[{"given":"Zaixu","family":"Cui","sequence":"first","affiliation":[{"name":"State Key Laboratory of Cognitive Neuroscience and Learning &amp; IDG\/McGovern Institute for Brain Research, Beijing Normal University Beijing 100875 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhichao","family":"Xia","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Cognitive Neuroscience and Learning &amp; IDG\/McGovern Institute for Brain Research, Beijing Normal University Beijing 100875 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengmeng","family":"Su","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Cognitive Neuroscience and Learning &amp; IDG\/McGovern Institute for Brain Research, Beijing Normal University Beijing 100875 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hua","family":"Shu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Cognitive Neuroscience and Learning &amp; IDG\/McGovern Institute for Brain Research, Beijing Normal University Beijing 100875 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gaolang","family":"Gong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Cognitive Neuroscience and Learning &amp; IDG\/McGovern Institute for Brain Research, Beijing Normal University Beijing 100875 China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2016,1,20]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neurobiolaging.2006.09.003"},{"key":"e_1_2_6_3_1","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awr263"},{"key":"e_1_2_6_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2005.02.018"},{"key":"e_1_2_6_5_1","doi-asserted-by":"publisher","DOI":"10.1002\/nbm.782"},{"key":"e_1_2_6_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2004.12.053"},{"key":"e_1_2_6_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.conb.2007.03.006"},{"key":"e_1_2_6_8_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1244333"},{"key":"e_1_2_6_9_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1009715923555"},{"key":"e_1_2_6_10_1","doi-asserted-by":"publisher","DOI":"10.1177\/08830738050200101401"},{"key":"e_1_2_6_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/1961189.1961199"},{"key":"e_1_2_6_12_1","doi-asserted-by":"crossref","unstructured":"ChenXF KaoHSR(2002): Visual\u2010Spatial Properties and Orthographic Processing of Chinese Characters. 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