• Kiho Im, Michael J Paldino, Annapurna Poduri, Olaf Sporns, and P Ellen Grant.
• Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA. Electronic address: Kiho.Im@childrens.harvard.edu.
• Neuroimage. 2014 Feb 1;86:182-93.

AbstractPolymicrogyria (PMG) is a cortical malformation characterized by multiple small gyri and altered cortical lamination, which may be associated with disrupted white matter connectivity. However, little is known about the topological patterns of white matter networks in PMG. We examined structural connectivity and network topology using individual primary gyral pattern-based nodes in PMG patients, overcoming the limitations of an atlas-based approach. Structural networks were constructed from structural and diffusion magnetic resonance images in 25 typically developing and 14 PMG subjects. The connectivity analysis for different fiber groups divided based on gyral topology revealed severely reduced connectivity between neighboring primary gyri (short U-fibers) in PMG, which was highly correlated with the regional involvement and extent of abnormal gyral folding. The patients also showed significantly reduced connectivity between distant gyri (long association fibers) and between the two cortical hemispheres. In relation to these results, gyral node-based graph theoretical analysis revealed significantly altered topological organization of the network (lower clustering and higher modularity) and disrupted network hub architecture in cortical association areas involved in cognitive and language functions in PMG patients. Furthermore, the network segregation in PMG patients decreased with the extent of PMG and the degree of language impairment. Our approach provides the first detailed findings and interpretations on altered cortical network topology in PMG related to abnormal cortical structure and brain function, and shows the potential for an individualized method to characterize network properties and alterations in connections that are associated with malformations of cortical development.© 2013 Elsevier Inc. All rights reserved.

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