https://scholars.lib.ntu.edu.tw/handle/123456789/425881
標題: | Quantifying Differences and Similarities in Whole-Brain White Matter Architecture Using Local Connectome Fingerprints | 作者: | Yeh, Fang Cheng Vettel, Jean M. Singh, Aarti Poczos, Barnabas Grafton, Scott T. Erickson, Kirk I. WEN-YIH TSENG Verstynen, Timothy D. |
公開日期: | 1-十一月-2016 | 卷: | 12 | 期: | 11 | 來源出版物: | PLoS Computational Biology | 摘要: | © 2016 Public Library of Science. All rights reserved. Quantifying differences or similarities in connectomes has been a challenge due to the immense complexity of global brain networks. Here we introduce a noninvasive method that uses diffusion MRI to characterize whole-brain white matter architecture as a single local connectome fingerprint that allows for a direct comparison between structural connectomes. In four independently acquired data sets with repeated scans (total N = 213), we show that the local connectome fingerprint is highly specific to an individual, allowing for an accurate self-versus-others classification that achieved 100% accuracy across 17,398 identification tests. The estimated classification error was approximately one thousand times smaller than fingerprints derived from diffusivity-based measures or region-to-region connectivity patterns for repeat scans acquired within 3 months. The local connectome fingerprint also revealed neuroplasticity within an individual reflected as a decreasing trend in self-similarity across time, whereas this change was not observed in the diffusivity measures. Moreover, the local connectome fingerprint can be used as a phenotypic marker, revealing 12.51% similarity between monozygotic twins, 5.14% between dizygotic twins, and 4.51% between none-twin siblings, relative to differences between unrelated subjects. This novel approach opens a new door for probing the influence of pathological, genetic, social, or environmental factors on the unique configuration of the human connectome. |
URI: | https://www2.scopus.com/inward/record.uri?eid=2-s2.0-84999837365&doi=10.1371%2fjournal.pcbi.1005203&partnerID=40&md5=95df1224b7b31f6651b699f8cbc82b88 https://scholars.lib.ntu.edu.tw/handle/123456789/425881 |
ISSN: | 1553734X | DOI: | 10.1371/journal.pcbi.1005203 |
顯示於: | 醫療器材與醫學影像研究所 |
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