Yeh, Fang ChengFang ChengYehVettel, Jean M.Jean M.VettelSingh, AartiAartiSinghPoczos, BarnabasBarnabasPoczosGrafton, Scott T.Scott T.GraftonErickson, Kirk I.Kirk I.EricksonWEN-YIH TSENGVerstynen, Timothy D.Timothy D.Verstynen2019-10-032019-10-032016-11-011553734Xhttps://www2.scopus.com/inward/record.uri?eid=2-s2.0-84999837365&doi=10.1371%2fjournal.pcbi.1005203&partnerID=40&md5=95df1224b7b31f6651b699f8cbc82b88https://scholars.lib.ntu.edu.tw/handle/123456789/425881© 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.en[SDGs]SDG3journal article10.1371/journal.pcbi.1005203278462122-s2.0-84999837365https://api.elsevier.com/content/abstract/scopus_id/84999837365