https://scholars.lib.ntu.edu.tw/handle/123456789/425881
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Yeh, Fang Cheng | en_US |
dc.contributor.author | Vettel, Jean M. | en_US |
dc.contributor.author | Singh, Aarti | en_US |
dc.contributor.author | Poczos, Barnabas | en_US |
dc.contributor.author | Grafton, Scott T. | en_US |
dc.contributor.author | Erickson, Kirk I. | en_US |
dc.contributor.author | WEN-YIH TSENG | en_US |
dc.contributor.author | Verstynen, Timothy D. | en_US |
dc.creator | Verstynen, Timothy D.;WEN-YIH ISAAC TSENG;Erickson, Kirk I.;Grafton, Scott T.;Poczos, Barnabas;Singh, Aarti;Vettel, Jean M.;Yeh, Fang Cheng | - |
dc.date.accessioned | 2019-10-03T05:44:14Z | - |
dc.date.available | 2019-10-03T05:44:14Z | - |
dc.date.issued | 2016-11-01 | - |
dc.identifier.issn | 1553734X | - |
dc.identifier.uri | https://www2.scopus.com/inward/record.uri?eid=2-s2.0-84999837365&doi=10.1371%2fjournal.pcbi.1005203&partnerID=40&md5=95df1224b7b31f6651b699f8cbc82b88 | - |
dc.identifier.uri | https://scholars.lib.ntu.edu.tw/handle/123456789/425881 | - |
dc.description.abstract | © 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_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | PLoS Computational Biology | en_US |
dc.title | Quantifying Differences and Similarities in Whole-Brain White Matter Architecture Using Local Connectome Fingerprints | en_US |
dc.type | journal article | en |
dc.identifier.doi | 10.1371/journal.pcbi.1005203 | - |
dc.identifier.pmid | 27846212 | - |
dc.identifier.scopus | 2-s2.0-84999837365 | - |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/84999837365 | - |
dc.relation.journalvolume | 12 | en_US |
dc.relation.journalissue | 11 | en_US |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
item.fulltext | no fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
item.openairetype | journal article | - |
item.grantfulltext | none | - |
crisitem.author.dept | Medical Device and Imaging | - |
crisitem.author.dept | Biomedical Engineering | - |
crisitem.author.dept | Brain and Mind Sciences | - |
crisitem.author.dept | Medical Imaging-NTUH | - |
crisitem.author.orcid | 0000-0002-2314-6868 | - |
crisitem.author.parentorg | College of Medicine | - |
crisitem.author.parentorg | College of Medicine | - |
crisitem.author.parentorg | College of Engineering | - |
crisitem.author.parentorg | College of Medicine | - |
crisitem.author.parentorg | National Taiwan University Hospital | - |
顯示於: | 醫療器材與醫學影像研究所 |
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