RT Journal Article
SR Electronic
T1 Local Connectome Fingerprinting Reveals the Uniqueness of Individual White Matter Architecture
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 043778
DO 10.1101/043778
A1 Fang-Cheng Yeh
A1 Jean M. Vettel
A1 Aarti Singh
A1 Barnabas Poczos
A1 Scott Grafton
A1 Kirk I. Erickson
A1 Wen-Yih I. Tseng
A1 Timothy D. Verstynen
YR 2016
UL http://biorxiv.org/content/early/2016/03/15/043778.abstract
AB It is generally assumed that the uniqueness of individual identity is reflected in the connective architecture of the human brain. Here we introduce local connectome fingerprinting, a noninvasive method that uses diffusion MRI to characterize white matter bundles as “fingerprints”. Using four independently acquired datasets (total n=213), we show that the local connectome fingerprint is highly specific to an individual, achieving 100% accuracy across 17,398 identification tests with an estimated classification error at 10−6. This uniqueness profile is higher than fingerprints derived from local fractional anisotropy or region-to-region connectivity patterns. We further illustrate that local connectome fingerprinting allows for quantifying similarity between genetically-associated individuals, e.g., monozygotic twins (12% connectomic similarity), and neuroplasticity with time, e.g., fingerprint uniqueness decreases 0.02% per day. This approach opens a new door for probing the influence of pathological, genetic, social, or environmental factors on the unique configuration of the human connectome.