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Nat Neurosci. 2015 Nov;18(11):1664-71. doi: 10.1038/nn.4135. Epub 2015 Oct 12.

Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity.

Author information

1
Interdepartmental Neuroscience Program, Yale University, New Haven, Connecticut, USA.
2
Department of Diagnostic Radiology, Yale School of Medicine, New Haven, Connecticut, USA.
3
Department of Psychology, Yale University, New Haven, Connecticut, USA.
4
Department of Neurobiology, Yale University, New Haven, Connecticut, USA.
5
Department of Biomedical Engineering, Yale University, New Haven, Connecticut, USA.
6
Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut, USA.

Abstract

Functional magnetic resonance imaging (fMRI) studies typically collapse data from many subjects, but brain functional organization varies between individuals. Here we establish that this individual variability is both robust and reliable, using data from the Human Connectome Project to demonstrate that functional connectivity profiles act as a 'fingerprint' that can accurately identify subjects from a large group. Identification was successful across scan sessions and even between task and rest conditions, indicating that an individual's connectivity profile is intrinsic, and can be used to distinguish that individual regardless of how the brain is engaged during imaging. Characteristic connectivity patterns were distributed throughout the brain, but the frontoparietal network emerged as most distinctive. Furthermore, we show that connectivity profiles predict levels of fluid intelligence: the same networks that were most discriminating of individuals were also most predictive of cognitive behavior. Results indicate the potential to draw inferences about single subjects on the basis of functional connectivity fMRI.

PMID:
26457551
PMCID:
PMC5008686
DOI:
10.1038/nn.4135
[Indexed for MEDLINE]
Free PMC Article
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