  The assessment of brain fingerprints has emerged in the recent years as an
important tool to study individual differences and to infer quality of
neuroimaging datasets. Studies so far have mainly focused on connectivity
fingerprints between different brain scans of the same individual. Here, we
extend the concept of brain connectivity fingerprints beyond test/retest and
assess fingerprint gradients in young adults by developing an extension of the
differential identifiability framework. To do so, we look at the similarity
between not only the multiple scans of an individual (subject fingerprint), but
also between the scans of monozygotic and dizygotic twins (twin fingerprint).
We have carried out this analysis on the 8 fMRI conditions present in the Human
Connectome Project -- Young Adult dataset, which we processed into functional
connectomes (FCs) and timeseries parcellated according to the Schaefer Atlas
scheme, which has multiple levels of resolution. Our differential
identifiability results show that the fingerprint gradients based on genetic
and environmental similarities are indeed present when comparing FCs for all
parcellations and fMRI conditions. Importantly, only when assessing optimally
reconstructed FCs, we fully uncover fingerprints present in higher resolution
atlases. We also study the effect of scanning length on subject fingerprint of
resting-state FCs to analyze the effect of scanning length and parcellation. In
the pursuit of open science, we have also made available the processed and
parcellated FCs and timeseries for all conditions for ~1200 subjects part of
the HCP-YA dataset to the scientific community.
