Functional Connectome Fingerprint Gradients in Young Adults

TL;DR

This study extends brain fingerprinting to include genetic and environmental influences by analyzing functional connectome gradients in young adults, revealing robust individual and twin similarities across multiple brain parcellations.

Contribution

We developed an extension of the differential identifiability framework to assess genetic and environmental brain fingerprint gradients in young adults.

Findings

Fingerprint gradients are consistent across all parcellations and conditions.

Optimal reconstruction of FCs reveals higher-resolution fingerprints.

Scanning length impacts the stability of subject fingerprints.

Abstract

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.