Functional connectomes (FCs) contain pairwise estimations of functional
couplings based on pairs of brain regions activity. FCs are commonly
represented as correlation matrices that are symmetric positive definite (SPD)
lying on or inside the SPD manifold. Since the geometry on the SPD manifold is
non-Euclidean, the inter-related entries of FCs undermine the use of
Euclidean-based distances. By projecting FCs into a tangent space, we can
obtain tangent functional connectomes (tangent-FCs). Tangent-FCs have shown a
higher predictive power of behavior and cognition, but no studies have
evaluated the effect of such projections with respect to fingerprinting. We
hypothesize that tangent-FCs have a higher fingerprint than regular FCs.
Fingerprinting was measured by identification rates (ID rates) on test-retest
FCs as well as on monozygotic and dizygotic twins. Our results showed that
identification rates are systematically higher when using tangent-FCs.
Specifically, we found: (i) Riemann and log-Euclidean matrix references
systematically led to higher ID rates. (ii) In tangent-FCs, Main-diagonal
regularization prior to tangent space projection was critical for ID rate when
using Euclidean distance, whereas barely affected ID rates when using
correlation distance. (iii) ID rates were dependent on condition and fMRI scan
length. (iv) Parcellation granularity was key for ID rates in FCs, as well as
in tangent-FCs with fixed regularization, whereas optimal regularization of
tangent-FCs mostly removed this effect. (v) Correlation distance in tangent-FCs
outperformed any other configuration of distance on FCs or on tangent-FCs
across the fingerprint gradient (here sampled by assessing test-retest,
Monozygotic and Dizygotic twins). (vi)ID rates tended to be higher in task
scans compared to resting-state scans when accounting for fMRI scan length.Comment: 29 pages, 10 figures, 2 table
