Tangent functional connectomes uncover more unique phenotypic traits

Kausar Abbas; Mintao Liu; Michael Wang; Duy Duong-Tran; Uttara Tipnis; Enrico Amico; Alan D Kaplan; Mario Dzemidzic; David Kareken; Beau M Ances; Jaroslaw Harezlak; Joaquín Goñi

doi:10.1016/j.isci.2023.107624

Tangent functional connectomes uncover more unique phenotypic traits

iScience. 2023 Aug 12;26(9):107624. doi: 10.1016/j.isci.2023.107624. eCollection 2023 Sep 15.

Authors

Kausar Abbas^{1

2}, Mintao Liu^{1

2}, Michael Wang^{1

2}, Duy Duong-Tran^{3

4}, Uttara Tipnis⁵, Enrico Amico^{6

7}, Alan D Kaplan⁵, Mario Dzemidzic⁸, David Kareken⁸, Beau M Ances⁹, Jaroslaw Harezlak¹⁰, Joaquín Goñi^{1

2

11}

Affiliations

¹ Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA.
² School of Industrial Engineering, Purdue University, West Lafayette, IN, USA.
³ Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
⁴ Department of Mathematics, United States Naval Academy, Annapolis, MD, USA.
⁵ Lawrence Livermore National Laboratory, Livermore, CA, USA.
⁶ Institute of Bioengineering, Center for Neuroprosthetics, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland.
⁷ Department of Radiology and Medical Informatics, University of Geneva (UNIGE), Geneva, Switzerland.
⁸ Department of Neurology, Indiana University School of Medicine, Indiana Alcohol Research Center, Indianapolis, IN, USA.
⁹ Department of Neurology, Washington University in Saint Louis, School of Medicine, St Louis, MO, USA.
¹⁰ Department of Epidemiology and Biostatistics, Indiana University, Bloomington, IN, USA.
¹¹ Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA.

Abstract

Functional connectomes (FCs) containing pairwise estimations of functional couplings between pairs of brain regions are commonly represented by correlation matrices. As symmetric positive definite matrices, FCs can be transformed via tangent space projections, resulting into tangent-FCs. Tangent-FCs have led to more accurate models predicting brain conditions or aging. Motivated by the fact that tangent-FCs seem to be better biomarkers than FCs, we hypothesized that tangent-FCs have also a higher fingerprint. We explored the effects of six factors: fMRI condition, scan length, parcellation granularity, reference matrix, main-diagonal regularization, and distance metric. Our results showed that identification rates are systematically higher when using tangent-FCs across the "fingerprint gradient" (here including test-retest, monozygotic and dizygotic twins). Highest identification rates were achieved when minimally (0.01) regularizing FCs while performing tangent space projection using Riemann reference matrix and using correlation distance to compare the resulting tangent-FCs. Such configuration was validated in a second dataset (resting-state).

Keywords: Biological sciences; Phenotyping.