Connectomic consistency: a systematic stability analysis of structural and functional connectivity

• Published in: Journal of neural engineering 2020-07, Vol.17 (4), p.045004-045004
• Main Authors: Osmanl o lu, Yusuf, Alappatt, Jacob A, Parker, Drew, Verma, Ragini
• Format: Article
• Language: English
• Subjects: Algorithms; Brain - diagnostic imaging; Connectome; consistency; dMRI; DTI; Humans; Magnetic Resonance Imaging; Neurobiology; rs-fMRI
• ISSN: 1741-2560; 1741-2552; 1741-2552
• DOI: 10.1088/1741-2552/ab947b

Objective. Connectomics, the study of brain connectivity, has become an indispensable tool in neuroscientific research as it provides insights into brain organization. Connectomes are generated using different modalities such as diffusion MRI to capture structural organization of the brain or functional MRI to elaborate brain's functional organization. Understanding links between structural and functional organizations is crucial in explaining how observed behavior emerges from the underlying neurobiological mechanisms. Many studies have investigated how these two organizations relate to each other; however, we still lack a comparative understanding on how much variation should be expected in the two modalities, both between people and within a single person across scans. Approach. In this study, we systematically analyzed the consistency of connectomes, that is the similarity between connectomes in terms of individual connections between brain regions and in terms of overall network topology. We present a comprehensive study of consistency in connectomes for a single subject examined longitudinally and across a large cohort of subjects cross-sectionally, in structure and function separately. Within structural connectomes, we compared connectomes generated by different tracking algorithms, parcellations, edge weighting schemes, and edge pruning techniques. In functional connectomes, we compared full, positive, and negative connectivity separately along with thresholding of weak edges. We evaluated consistency using correlation (incorporating information at the level of individual edges) and graph matching accuracy (evaluating connectivity at the level of network topology). We also examined the consistency of connectomes that are generated using different communication schemes. Main results. Our results demonstrate varying degrees of consistency for the two modalities, with structural connectomes showing higher consistency than functional connectomes. Moreover, we observed a wide variation in consistency depending on how connectomes are generated. Significance. Our study sets a reference point for consistency of connectome types, which is especially important for structure-function coupling studies in evaluating mismatches between modalities.