Variability and Reproducibility of Directed and Undirected Functional MRI Connectomes in the Human Brain

Abstract

A growing number of studies are focusing on methods to estimate and analyze the functional connectome of the human brain. Graph theoretical measures are commonly employed to interpret and synthesize complex network-related information. While resting state functional MRI (rsfMRI) is often employed in this context, it is known to exhibit poor reproducibility, a key factor which is commonly neglected in typical cohort studies using connectomics-related measures as biomarkers. We aimed to fill this gap by analyzing and comparing the inter- and intra-subject variability of connectivity matrices, as well as graph-theoretical measures, in a large (n = 1003) database of young healthy subjects which underwent four consecutive rsfMRI sessions. We analyzed both directed (Granger Causality and Transfer Entropy) and undirected (Pearson Correlation and Partial Correlation) time-series association measures and related global and local graph-theoretical measures. While matrix weights exhibit a higher reproducibility in undirected, as opposed to directed, methods, this difference disappears when looking at global graph metrics and, in turn, exhibits strong regional dependence in local graphs metrics. Our results warrant caution in the interpretation of connectivity studies, and serve as a benchmark for future investigations by providing quantitative estimates for the inter- and intra-subject variabilities in both directed and undirected connectomic measures.

Reorganization of the structural connectome in primary open angle Glaucoma

“…Local metrics: local strength, betweenness centrality, measures of centrality, local efficiency, clustering coefficient, measures of functional segregation. Global measures: global strength, global clustering coefficient, global efficiency and transitivity ( Conti et al, 2019 ). All metrics were computed using the Brain Connectivity Toolbox ( Rubinov and Sporns, 2010 ).…”

Dementia ConnEEGtome: Towards multicentric harmonization of EEG connectivity in neurodegeneration

“…Nevertheless, further investigation is needed before a composite connectivity metric can be proposed as the standard for neurodegenerative studies. This include assessing the robustness of the connectivity metrics to the intra-subject and inter-subject variability in longitudinal studies ( Conti et al, 2019 ).…”

Echo state network models for nonlinear Granger causality

“…ND are in general bounded within the interval [−1, 1] (figure 11a), however for the top 10% strongest estimated connections, the absolute value of the ND is lower than 0.3 (figure 11b). Considering the low reproducibility of resting state fMRI as quantified using the same data employed in this paper [52], this result points towards a satisfactory degree of robustness in our method. (see [52] for reproducibility for general GC in resting state fMRI).…”

“…Considering the low reproducibility of resting state fMRI as quantified using the same data employed in this paper [52], this result points towards a satisfactory degree of robustness in our method. (see [52] for reproducibility for general GC in resting state fMRI).…”