Version 1
: Received: 1 May 2019 / Approved: 6 May 2019 / Online: 6 May 2019 (07:47:11 CEST)
How to cite:
Conti, A.; Duggento, A.; Guerrisi, M.; Passamonti, L.; Indovina, I.; Toschi, N. Variability and Reproducibility of Directed and Undirected Functional MRI Connectomes in the Human Brain. Preprints2019, 2019050031. https://doi.org/10.20944/preprints201905.0031.v1
Conti, A.; Duggento, A.; Guerrisi, M.; Passamonti, L.; Indovina, I.; Toschi, N. Variability and Reproducibility of Directed and Undirected Functional MRI Connectomes in the Human Brain. Preprints 2019, 2019050031. https://doi.org/10.20944/preprints201905.0031.v1
Conti, A.; Duggento, A.; Guerrisi, M.; Passamonti, L.; Indovina, I.; Toschi, N. Variability and Reproducibility of Directed and Undirected Functional MRI Connectomes in the Human Brain. Preprints2019, 2019050031. https://doi.org/10.20944/preprints201905.0031.v1
APA Style
Conti, A., Duggento, A., Guerrisi, M., Passamonti, L., Indovina, I., & Toschi, N. (2019). Variability and Reproducibility of Directed and Undirected Functional MRI Connectomes in the Human Brain. Preprints. https://doi.org/10.20944/preprints201905.0031.v1
Chicago/Turabian Style
Conti, A., Iole Indovina and Nicola Toschi. 2019 "Variability and Reproducibility of Directed and Undirected Functional MRI Connectomes in the Human Brain" Preprints. https://doi.org/10.20944/preprints201905.0031.v1
Abstract
A growing number of studies focus 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, 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 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.
Keywords
functional networks; functional magnetic resonance imaging; connectome; connectivity matrices; graphs; reproducibility; granger causality; transfer entropy
Subject
Biology and Life Sciences, Biophysics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
,
