Next Article in Journal
Entropy and Information within Intrinsically Disordered Protein Regions
Previous Article in Journal
Estimating Topic Modeling Performance with Sharma–Mittal Entropy
Previous Article in Special Issue
A Parsimonious Granger Causality Formulation for Capturing Arbitrarily Long Multivariate Associations
Article Menu

Export Article

Open AccessArticle

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

1
Laboratory of Neuromotor Physiology, IRCCS Santa Lucia Foundation, 00179 Rome, Italy
2
Department of Biomedicine and Prevention, University of Rome Tor Vergata, 00133 Rome, Italy
3
Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
4
Institute of Bioimaging and Molecular Physiology, National Research Council, 20090 Milano, Italy
5
Saint Camillus International University of Health and Medical Sciences, 00131 Rome, Italy
6
Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA 02129, USA
*
Authors to whom correspondence should be addressed.
Entropy 2019, 21(7), 661; https://doi.org/10.3390/e21070661
Received: 1 May 2019 / Revised: 23 June 2019 / Accepted: 4 July 2019 / Published: 6 July 2019
(This article belongs to the Special Issue Information Dynamics in Brain and Physiological Networks)
  |  
PDF [4688 KB, uploaded 8 July 2019]
  |  

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. View Full-Text
Keywords: functional networks; functional magnetic resonance imaging; connectome; connectivity matrices; graphs; reproducibility; granger causality; transfer entropy functional networks; functional magnetic resonance imaging; connectome; connectivity matrices; graphs; reproducibility; granger causality; transfer entropy
Figures

Figure 1

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 (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

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. Entropy 2019, 21, 661.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top