AUTHOR=Qian Jingyu , Diez Ibai , Ortiz-Terán Laura , Bonadio Christian , Liddell Thomas , Goñi Joaquin , Sepulcre Jorge TITLE=Positive Connectivity Predicts the Dynamic Intrinsic Topology of the Human Brain Network JOURNAL=Frontiers in Systems Neuroscience VOLUME=12 YEAR=2018 URL=https://www.frontiersin.org/journals/systems-neuroscience/articles/10.3389/fnsys.2018.00038 DOI=10.3389/fnsys.2018.00038 ISSN=1662-5137 ABSTRACT=

Functional connectivity MRI (fcMRI) has become instrumental in facilitating research of human brain network organization in terms of coincident interactions between positive and negative synchronizations of large-scale neuronal systems. Although there is a common agreement concerning the interpretation of positive couplings between brain areas, a major debate has been made in disentangling the nature of negative connectivity patterns in terms of its emergence in several methodological approaches and its significance/meaning in specific neuropsychiatric diseases. It is still not clear what information the functional negative correlations or connectivity provides or how they relate to the positive connectivity. Through implementing stepwise functional connectivity (SFC) analysis and studying the causality of functional topological patterns, this study aims to shed light on the relationship between positive and negative connectivity in the human brain functional connectome. We found that the strength of negative correlations between voxel-pairs relates to their positive connectivity path-length. More importantly, our study describes how the spatio-temporal patterns of positive connectivity explain the evolving changes of negative connectivity over time, but not the other way around. This finding suggests that positive and negative connectivity do not display equivalent forces but shows that the positive connectivity has a dominant role in the overall human brain functional connectome. This phenomenon provides novel insights about the nature of positive and negative correlations in fcMRI and will potentially help new developments for neuroimaging biomarkers.