The Resting-State Causal Human Connectome is Characterized by Hub Connectivity of Executive and Attentional Networks

Abstract

We introduce a data-driven causal discovery method (Greedy Adjacencies and Non-Gaussian Orientations; GANGO) for calculating a "causal connectome" of directed connectivity from resting-state fMRI data and characterizing hubs of directed information transfer across the human cortex. Prominent hubs of the causal connectome were situated in attentional (dorsal attention) and executive (frontoparietal and cingulo-opercular) networks. These hub networks had distinctly different connectivity profiles. Attentional networks shared incoming connections with sensory regions and outgoing connections with higher cognitive networks, while executive networks primarily connected to other higher cognitive networks and had a high degree of bidirected connectivity. Virtual lesion analyses accentuated these findings, demonstrating that attentional and executive hubs are points of critical vulnerability in the human causal connectome. These data highlight the central role of attention and executive control networks in the human cortical connectome and set the stage for future applications of data-driven causal ("effective") connectivity analysis in psychiatry.

Power Analysis for Causal Discovery

“…It is increasingly being recognized that many scientific fields struggle to infer cause-effect relationships in contexts with large numbers of interacting elements, such as interacting collections of gene expressions, proteins, neurons, or symptoms. Researchers have started to apply causal discovery methods to solve problems like these and successfully discovered important causal relationships [21,[29][30][31][32][33][34][35][36][37]. However, prior to the work presented here, there were no methods for computing the power sample characteristics for causal discovery analysis, which has limited the ability of researchers to plan projects and interpret results.…”