Fig. 1.

Schematic representation of the procedure for the network-based independent component (IC) analysis. In each single-subject connectivity map (a), independent component (IC) analysis-based automatic removal of motion artifacts (ICA_AROMA) was applied (b). Pre-processed ‘clean’ resting state functional MRI data (c) were temporally concatenated across participants to create 4D group-level IC networks (d). A dual-regression procedure was performed and spatial maps of all participants were collected into single 4D files for each original IC (e). Finally, functional connectivity was investigated within each IC according to a specific general linear model. Here we provided the illustrative example of analysis at baseline (f): functional connectivity was compared between ALS patients and controls within each IC using a general linear model which includes the group as independent factor and accounts for voxel-based grey matter density. Abbreviations: ALS = amyotrophic lateral sclerosis; HC = healthy controls; GM = grey matter.