all having the same timecourse (according to the model). If a higher number of components is estimated79, these are more likely to be smaller regions (parcels), which can then be considered as nodes for use in network analysis80, where the spatial maps are used to define subject-specific time courses (the first stage of dual regression1). These time courses are used to estimate the size of signal fluctuation in each node, as well as to estimate connectivity between pairs of nodes using L2-regularised partial correlation81. The connectivity estimates are provided as IDPs at both parcellation dimensionalities (25 and 100 nodes); after removal of group-ICA components considered to be artefactual (i.e., relating either to scanning artefacts, or to non-neuronal biophysical processes such as cardiac fluctuations and head motion), this results in 21 and (respectively) 55 nodes left for forming the IDPs such as network matrices (functional connectivities between pairs of nodes).
