1Clinical Sciences, Intervention and Technology, Karolinska Institute, Stockholm, Sweden, 2Medical Physics, Karolinska University Hospital, Stockholm, Sweden
A data-driven analysis method based on
hierarchical clustering was used to analyze the sensory-motor resting-state
network from resting-state fMRI data. It was used to analyze the network’s functional
sub-division, and intra-network functional organization, in different levels of
detail. Sub-network for the sensory-motor network as obtained by hierarchical
clustering is anatomically and functionally sensible. Further sub-division of
the paracentral lobule network hub successfully revealed its functional
sub-division in great detail. The intra-network organization of intrinsic
functional connectivity derived from spontaneous activity of the brain at rest
reflects consistently, the functional and neural anatomic connectivity
topography of the resting-state network.
