  Recent studies indicate that the neurons involved in a cognitive task aren't
locally limited but span out to multiple human brain regions. We obtain network
components and their locations for the task of listening to music. The recorded
EEG data is modeled as a graph, and it is assumed that the overall activity is
a contribution of several independent subnetworks. To identify these intrinsic
cognitive subnetworks corresponding to music perception, we propose to
decompose the whole brain graph-network into multiple subnetworks. We perform
this decomposition to a group of brain networks by performing Graph-Independent
Component Analysis. Graph-ICA is a variant of ICA that decomposes the measured
graph into independent source graphs. Having obtained independent subnetworks,
we calculate the electrode positions by computing the local maxima of these
subnetwork matrices. We observe that the computed electrodes' location
corresponds to the temporal lobes and the Broca's area, which are indeed
involved in the task of auditory processing and perception. The computed
electrodes also span the brain's frontal lobe, which is involved in attention
and generating a stimulus-evoked response. The weight of the subnetwork that
corresponds to the aforementioned brain regions increases with the increase in
the music recording's tempo. The results suggest that whole-brain networks can
be decomposed into independent subnetworks and analyze cognitive responses to
music stimulus.
