Brain tumors can
alter not only functions located in the perilesional area, but also the distal
ones. Thus, the possibility to inform preoperatively surgeons about the state
of preservation/alteration of a network could be a powerful aid for a better
patient outcome. In this work we used independent component analysis (ICA) to
map resting state networks (RSNs) at the single-subject level characterizing
their alterations in terms of cosine similarity spatial patterns. Comparing the
patient-specific spatial maps with those obtained for a group of healthy
controls, we defined the presence of an alteration for each of the 44 analyzed
RSNs.
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