  In this paper we utilized the concept of stable phase synchronization
topography - synchrostates - over the scalp derived from EEG recording for
formulating brain connectivity network in Autism Spectrum Disorder (ASD) and
typically-growing children. A synchronization index is adapted for forming the
edges of the connectivity graph capturing the stability of each of the
synchrostates. Such network is formed for 11 ASD and 12 control group children.
Comparative analyses of these networks using graph theoretic measures show that
children with autism have a different modularity of such networks from typical
children. This result could pave the way to a new modality for possible
identification of ASD from non-invasively recorded EEG data.

Medical Physics;Neurons and Cognition;Applications