Using Brain Connectivity Measure of EEG Synchrostates for Discriminating Typical and Autism Spectrum Disorder
Institute of Electrical and Electronics Engineers (IEEE)
© 2014 IEEE
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.
This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.
2013 6th International IEEE/EMBS Conference on Neural Engineering (NER), San Diego, CA, USA, 6-8 November 2013, pp. 1402-1405