Ongoing (Aug 2016 _ Present)
CSTC is the main body for planning and decision-making in the field of cognitive science and technologies in Iran. The council provides financial support to public and private institutions, academicians and researchers who conduct research and contribute to the field.
On section on network analysis
It is planned to use network segregation metrics used to quantify the modularity of the network i.e. to determine if a network has specialized sub-networks in itself. Clustering coefficient and transitivity are the two most widely used metrics of segregation. The former directly quantifies the modularity of a network around individual nodes if calculated locally (for one node).We intend to consider these measures as part of quantification and characterization of brain network.
An important metrics to be considered in our analysis is measures of integration used to quantify the network’s ability to stream information between its many nodes and specialized modules. One of the simplest integration metrics is characteristic path length. Locally, it is defined as the number of edges in the shortest path available between two nodes. However, it is usually considered globally with averaging the characteristic path length of all node pairs in a network. As stated in summary section of this proposal, necessary software routines will be developed and added to the open source software routines to cover the additional network analysis and quantification as needed in the project.
Collaborators:
Adjunct Professor of Electrical and Computer Engineering at The University of British Columbia
Professor of Pediatric Neurology at Shahid Beheshti University of Medical Sciences
Assistant Professor of Child Neurology at Shahid Beheshti University of Medical Sciences
Farnaz Mohammadi
B.Sc. Student at University of Tehran
Ghazal Sahebzamani
B.Sc. Student at University of Tehran