Using Social Network Analysis to enhance the understanding of Brain Connectivity

Graph-based network modelling is becoming increasingly pervasive touching at very different fields, ranging from social networks to brain connectivity. This works is a first attempt to borrow the concept of “transtopic messaging” from social network for its exploitation in the functional connectivity framework. Basically, different functional tasks are mapped to different “semantic topics”, and the overall relevance (according to given metrics) of the nodes of the network graph in ruling the spread of the different “topics” is assessed. This rises the connectivity analysis of one level of abstraction allowing to assess the overall transtopical relevance of each node of the graph providing information on the higher-level structure of the network.