Synchronization in Electrically Coupled Neural Networks
  In this report, we investigate the synchronization of temporal activity in an electrically coupled neural network model. The electrical coupling is established by homotypic static gap-junctions (Connexin 43). Two distinct network topologies, namely: {\em sparse random network, (SRN)} and {\em fully connected network, (FCN)} are used to establish the connectivity. The strength of connectivity in the FCN is governed by the {\em mean gap junctional conductance} ($\mu$). In the case of the SRN, the overall strength of connectivity is governed by the {\em density of connections} ($\delta$) and the connection strength between two neurons ($S_0$). The synchronization of the network with increasing gap junctional strength and varying population sizes is investigated. It was observed that the network {\em abruptly} makes a transition from a weakly synchronized to a well synchronized regime when ($\delta$) or ($\mu$) exceeds a critical value. It was also observed that the ($\delta$, $\mu$) values used to achieve synchronization decreases with increasing network size. 
Rajesh G Kavasseri, Radhakrishnan Nagarajan