Name
Abstract | ||
|---|---|---|
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. |
Year | Venue | Keywords |
|---|---|---|
2006 | Complex Systems | networks.,: synchronization,electrical coupling,neural network,network topology,population size,gap junction,neural network model,critical value |
Field | DocType | Volume |
Synchronization,Random graph,Random neural network,Computer science,Stochastic neural network,Computer network,Network topology,Echo state network,Artificial intelligence,Artificial neural network,Machine learning | Journal | 16 |
Issue | Citations | PageRank |
4 | 0 | 0.34 |
References | Authors | |
4 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rajesh G. Kavasseri | 1 | 31 | 6.98 |
| Radhakrishnan Nagarajan | 2 | 82 | 12.21 |