A high Clustering Coefficient (CC) in combination with a low Characteristic Path Length
(CPL) are the defining characteristics of the category of graphs called small-world
Numerical results have shown that small-world networks are highly
efficient and robust in terms of information spreading .
In this sense, small-world
networks are optimal functional architectures for information processing.
architectures are predominant in networks like the Internet, social communication
networks, and other networks that communicate through sparse connections [3,4].
Recently, the functional architecture of the brain was shown to have small-world
In  it was shown that an algorithm coupled chaotic activation functions consistently
evolve to small-world structures.
Chaotic activation has been observed in various real-life
We may, therefore, propose the chaotic-adaptive rewiring
algorithm as an extremely simplified model for the evolution of small-world connectivity
in the brain.
Recent studies have shown that the human visual cortex consists of various densely connected
cluster with relatively few connections between them .
The suspicion is that the previously
presented algorithm produces very similar networks. The goal of this study is to investigate these properties.
Part 1 - Survey
In the Survey, connections should be labeled by an integer value which replaces the boolean
As such, the connections 'movement' can be traced throughout the network's evolution.
A network of 400 units with 5000 connections should be used. It should be iterated 4 000 000 times
and during this cycle, a record of all changes in connections should be kept.
In an initial phase,
it could be taken every 1000 iterations to gain a global perspective.
Goal of this survey is to verify or falsify the hypothesis that when this network reaches its global
a small percentage of connections keeps changing whereas a large part becomes
fixed within the clusters.
Part 2 - Analysis
This part will only be commenced in succession to succesful completement of part 1. After analysing
which connections stay fixed,
it might be possible to determine which units and connections form
fixed clusters and what their size is. In an extended case, other networks could be probed.
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