Time Series Simulations

Wernickesarea has some compiled MikeNet code to generate simulate time series data for a small network that generates activation throughout a 3-layer network in response to inputs 0 and 1 (A and B). Activation of these units drives activation in 3 banks of 4 units in layer 1 (1A, 1NULL, 1B). Up to 4 1A units are active when input[0] is active, and up to 4 units of 1B are active when input[1] is active. The 1NNULL units are active only when both inputs are inactive. Also, one of the units in 1A and 1B are inhibited .8 of the time. 1A and 1B connect fully to 4 units in 2A and 2B respectively, and all units in 2A and 2B connect to layer3, which is maximally active only when both inputs are active (i.e., superadditivity).

Procedure

Generate Time Series

A shell script generates a specified (hard-coded) number of simulations:

#!/bin/bash
for i in $(seq -f "%04g" 0 999)
do
 echo $i
 ./xor >> simdat.txt
done

Remove Delimiters

Each of the banks of units are delimited by a ^ (caret) symbol for readability, but this character interferes with MATLAB import. To strip that character out with sed

sed -i 's/\^//g' simdat.txt #this syntax works on linux, but not on OSX

Conventional Correlation-Based Connectivity

The full work-up based on correlations is implemented in the script simdata_connectivity.m, which implements connectivity analyses posted elsewhere on this wiki. The interesting thing to look for is how do units 1 and 9 cluster, because these units are in banks 1A and 1B, respectively, but are inhibited .80 of the time. In a large data set, it looks like these units fail to cluster with their layer buddies because they are more weakly correlated.