This is matlab code to run simulations for the CTLN model introduced in the paper https://arxiv.org/abs/1605.04463 .
This is a bare bones package to run simple simulations and make plots using the CTLN model. Details about the model can be found in the following preprint:
Diversity of emergent dynamics in competitive threshold-linear networks: a preliminary report.
Katherine Morrison, Anda Degeratu, Vladimir Itskov & Carina Curto. Available at https://arxiv.org/abs/1605.04463
The code was written by Carina Curto and Katherine Morrison, and packaged together on May 22, 2016.
SUMMARY OF THE CODE:
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The adjacency matrix sA: The basic input object that defines a CTLN model is an nxn matrix "sA", which is the adjacency matrix for a simple directed graph on n nodes (neurons). sA should be a binary matrix with zeros on the diagonal. Our convention (due to the form of the ODEs) is that sA(i,j) = 1 iff j->i in the graph. sA is thus the transpose of the usual adjacency matrix.
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run_CTLN_model_script.m: This is a sample executable that allows you to enter an sA matrix (or load a saved example matrix, or generate one at random with randDigraph.m), and then simulate the corresponding CTLN model with a choice of parameters and initial conditions.
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The simulations are done by the function sA2soln.m, which returns a "soln" structure. The results are plotted using the function plot_soln.m, using "soln" as input.
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engineering_script.m: This script illustrates how to use the function patterns2sA.m in order to engineer networks with prescribed dynamic patterns. It also calls sA2soln.m and plot_soln.m.
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All other functions are either plotting routines, called by plot_soln.m, or functions used in the simulations, called by sA2soln.m.