Figure 1.
(A) Networks were randomly generated with n binary linear threshold nodes (Si ∈ {0, 1}, ϴ ≥ 1.0) and connections (Wij ∈ {−1, 0, 1}). Each network was perturbed into each possible initial state, and the following state transitions were recorded. (B) The networks’ node mechanism and connection weights were used to generate a transition probability matrix (TPM), containing the probability of one state leading to any other state. (C) From the TPM, we generated an “observed” time series using frequent perturbations of the initial states. The sequence of state transitions following an initial state perturbation is termed an epoch.