Modeling cortical synaptic effects of anesthesia and their cholinergic reversal
Fig 11
Parameter search fine-tuned through Differential Evolution algorithm.
A). Evolutionary algorithm procedure, differential evolution, was used to optimize model parameters. For each generation, 10 agents (parameter sets) with the highest cost function from the population of 30, were chosen for replacement. Algorithm was repeated until stopping criteria of 100 generations without change in lowest cost function value across the population was met. B,C) Example optimization cost of lowest cost parameters across the population for each generation in the A-series (B) and B-series (C). Population A1/B1, A2/B2, A3/B3 and A4/B4 were optimized to experimental data from the 0%, 2%, 4% and 6% anesthetic cases, respectively. The optimizations for A1 and B1 were identical. In the A-series (A2-A4), PNDMA, PGABA, were optimized and in the B-Series (B2-B4), PNDMA, PGABA, gKs were varied.