Skip to main content
. Author manuscript; available in PMC: 2022 May 1.
Published in final edited form as: Neuroscience. 2021 Sep 8;489:111–142. doi: 10.1016/j.neuroscience.2021.08.035

Fig. 3. Accounting for heterogeneity and degeneracy in computational models.

Fig. 3

(A) Parameter values (Pi) are picked randomly from their respective experimental ranges. A set of parameters constitutes a model/individual, Mi. (B) MPMOSS algorithm. (C) Genetic algorithm (GA). Note that while MPMOSS is a highly parallelized algorithm, GA is by design iterative and spans several generations. There are several variants of the generic GA depicted here, with slight modifications to each step suited for different purposes.