Foraging is an embodied cognitive process which balances the
search constraints of exploration versus exploitation. As such,
foraging strategies and mechanisms offer useful insight into
abstract forms of search such as visual search, problem solving,
and semantic recall. We performed a series of simulations
using artificial neural networks to relate metastable neuronal
dynamics to observed foraging behaviors. We show that the
velocity and tortuosity of the foraging paths are influenced by
metastable neuronal activity, while resource collection is
unaffected. These initial results indicate that neuronal
metastability may contribute to foraging behaviors but
additional mechanisms are needed to optimally exploit
environmental resources.