Effects of Network Topology on Decision-Making in a Biological Network Model

The topology of a network often plays a crucial role in determining its dynamical features. The present study investigated how the network structure influences decision-making behaviors in the brain. We construct a recurrent network model to simulate the decision-making process of brain with three topological networks: regular, random, and small-world. We found that the regular and the small-world networks show significant better performance of decision-making than that in the random network when the internal noise of the networks is low. However, following the increase of the internal noise, the random network, instead of two other networks, shows better ability to resist the noise. Together, our results indicate that network topology significantly influence the network behaviors in our model of decision-making.