Evolving processing speed asymmetries and hemispheric interactions in a neural network model

Substantial experimental data suggests that the cerebral hemispheres have different processing speeds, and that this may contribute to hemispheric specialization. Here, we use evolutionary computation models to examine whether asymmetric hemispheric processing speeds and lateralization can emerge in neural networks from the need to respond quickly to stimuli and/or to minimize energy consumption. Simulated neuroevolution produced networks with left-right asymmetric processing speeds whenever fitness depended on energy minimization, but not on quickness of response. The results also provide support for a recent hypothesis that subcortical cross-midline interactions are inhibitory/competitive.