Visual choice behavior by bumblebees (Bombus impatiens) confirms unsupervised neural network's predictions.

Abstract

The behavioral experiment herein tests the computational load hypothesis generated by an unsupervised neural network to examine bumblebee (Bombus impatiens) behavior at 2 visual properties: spatial frequency and symmetry. Untrained "flower-naïve" bumblebees were hypothesized to prefer symmetry only when the spatial frequency of artificial flowers is high and therefore places great information-processing demands on the bumblebees' visual system. Bumblebee choice behavior was recorded using high-definition motion-sensitive camcorders. The results support the computational model's prediction: 1-axis symmetry influenced bumblebees' preference behavior at low and high spatial frequency patterns. Additionally, increasing the level of symmetry from 1 axis to 4 axes amplified preference toward the symmetric patterns of both low and high spatial frequency patterns. The results are discussed in the context of the artificial neural network model and other hypotheses generated from the behavioral literature.