Discrimination strategies of human and monkey for complex visual displays

By learning to discriminate among visual stimuli, human observers can become experts at specific visual tasks. The same is true for Rhesus monkeys, the major animal model of human visual perception. Here, we systematically compare how humans and monkeys solve a simple visual task. We trained humans and monkeys to discriminate between the members of small natural-image sets. We employed the “Bubbles” procedure [1] to determine the stimulus features used by the observers. On average, monkeys used image features drawn from a diagnostic region covering about 7% ± 2% of the images. Humans were able to use image features drawn from a much larger diagnostic region covering on average 51% ± 4% of the images. Similarly for the two species, however, about 2% of the image needed to be visible within the diagnostic region on any individual trial for correct performance. We characterize the low-level image properties of the diagnostic regions and discuss individual differences among the monkeys. Our results reveal tha t monkeys base their behavior on confined image patches and essentially ignore a large fraction of the visual input, whereas humans are able to gather visual information with greater flexibility from large image regions