Visual perception of planar-rotated 2D objects in goldfish (Carassius auratus)

Visual Perception of Photographs of Rotated 3D Objects in Goldfish (Carassius auratus)

This study examined goldfishes' ability to recognize photographs of rotated 3D objects. Six goldfish were presented with color photographs of a plastic model turtle and frog at 0° in a two-alternative forced-choice task. Fish were tested with stimuli at 0°, 90°, 180°, and 270° rotated in the picture plane and two depth planes. All six fish performed significantly above chance at all orientations in the three rotation planes tested. There was no significant difference in performance as a function of aspect angle, which supported viewpoint independence. However, fish were significantly faster at 180° than at +/-90°, so there is also evidence for viewpoint-dependent representations. These fish subjects performed worse overall in the current study with 2D color photographs (M = 88.0%) than they did in our previous study with 3D versions of the same turtle and frog stimuli (M = 92.6%), although they performed significantly better than goldfish in our two past studies presented with black and white 2D stimuli (M = 67.6% and 69.0%). The fish may have relied on color as a salient cue. This study was a first attempt at examining picture-object recognition in fish. More work is needed to determine the conditions under which fish succeed at object constancy tasks, as well as whether they are capable of perceiving photographs as representations of real-world objects.

Recognition of natural objects in the archerfish

Recognition of individual objects and their categorization is a complex computational task. Nevertheless, visual systems can perform this task in a rapid and accurate manner. Humans and other animals can efficiently recognize objects despite countless variations in their projection on the retina due to different viewing angles, distance, illumination conditions and other parameters. To gain a better understanding of the recognition process in teleosts, we explored it in archerfish, a species that hunts by shooting a jet of water at aerial targets and thus can benefit from ecologically relevant recognition of natural objects. We found that archerfish not only can categorize objects into relevant classes but also can do so for novel objects, and additionally they can recognize an individual object presented under different conditions. To understand the mechanisms underlying this capability, we developed a computational model based on object features and a machine learning classifier. The analysis of the model revealed that a small number of features was sufficient for categorization, and the fish were more sensitive to object contours than textures. We tested these predictions in additional behavioral experiments and validated them. Our findings suggest the existence of a complex visual process in the archerfish visual system that enables object recognition and categorization.

Highlighted Article: Archerfish are capable of natural object recognition and categorization based on a small number of visual features.