Insect-Inspired Sequential Inspection Strategy Enables an Artificial Network of Four Neurons to Estimate Numerosity

• Main Authors: Vera Vasas, Lars Chittka
• Format: Article
• Language: English
• Published: Elsevier 2019-01-01
• Series: iScience
• Online Access: http://www.sciencedirect.com/science/article/pii/S2589004218302384

Summary: Varying levels of numerical cognition have been found in several animal species. Bees, in particular, have been argued to be able to count up to four items and solve complex numerical tasks. Here we present an exceedingly simple neural circuit that, when provided with the actual visual input that the bee is receiving while carrying out the task, can make reliable estimates on the number of items in the display. Thus we suggest that the elegance of numerical problem solving in bees might not lie in the formation of numerical concepts (such as “more,” “less,” or “zero”), but in the use of specific flight movements to scan targets, which streamlines the visual input and so renders the task of counting computationally inexpensive. Careful examination of the actual inspection strategies used by animals might reveal that animals often employ active scanning behaviors as shortcuts to simplify complex visual pattern discrimination tasks. : Neuroscience; Cognitive Neuroscience; Biocomputational Method Subject Areas: Neuroscience, Cognitive Neuroscience, Biocomputational Method