Vasas V, Chittka L. Insect-Inspired Sequential Inspection Strategy Enables an Artificial Network of Four Neurons to Estimate Numerosity.
iScience 2018;
11:85-92. [PMID:
30590253 PMCID:
PMC6308245 DOI:
10.1016/j.isci.2018.12.009]
[Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Revised: 11/29/2018] [Accepted: 12/05/2018] [Indexed: 11/25/2022] Open
Abstract
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.
Small-brained animals such as bees can solve counting tasks
Exceedingly small neural circuits can mediate numerosity estimations
The method requires a sequential inspection strategy to generate the visual input
Active scanning behavior is suggested to play a role in complex cognitive tasks
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