Literature DB >> 19684204

What does an insect see?

Adrian Horridge1.   

Abstract

The compound eye of the bee is an array of photoreceptors, each at an angle to the next, and therefore it catches an image of the outside world just as does the human eye, except that the image is not inverted. Eye structure, however, tells us little about what the bee actually abstracts from the panorama. Moreover, it is not sufficient to observe that bees recognise patterns, because they may be responding to only small parts of them. The only way we can tell what the bee actually detects is to train bees to come to simple patterns or distinguish between two patterns and then present the trained bees with test patterns to see what they have learned. After much training and numerous tests, it was possible to identify the parameters in the patterns that the bees detected and remembered, to study the responses of the trained bees to unfamiliar patterns and to infer the steps in the visual processing mechanism. We now have a simple mechanistic explanation for many observations that for almost a century have been explained by analogy with cognitive behaviour of higher animals. A re-assessment of the capabilities of the bee is required. Below the photoreceptors, the next components of the model mechanism are small feature detectors that are one, two or three ommatidia wide that respond to light intensity, direction of passing edges or orientation of edges displayed by parameters in the pattern. At the next stage, responses of the feature detectors for area and edges are summed in various ways in each local region of the eye to form several types of local internal feature totals, here called cues. The cues are the units of visual memory in the bee. At the next stage, summation implies that there is one of each type in each local eye region and that local details of the pattern are lost. Each type of cue has its own identity, a scalar quantity and a position. The coincidence of the cues in each local region of the eye is remembered as a retinotopic label for a landmark. Bees learn landmark labels at large angles to each other and use them to identify a place and find the reward. The receptors, feature detectors, cues and coincidences of labels for landmarks at different angles, correspond to a few letters, words and sentences and a summary description for a place. Shapes, objects and cognitive appraisal of the image have no place in bee vision. Several factors prevented the advance in understanding until recently. Firstly, until the mid-century, so little was known that no mechanisms were proposed. At that time it was thought that the mechanism of the visual processing could be inferred intuitively from a successful training alone or from quantitative observations of the percentage of correct choices after manipulation of the patterns displayed. The components were unknown and there were too many unidentified channels of causation in parallel (too many cues learned at the same time) for this method to succeed. Secondly, for 100 years, the criterion of success of the bees was their landing at or near the reward hole in the centre of the pattern. At the moment of choice, therefore, the angle subtended by the pattern at the eye of the bees was very large, 100-130 deg., with the result that a large part of the eye learned a number of cues and several labels on the target. As a result, in critical tests the bees would not respond but just went away, so that the components of the system could not be identified. Much effort was therefore wasted. These problems were resolved when the size of the target was reduced to about the size of one or two fields of the cues and landmark labels, 40-45 deg., and the trained bees were tested to see whether they could or could not recognise the test targets.

Entities:  

Mesh:

Year:  2009        PMID: 19684204     DOI: 10.1242/jeb.030916

Source DB:  PubMed          Journal:  J Exp Biol        ISSN: 0022-0949            Impact factor:   3.312


  11 in total

1.  Report on the 12th symposium on invertebrate neurobiology held 31 August-4 September 2011 at the Balaton Limnological Research Institute of the Hungarian Academy of Sciences, Tihany, Hungary.

Authors:  Lindy Holden-Dye; Robert J Walker
Journal:  Invert Neurosci       Date:  2012-04-06

2.  Reply to Cheung et al.: The cognitive map hypothesis remains the best interpretation of the data in honeybee navigation.

Authors:  James F Cheeseman; Craig D Millar; Uwe Greggers; Konstantin Lehmann; Matthew D M Pawley; Charles R Gallistel; Guy R Warman; Randolf Menzel
Journal:  Proc Natl Acad Sci U S A       Date:  2014-10-02       Impact factor: 11.205

3.  The forest or the trees: preference for global over local image processing is reversed by prior experience in honeybees.

Authors:  Aurore Avarguès-Weber; Adrian G Dyer; Noha Ferrah; Martin Giurfa
Journal:  Proc Biol Sci       Date:  2015-01-22       Impact factor: 5.349

4.  Discrimination of edge orientation by bumblebees.

Authors:  Marie Guiraud; Mark Roper; Stephan Wolf; Joseph L Woodgate; Lars Chittka
Journal:  PLoS One       Date:  2022-06-16       Impact factor: 3.752

5.  Aversive reinforcement improves visual discrimination learning in free-flying honeybees.

Authors:  Aurore Avarguès-Weber; Maria G de Brito Sanchez; Martin Giurfa; Adrian G Dyer
Journal:  PLoS One       Date:  2010-10-15       Impact factor: 3.240

6.  Honeybees can discriminate between Monet and Picasso paintings.

Authors:  Wen Wu; Antonio M Moreno; Jason M Tangen; Judith Reinhard
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2012-10-18       Impact factor: 1.836

7.  Long term effects of aversive reinforcement on colour discrimination learning in free-flying bumblebees.

Authors:  Miguel A Rodríguez-Gironés; Alejandro Trillo; Guadalupe Corcobado
Journal:  PLoS One       Date:  2013-08-12       Impact factor: 3.240

8.  A mismatch between the perceived fighting signal and fighting ability reveals survival and physiological costs for bearers.

Authors:  Isaac González-Santoyo; Daniel M González-Tokman; Roberto E Munguía-Steyer; Alex Córdoba-Aguilar
Journal:  PLoS One       Date:  2014-01-07       Impact factor: 3.240

9.  Functional Significance of Labellum Pattern Variation in a Sexually Deceptive Orchid (Ophrys heldreichii): Evidence of Individual Signature Learning Effects.

Authors:  Kerstin Stejskal; Martin Streinzer; Adrian Dyer; Hannes F Paulus; Johannes Spaethe
Journal:  PLoS One       Date:  2015-11-16       Impact factor: 3.240

10.  Innate pattern recognition and categorization in a jumping spider.

Authors:  Yinnon Dolev; Ximena J Nelson
Journal:  PLoS One       Date:  2014-06-03       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.