What does the honeybee see? And how do we know?

This book is the only account of what the bee, as an example of an insect, actually detects with its eyes. Bees detect some visual features such as edges and colours, but there is no sign that they reconstruct patterns or put together features to form objects. Bees detect motion but have no perception of what it is that moves, and certainly they do not recognize “things” by their shapes. Yet they clearly see well enough to fly and find food with a minute brain. Bee vision is therefore relevant to the construction of simple artificial visual systems, for example for mobile robots. The surprising conclusion is that bee vision is adapted to the recognition of places, not things. In this volume, Adrian Horridge also sets out the curious and contentious history of how bee vision came to be understood, with an account of a century of neglect of old experimental results, errors of interpretation, sharp disagreements, and failures of the scientific method. The design of the experiments and the methods of making inferences from observations are also critically examined, with the conclusion that scientists are often hesitant, imperfect and misleading, ignore the work of others, and fail to consider alternative explanations. The erratic path to understanding makes interesting reading for anyone with an analytical mind who thinks about the methods of science or the engineering of seeing machines

How bees distinguish colors

Behind each facet of the compound eye, bees have photoreceptors for ultraviolet, green, and blue wavelengths that are excited by sunlight reflected from the surrounding panorama. In experiments that excluded ultraviolet, bees learned to distinguish between black, gray, white, and various colors. To distinguish two targets of differing color, bees detected, learned, and later recognized the strongest preferred inputs, irrespective of which target displayed them. First preference was the position and measure of blue reflected from white or colored areas. They also learned the positions and a measure of the green receptor modulation at vertical edges that displayed the strongest green contrast. Modulation is the receptor response to contrast and was summed over the length of a contrasting vertical edge. This also gave them a measure of angular width between outer vertical edges. Third preference was position and a measure of blue modulation. When they returned for more reward, bees recognized the familiar coincidence of these inputs at that place. They cared nothing for colors, layout of patterns, or direction of contrast, even at black/white edges. The mechanism is a new kind of color vision in which a large-field tonic blue input must coincide in time with small-field phasic modulations caused by scanning vertical edges displaying green or blue contrast. This is the kind of system to expect in medium-lowly vision, as found in insects; the next steps are fresh looks at old observations and quantitative models

How bees discriminate a pattern of two colours from its mirror image

A century ago, in his study of colour vision in the honeybee (Apis mellifera), Karl von Frisch showed that bees distinguish between a disc that is half yellow, half blue, and a mirror image of the same. Although his inference of colour vision in this example has been accepted, some discrepancies have prompted a new investigation of the detection of polarity in coloured patterns. In new experiments, bees restricted to their blue and green receptors by exclusion of ultraviolet could learn patterns of this type if they displayed a difference in green contrast between the two colours. Patterns with no green contrast required an additional vertical black line as a landmark. Tests of the trained bees revealed that they had learned two inputs; a measure and the retinotopic position of blue with large field tonic detectors, and the measure and position of a vertical edge or line with small-field phasic green detectors. The angle between these two was measured. This simple combination was detected wherever it occurred in many patterns, fitting the definition of an algorithm, which is defined as a method of processing data. As long as they excited blue receptors, colours could be any colour to human eyes, even white. The blue area cue could be separated from the green receptor modulation by as much as 50°. When some blue content was not available, the bees learned two measures of the modulation of the green receptors at widely separated vertical edges, and the angle between them. There was no evidence that the bees reconstructed the lay-out of the pattern or detected a tonic input to the green receptors

Direct response of the crab Carcinus to the movement of the sun

1. The eyes of the crab follow the movement of the sun if stationary landmarks, which would arrest the eye movement, are obscured. 2. Therefore, even if the eyes do not move when the crab is in a normal environment, the sun's movement is certainly seen by the crab. 3. The eye movements in response to tilting the whole animal only partially compensate for the body tilt. Therefore an obvious contrasting object such as the sun is not absolutely stabilized on the retina in tilting. 4. This sensory ability of the crab could form the basis of a compass response with a minimum latency of 10 sec

How bees distinguish black from white

Bee eyes have photoreceptors for ultraviolet, green, and blue wavelengths that are excited by reflected white but not by black. With ultraviolet reflections excluded by the apparatus, bees can learn to distinguish between black, gray, and white, but theories of color vision are clearly of no help in explaining how they succeed. Human vision sidesteps the issue by constructing black and white in the brain. Bees have quite different and accessible mechanisms. As revealed by extensive tests of trained bees, bees learned two strong signals displayed on either target. The first input was the position and a measure of the green receptor modulation at the vertical edges of a black area, which included a measure of the angular width between the edges of black. They also learned the average position and total amount of blue reflected from white areas. These two inputs were sufficient to help decide which of two targets held the reward of sugar solution, but the bees cared nothing for the black or white as colors, or the direction of contrast at black/white edges. These findings provide a small step toward understanding, modeling, and implementing in silicon the anti-intuitive visual system of the honeybee, in feeding behavior

Commentary: What does an insect see?

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, 100-130deg., 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

Eyecup withdrawal in the crab, Carcinus, and its interaction with the optokinetic response

Summary 1. Protective withdrawal of the eyecup is caused by a burst of impulses in two axons of the optic tract, one to muscles 19a, 19b and 20a, the other to muscles 18, 20b, 21 and 22. 2. At a reflex eyecup withdrawal other concurrent activity is mechanically overridden ; the tonic activity in only one muscle is inhibited centrally. At a ‘spontaneous’ withdrawal, however, all motor activity to that eyecup is inhibited. 3. The largest muscle, 19a, inactive in other eyecup movements, is the prime mover in withdrawal, and some tonic fibres of this muscle hold the eyecup withdrawn. 4. Two muscles which move the eyecup toward the mid line on optokinetic responses are excited during a withdrawal. It is therefore possible for one muscle to contribute to movements in opposite directions. 5. Repeated reflex withdrawal of an eyecup moving towards the mid line inhibits the optokinetic response of the other eye. 6. Weak stimulation of an eyecup region by a variety of means, including withdrawal, improves the optokinetic response of that eyecup and sometimes of the other eyecup

Anatomy of the regional differences in the eye of the mantis Ciulfina

In the compound eye of Ciulfina (Mantidae) there are large regional differences in interommatidial angle as measured optically from the pseudo-pupil. Notably there is an acute zone which looks backwards as well as one looking forwards. There are correlated regional differences in the dimensions of the ommatidia. The following anatomical features which influence the optical performance have been measured in different parts of the eye The facet diameter is greater where the interommatidial angle is smaller. This could influence resolving power, but calculation shows that facet size does not exert a dominant effect on the visual fields of the receptors. The rhabdom tip diameter, which theoretically has a strong influence on the size of visual fields, is narrower in eye regions where the interommatidial angle is smaller. The cone length, from which the focal length can be estimated, is greater where the interommatidial angle is smaller. Estimation of the amount of light reaching the rhabdom suggests that different parts of the eye have similar sensitivity to a point source of light, but differ by a factor of at least 10 in sensitivity to an extended source. There is anatomical evidence that in the acute zone the sensitivity has been sacrificed for the sake of resolution. Maps of the theoretical minimum fields of the photoreceptors, plotted in their positions on the eye in angular coordinates, suggest that there are too few ommatidia for the eye as a whole to reconstruct all the visual detail that the individual receptors can resolve. The conclusion from (3) and (4), together with some behavioural evidence, suggests that the eye structure must make possible the resolution of small movements of contrasting edges and of small dark contrasting objects but there is less emphasis on the total reconstruction of fine patterns because the interommatidial angle is greater than the estimate of the acceptance angle

Efferent copy and voluntary eyecup movement in the crab, Carcinus

At the time of publication the author was affiliated with the Gatty Marine Laboratory and Department of Natural History, University of St Andrews, Fife, Scotland

How bees distinguish patterns by green and blue modulation

In the 1920s, Mathilde Hertz found that trained bees discriminated between shapes or patterns of similar size by something related to total length of contrasting contours. This input is now interpreted as modulation in green and blue receptor channels as flying bees scan in the horizontal plane. Modulation is defined as total contrast irrespective of sign multiplied by length of edge displaying that contrast, projected to vertical, therefore, combining structure and contrast in a single input. Contrast is outside the eye; modulation is a phasic response in receptor pathways inside. In recent experiments, bees trained to distinguish color detected, located, and measured three independent inputs and the angles between them. They are the tonic response of the blue receptor pathway and modulation of small-field green or (less preferred) blue receptor pathways. Green and blue channels interacted intimately at a peripheral level. This study explores in more detail how various patterns are discriminated by these cues. The direction of contrast at a boundary was not detected. Instead, bees located and measured total modulation generated by horizontal scanning of contrasts, irrespective of pattern. They also located the positions of isolated vertical edges relative to other landmarks and distinguished the angular widths between vertical edges by green or blue modulation alone. The preferred inputs were the strongest green modulation signal and angular width between outside edges, irrespective of color. In the absence of green modulation, the remaining cue was a measure and location of blue modulation at edges. In the presence of green modulation, blue modulation was inhibited. Black/white patterns were distinguished by the same inputs in blue and green receptor channels. Left-right polarity and mirror images could be discriminated by retinotopic green modulation alone. Colors in areas bounded by strong green contrast were distinguished as more or less blue than the background. The blue content could also be summed over the whole target. There were no achromatic patterns for bees and no evidence that they detected black, white, or gray levels apart from the differences in blue content or modulation at edges. Most of these cues would be sensitive to background color but some were influenced by changes in illumination. The bees usually learned only to avoid the unrewarded target. Exactly the same preferences of the same inputs were used in the detection of single targets as in discrimination between two targets