Randolf Menzel

The spectral input systems of hymenopteran insects and their receptor-based colour vision.

SummarySpectral sensitivity functions S(λ) of single photoreceptor cells in 43 different hymenopteran species were measured intracellularly with the fast spectral scan method. The distribution of maximal sensitivity values (λmax) shows 3 major peaks at 340 nm, 430 nm and 535 nm and a small peak at 600 nm. Predictions about the colour vision systems of the different hymenopteran species are derived from the spectral sensitivities by application of a receptor model of colour vision and a model of two colour opponent channels. Most of the species have a trichromatic colour vision system. Although the S(λ) functions are quite similar, the predicted colour discriminability curves differ in their relative height of best discriminability in the UV-blue or bluegreen area of the spectrum, indicating that relatively small differences in the S(λ) functions may have considerable effects on colour discriminability. Four of the hymenopteran insects tested contain an additional R-receptor with maximal sensitivity around 600 nm. The R-receptor of the solitary bee Callonychium petuniae is based on a pigment (P596) with a long λmax, whereas in the sawfly Tenthredo campestris the G-receptor appears to act as filter to a pigment (P570), shifting its λmax value to a longer wavelength and narrowing its bandwidth. Evolutionary and life history constraints (e.g. phylogenetic relatedness, social or solitary life, general or specialized feeding behaviour) appear to have no effect on the S(λ) functions. The only effect is found in UV receptors, for which λmax values at longer wavelengths are found in bees flying predominantly within the forest.

Memory dynamics in the honeybee

Abstract Reward learning in honeybees initiates a sequence of events which leads to long-lasting memory passing through multiple phases of transient memories. The study of memory dynamics is performed at the behavioral (both natural foraging behavior and appetitive conditioning), neural circuit and molecular levels. The results of these combined efforts lead to a model which assumes five kinds of sequential memories, each characterized by a set of behavioral and mechanistic properties. It is argued that these properties, although reflecting general characteristics of step-wise memory formation, are adapted to the species-specific adaptations in natural behavior, here to foraging at scattered and unreliable food sources.

Evaluation of Atlas Selection Strategies for Atlas-Based Image Segmentation with Application to Confocal Microscopy Images of Bee Brains

This paper evaluates strategies for atlas selection in atlas-based segmentation of three-dimensional biomedical images. Segmentation by intensity-based nonrigid registration to atlas images is applied to confocal microscopy images acquired from the brains of 20 bees. This paper evaluates and compares four different approaches for atlas image selection: registration to an individual atlas image (IND), registration to an average-shape atlas image (AVG), registration to the most similar image from a database of individual atlas images (SIM), and registration to all images from a database of individual atlas images with subsequent multi-classifier decision fusion (MUL). The MUL strategy is a novel application of multi-classifier techniques, which are common in pattern recognition, to atlas-based segmentation. For each atlas selection strategy, the segmentation performance of the algorithm was quantified by the similarity index (SI) between the automatic segmentation result and a manually generated gold standard. The best segmentation accuracy was achieved using the MUL paradigm, which resulted in a mean similarity index value between manual and automatic segmentation of 0.86 (AVG, 0.84; SIM, 0.82; IND, 0.81). The superiority of the MUL strategy over the other three methods is statistically significant (two-sided paired t test, P < 0.001). Both the MUL and AVG strategies performed better than the best possible SIM and IND strategies with optimal a posteriori atlas selection (mean similarity index for optimal SIM, 0.83; for optimal IND, 0.81). Our findings show that atlas selection is an important issue in atlas-based segmentation and that, in particular, multi-classifier techniques can substantially increase the segmentation accuracy.

The concepts of 'sameness' and 'difference' in an insect

Insects process and learn information flexibly to adapt to their environment. The honeybee Apis mellifera constitutes a traditional model for studying learning and memory at behavioural, cellular and molecular levels. Earlier studies focused on elementary associative and non-associative forms of learning determined by either olfactory conditioning of the proboscis extension reflex or the learning of visual stimuli in an operant context. However, research has indicated that bees are capable of cognitive performances that were thought to occur only in some vertebrate species. For example, honeybees can interpolate visual information, exhibit associative recall, categorize visual information and learn contextual information. Here we show that honeybees can form ‘sameness’ and ‘difference’ concepts. They learn to solve ‘delayed matching-to-sample’ tasks, in which they are required to respond to a matching stimulus, and ‘delayed non-matching-to-sample’ tasks, in which they are required to respond to a different stimulus; they can also transfer the learned rules to new stimuli of the same or a different sensory modality. Thus, not only can bees learn specific objects and their physical parameters, but they can also master abstract inter-relationships, such as sameness and difference.

Localization of short‐term memory in the brain of the bee, Apis mellifera

ABSTRACT. Fixed honey‐bees were conditioned to a scent in a one‐trial learning paradigm. In contrast to free‐flying colour‐conditioned bees, fixed scent‐conditioned bees do not show a biphasic time dependence of the conditioned response. Small metal probes were used to cool localized areas of the antennal lobes, alpha‐lobes, and calyces of the mushroom bodies of the brain at various times after conditioning. Localized cooling impaired the formation of memory in all three structures. The susceptibility to impairment after conditioning lasted approximately 3 min in the antennal lobes, 7 min in the alpha‐lobes, and 10 min in the calyx area. It was possible to determine the influence of the contralateral hemisphere (relative to the learning antenna) by conditioning bees with only one antenna. No contralateral impairment was found in the antennal lobes; there were minor effects in the alphalobes; contralateral cooling led to reductions of the conditioned response only in the calyx area. The temperature dependence of memory impairment was different for the antennal lobes and the mushroom bodies (alpha‐lobes and calyces). The latter were most sensitive to cooling at 5°C. No correlation between cooling duration and impairment of memory was found in the antennal lobes, but there was a linear relation between impairment and cooling duration in the alpha‐lobes. Brief cooling (5 or 10 s) resulted in significant impairment of memory formation only in the calyx area. A series of control experiments proved that the impairment of memory is due to a reversible block of neural activity. It was possible to show that the impairment is specific for the three neural structures analysed, by cooling the lobula of the optic system at various times after conditioning. Lesions of the brain or application of KCl also resulted in time‐dependent reductions of the conditioned response. Cooling the entire animal at various times after conditioning led to similar memory impairment to that resulting from localized cooling of the alphalobes.

Cognitive architecture of a mini-brain: the honeybee

Honeybees have small brains, but their behavioural repertoire is impressive. In this article we focus on the extent to which adaptive behaviour in honeybees exceeds elementary forms of learning. We use the concept of modularity of cognitive functions to characterize levels of complexity in the honeybee brain. We show that behavioural complexity in the honeybee cannot be explained by independent functions of vertically arranged, domain-specific processing modules, but requires horizontal integration in a central state, and we identify neural mechanisms that may underlie domain-specific processing and central integration. The honeybee may serve as a useful model for the study of intermediate levels of complexity in cognitive functions and the search for their neural substrates.

Ultraviolet as a Component of Flower Reflections, and the Colour Perception of Hymenoptera

Based on the measurements of 1063 flower reflection spectra, we show that flower colours fall into distinct clusters in the colour space of a bee. It is demonstrated that this clustering is caused by a limited variability in the floral spectral reflectance curves. There are as few as 10 distinct types of such curves, five of which constitute 85% of all measurements. UV reflections are less frequent and always lower in intensity than reflections in other parts of the spectrum. A further cluster of colour loci is formed in the centre of the colour space. It contains the colour loci of green leaves, several other background materials and only very few flowers. We propose a system to classify the reflection functions of flowers, and a set of colour names for bee colours.

Associative learning modifies neural representations of odors in the insect brain

Recording brain activity in vivo during learning is fundamental to understanding how memories are formed. We used functional calcium imaging to track odor representations in the primary chemosensory center of the honeybee, the antennal lobe, while training animals to discriminate a rewarded odor from an unrewarded one. Our results show that associative learning transforms odor representations and decorrelates activity patterns for the rewarded versus the unrewarded odor, making them less similar. Additionally, activity for the rewarded but not for the unrewarded odor is increased. These results indicate that neural representations of the environment may be modified through associative learning.

The glomerular code for odor representation is species specific in the honeybee Apis mellifera

Odors are coded by glomerular activity patterns in the insect antennal lobe (AL) and in the mammalian olfactory bulb. We measured glomerular responses to 30 different odors in the AL of honeybees using calcium-sensitive dyes. By subsequently staining glomeruli and identifying individual glomerular outlines, we were able to compare the patterns between animals. Regardless of whether the odors were mixtures or pure substances, environmental odors or pheromones, their representations were highly conserved among individuals. Therefore, it may be possible to create a functional atlas of the AL in which particular molecular receptive ranges are attributed to each glomerulus.

Detection of coloured stimuli by honeybees: minimum visual angles and receptor specific contrasts

Honeybees Apis mellifera were trained to distinguish between the presence and the absence of a rewarded coloured spot, presented on a vertical, achromatic plane in a Y-maze. They were subsequently tested with different subtended visual angles of that spot, generated by different disk diameters and different distances from the decision point in the device. Bees were trained easily to detect bee-chromatic colours, but not an achromatic one. Chromatic contrast was not the only parameter allowing learning and, therefore, detection: αmin, the subtended visual angle at which the bees detect a given stimulus with a probability P0 = 0.6, was 5° for stimuli presenting both chromatic contrast and contrast for the green photoreceptors [i.e. excitation difference in the green photoreceptors, between target and background (green contrast)], and 15° for stimuli presenting chromatic but no green contrast. Our results suggest that green contrast can be utilized for target detection if target recognition has been established by means of the colour vision system. The green-contrast signal would be used as a far-distance signal for flower detection. This signal would always be detected before chromatic contrast during an approach flight and would be learned in compound with chromatic contrast, in a facilitation-like process.