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643 KiB

Open AccessArticle

Color Difference and Memory Recall in Free-Flying Honeybees: Forget the Hard Problem

by Adrian G. Dyer and Jair E. Garcia

Insects 2014, 5(3), 629-638; https://doi.org/10.3390/insects5030629 - 30 Jul 2014

Cited by 15 | Viewed by 6634

Free-flying honeybees acquire color information differently depending upon whether a target color is learnt in isolation (absolute conditioning), or in relation to a perceptually similar color (differential conditioning). Absolute conditioning allows for rapid learning, but color discrimination is coarse. Differential conditioning requires more [...] Read more.

Free-flying honeybees acquire color information differently depending upon whether a target color is learnt in isolation (absolute conditioning), or in relation to a perceptually similar color (differential conditioning). Absolute conditioning allows for rapid learning, but color discrimination is coarse. Differential conditioning requires more learning trials, but enables fine discriminations. Currently it is unknown whether differential conditioning to similar colors in honeybees forms a long-term memory, and the stability of memory in a biologically relevant scenario considering similar or saliently different color stimuli. Individual free-flying honeybees (N = 6) were trained to similar color stimuli separated by 0.06 hexagon units for 60 trials and mean accuracy was 81.7% ± 12.2% s.d. Bees retested on subsequent days showed a reduction in the number of correct choices with increasing time from the initial training, and for four of the bees this reduction was significant from chance expectation considering binomially distributed logistic regression models. In contrast, an independent group of 6 bees trained to saliently different colors (>0.14 hexagon units) did not experience any decay in memory retention with increasing time. This suggests that whilst the bees’ visual system can permit fine discriminations, flowers producing saliently different colors are more easily remembered by foraging bees over several days. Full article

(This article belongs to the Special Issue Honey Bee Behavior)

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645 KiB

Open AccessArticle

Observation of the Mating Behavior of Honey Bee (Apis mellifera L.) Queens Using Radio-Frequency Identification (RFID): Factors Influencing the Duration and Frequency of Nuptial Flights

by Ina Monika Margret Heidinger, Marina Doris Meixner, Stefan Berg and Ralph Büchler

Insects 2014, 5(3), 513-527; https://doi.org/10.3390/insects5030513 - 01 Jul 2014

Cited by 32 | Viewed by 11605

Abstract

We used radio-frequency identification (RFID) to record the duration and frequency of nuptial flights of honey bee queens (Apis mellifera carnica) at two mainland mating apiaries. We investigated the effect of a number of factors on flight duration and frequency: mating [...] Read more.

We used radio-frequency identification (RFID) to record the duration and frequency of nuptial flights of honey bee queens (Apis mellifera carnica) at two mainland mating apiaries. We investigated the effect of a number of factors on flight duration and frequency: mating apiary, number of drone colonies, queen’s age and temperature. We found significant differences between the two locations concerning the number of flights on the first three days. We also observed an effect of the ambient temperature, with queens flying less often but longer at high temperatures compared to lower temperatures. Increasing the number of drone colonies from 33 to 80 colonies had no effect on the duration or on the frequency of nuptial flights. Since our results agree well with the results of previous studies, we suggest RFID as an appropriate tool to investigate the mating behavior of honey bee queens. Full article

(This article belongs to the Special Issue Honey Bee Behavior)

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635 KiB

Open AccessArticle

Honey Bee Location- and Time-Linked Memory Use in Novel Foraging Situations: Floral Color Dependency

by Marisol Amaya-Márquez, Peggy S. M. Hill, Charles I. Abramson and Harrington Wells

Insects 2014, 5(1), 243-269; https://doi.org/10.3390/insects5010243 - 14 Feb 2014

Cited by 9 | Viewed by 7090

Abstract

Learning facilitates behavioral plasticity, leading to higher success rates when foraging. However, memory is of decreasing value with changes brought about by moving to novel resource locations or activity at different times of the day. These premises suggest a foraging model with location- [...] Read more.

Learning facilitates behavioral plasticity, leading to higher success rates when foraging. However, memory is of decreasing value with changes brought about by moving to novel resource locations or activity at different times of the day. These premises suggest a foraging model with location- and time-linked memory. Thus, each problem is novel, and selection should favor a maximum likelihood approach to achieve energy maximization results. Alternatively, information is potentially always applicable. This premise suggests a different foraging model, one where initial decisions should be based on previous learning regardless of the foraging site or time. Under this second model, no problem is considered novel, and selection should favor a Bayesian or pseudo-Bayesian approach to achieve energy maximization results. We tested these two models by offering honey bees a learning situation at one location in the morning, where nectar rewards differed between flower colors, and examined their behavior at a second location in the afternoon where rewards did not differ between flower colors. Both blue-yellow and blue-white dimorphic flower patches were used. Information learned in the morning was clearly used in the afternoon at a new foraging site. Memory was not location-time restricted in terms of use when visiting either flower color dimorphism. Full article

(This article belongs to the Special Issue Honey Bee Behavior)

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292 KiB

Open AccessArticle

The First Order Transfer Function in the Analysis of Agrochemical Data in Honey Bees (Apis Mellifera L.): Proboscis Extension Reflex (PER) Studies

by Lisa A. De Stefano, Igor I. Stepanov and Charles I. Abramson

Insects 2014, 5(1), 167-198; https://doi.org/10.3390/insects5010167 - 07 Jan 2014

Cited by 11 | Viewed by 5669

Abstract

This paper describes a mathematical model of the learning process suitable for studies of conditioning using the proboscis extension reflex (PER) in honey bees when bees are exposed to agrochemicals. Although procedural variations exist in the way laboratories use the PER paradigm, proboscis [...] Read more.

This paper describes a mathematical model of the learning process suitable for studies of conditioning using the proboscis extension reflex (PER) in honey bees when bees are exposed to agrochemicals. Although procedural variations exist in the way laboratories use the PER paradigm, proboscis conditioning is widely used to investigate the influence of pesticides and repellents on honey bee learning. Despite the availability of several mathematical models of the learning process, no attempts have been made to apply a mathematical model to the learning curve in honey bees exposed to agrochemicals. Our model is based on the standard transfer function in the form Y=B3 e^{-B2 (X-1)} +B4(1-e^{-B2 (X-1)}) where X is the trial number, Y is the proportion of correct responses, B2 is the learning rate, B3 is readiness to learn, and B4 is ability to learn. We reanalyze previously published data on the effect of several classes of agrochemicals including: (1) those that are considered harmless to bees (e.g., pymetrozine, essential oils, dicofol); (2) sublethal exposure to pesticides known to harm honey bees (e.g., coumaphos, cyfluthrin, fluvalinate, permethrin); and (3) putative repellents of honey bees (e.g., butyric acid, citronella). The model revealed additional effects not detected with standard statistical tests of significance. Full article

(This article belongs to the Special Issue Honey Bee Behavior)

898 KiB

Open AccessArticle

Effect of Olfactory Stimulus on the Flight Course of a Honeybee, Apis mellifera, in a Wind Tunnel

by Hidetoshi Ikeno, Tadaaki Akamatsu, Yuji Hasegawa and Hiroyuki Ai

Insects 2014, 5(1), 92-104; https://doi.org/10.3390/insects5010092 - 31 Dec 2013

Cited by 8 | Viewed by 7415

Abstract

It is known that the honeybee, Apis mellifera, uses olfactory stimulus as important information for orienting to food sources. Several studies on olfactory-induced orientation flight have been conducted in wind tunnels and in the field. From these studies, optical sensing is used [...] Read more.

It is known that the honeybee, Apis mellifera, uses olfactory stimulus as important information for orienting to food sources. Several studies on olfactory-induced orientation flight have been conducted in wind tunnels and in the field. From these studies, optical sensing is used as the main information with the addition of olfactory signals and the navigational course followed by these sensory information. However, it is not clear how olfactory information is reflected in the navigation of flight. In this study, we analyzed the detailed properties of flight when oriented to an odor source in a wind tunnel. We recorded flying bees with a video camera to analyze the flight area, speed, angular velocity and trajectory. After bees were trained to be attracted to a feeder, the flight trajectories with or without the olfactory stimulus located upwind of the feeder were compared. The results showed that honeybees flew back and forth in the proximity of the odor source, and the search range corresponded approximately to the odor spread area. It was also shown that the angular velocity was different inside and outside the odor spread area, and trajectories tended to be bent or curved just outside the area. Full article

(This article belongs to the Special Issue Honey Bee Behavior)

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397 KiB

Open AccessArticle

Honey Bees Inspired Optimization Method: The Bees Algorithm

by Baris Yuce, Michael S. Packianather, Ernesto Mastrocinque, Duc Truong Pham and Alfredo Lambiase

Insects 2013, 4(4), 646-662; https://doi.org/10.3390/insects4040646 - 06 Nov 2013

Cited by 135 | Viewed by 15407

Abstract

Optimization algorithms are search methods where the goal is to find an optimal solution to a problem, in order to satisfy one or more objective functions, possibly subject to a set of constraints. Studies of social animals and social insects have resulted in [...] Read more.

Optimization algorithms are search methods where the goal is to find an optimal solution to a problem, in order to satisfy one or more objective functions, possibly subject to a set of constraints. Studies of social animals and social insects have resulted in a number of computational models of swarm intelligence. Within these swarms their collective behavior is usually very complex. The collective behavior of a swarm of social organisms emerges from the behaviors of the individuals of that swarm. Researchers have developed computational optimization methods based on biology such as Genetic Algorithms, Particle Swarm Optimization, and Ant Colony. The aim of this paper is to describe an optimization algorithm called the Bees Algorithm, inspired from the natural foraging behavior of honey bees, to find the optimal solution. The algorithm performs both an exploitative neighborhood search combined with random explorative search. In this paper, after an explanation of the natural foraging behavior of honey bees, the basic Bees Algorithm and its improved versions are described and are implemented in order to optimize several benchmark functions, and the results are compared with those obtained with different optimization algorithms. The results show that the Bees Algorithm offering some advantage over other optimization methods according to the nature of the problem. Full article

(This article belongs to the Special Issue Honey Bee Behavior)

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428 KiB

Open AccessArticle

Pollen Elicits Proboscis Extension but Does not Reinforce PER Learning in Honeybees

by Elizabeth Nicholls and Natalie Hempel De Ibarra

Insects 2013, 4(4), 542-557; https://doi.org/10.3390/insects4040542 - 18 Oct 2013

Cited by 9 | Viewed by 6434

Abstract

The function of pollen as a reward for foraging bees is little understood, though there is evidence to suggest that it can reinforce associations with visual and olfactory floral cues. Foraging bees do not feed on pollen, thus one could argue that it [...] Read more.

The function of pollen as a reward for foraging bees is little understood, though there is evidence to suggest that it can reinforce associations with visual and olfactory floral cues. Foraging bees do not feed on pollen, thus one could argue that it cannot serve as an appetitive reinforcer in the same way as sucrose. However, ingestion is not a critical parameter for sucrose reinforcement, since olfactory proboscis extension (PER) learning can be conditioned through antennal stimulation only. During pollen collection, the antennae and mouthparts come into contact with pollen, thus it is possible that pollen reinforces associative learning through similar gustatory pathways as sucrose. Here pollen was presented as the unconditioned stimulus (US), either in its natural state or in a 30% pollen-water solution, and was found to elicit proboscis extension following antennal stimulation. Control groups were exposed to either sucrose or a clean sponge as the US, or an unpaired presentation of the conditioned stimulus (CS) and pollen US. Despite steady levels of responding to the US, bees did not learn to associate a neutral odour with the delivery of a pollen reward, thus whilst pollen has a proboscis extension releasing function, it does not reinforce olfactory PER learning. Full article

(This article belongs to the Special Issue Honey Bee Behavior)

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Review

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2148 KiB

Open AccessReview

The Bee as a Model to Investigate Brain and Behavioural Asymmetries

by Elisa Frasnelli, Albrecht Haase, Elisa Rigosi, Gianfranco Anfora, Lesley J. Rogers and Giorgio Vallortigara

Insects 2014, 5(1), 120-138; https://doi.org/10.3390/insects5010120 - 02 Jan 2014

Cited by 42 | Viewed by 9359

Abstract

The honeybee Apis mellifera, with a brain of only 960,000 neurons and the ability to perform sophisticated cognitive tasks, has become an excellent model in life sciences and in particular in cognitive neurosciences. It has been used in our laboratories to investigate [...] Read more.

The honeybee Apis mellifera, with a brain of only 960,000 neurons and the ability to perform sophisticated cognitive tasks, has become an excellent model in life sciences and in particular in cognitive neurosciences. It has been used in our laboratories to investigate brain and behavioural asymmetries, i.e., the different functional specializations of the right and the left sides of the brain. It is well known that bees can learn to associate an odour stimulus with a sugar reward, as demonstrated by extension of the proboscis when presented with the trained odour in the so-called Proboscis Extension Reflex (PER) paradigm. Bees recall this association better when trained using their right antenna than they do when using their left antenna. They also retrieve short-term memory of this task better when using the right antenna. On the other hand, when tested for long-term memory recall, bees respond better when using their left antenna. Here we review a series of behavioural studies investigating bees’ lateralization, integrated with electrophysiological measurements to study asymmetries of olfactory sensitivity, and discuss the possible evolutionary origins of these asymmetries. We also present morphological data obtained by scanning electron microscopy and two-photon microscopy. Finally, a behavioural study conducted in a social context is summarised, showing that honeybees control context-appropriate social interactions using their right antenna, rather than the left, thus suggesting that lateral biases in behaviour might be associated with requirements of social life. Full article

(This article belongs to the Special Issue Honey Bee Behavior)

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