Visual attention is commonly studied by using visuo-spatial cues indicating probable locations of a target and assessing the effect of the validity of the cue on perceptual performance and its neural correlates. Here, we adapt a cueing task to measure spatial cueing effects on the decisions of honeybees and compare their behavior to that of humans and monkeys in a similarly structured two-alternative forced-choice perceptual task. Unlike the typical cueing paradigm in which the stimulus strength remains unchanged within a block of trials, for the monkey and human studies we randomized the contrast of the signal to simulate more real world conditions in which the organism is uncertain about the strength of the signal. A Bayesian ideal observer that weights sensory evidence from cued and uncued locations based on the cue validity to maximize overall performance is used as a benchmark of comparison against the three animals and other suboptimal models: probability matching, ignore the cue, always follow the cue, and an additive bias/single decision threshold model. We find that the cueing effect is pervasive across all three species but is smaller in size than that shown by the Bayesian ideal observer. Humans show a larger cueing effect than monkeys and bees show the smallest effect. The cueing effect and overall performance of the honeybees allows rejection of the models in which the bees are ignoring the cue, following the cue and disregarding stimuli to be discriminated, or adopting a probability matching strategy. Stimulus strength uncertainty also reduces the theoretically predicted variation in cueing effect with stimulus strength of an optimal Bayesian observer and diminishes the size of the cueing effect when stimulus strength is low. A more biologically plausible model that includes an additive bias to the sensory response from the cued location, although not mathematically equivalent to the optimal observer for the case stimulus strength uncertainty, can approximate the benefits of the more computationally complex optimal Bayesian model. We discuss the implications of our findings on the field’s common conceptualization of covert visual attention in the cueing task and what aspects, if any, might be unique to humans.
Honeybees, like other insects, accumulate electric charge in flight, and when their body parts are moved or rubbed together. We report that bees emit constant and modulated electric fields when flying, landing, walking and during the waggle dance. The electric fields emitted by dancing bees consist of low- and high-frequency components. Both components induce passive antennal movements in stationary bees according to Coulomb's law. Bees learn both the constant and the modulated electric field components in the context of appetitive proboscis extension response conditioning. Using this paradigm, we identify mechanoreceptors in both joints of the antennae as sensors. Other mechanoreceptors on the bee body are potentially involved but are less sensitive. Using laser vibrometry, we show that the electrically charged flagellum is moved by constant and modulated electric fields and more strongly so if sound and electric fields interact. Recordings from axons of the Johnston organ document its sensitivity to electric field stimuli. Our analyses identify electric fields emanating from the surface charge of bees as stimuli for mechanoreceptors, and as biologically relevant stimuli, which may play a role in social communication.
electric surface charge; mechanoreceptors as sensors for electric fields; Johnston organ; learning of electric field stimuli
Three neonicotinoids, imidacloprid, clothianidin and thiacloprid, agonists of the nicotinic acetylcholine receptor in the central brain of insects, were applied at non-lethal doses in order to test their effects on honeybee navigation. A catch-and-release experimental design was applied in which feeder trained bees were caught when arriving at the feeder, treated with one of the neonicotinoids, and released 1.5 hours later at a remote site. The flight paths of individual bees were tracked with harmonic radar. The initial flight phase controlled by the recently acquired navigation memory (vector memory) was less compromised than the second phase that leads the animal back to the hive (homing flight). The rate of successful return was significantly lower in treated bees, the probability of a correct turn at a salient landscape structure was reduced, and less directed flights during homing flights were performed. Since the homing phase in catch-and-release experiments documents the ability of a foraging honeybee to activate a remote memory acquired during its exploratory orientation flights, we conclude that non-lethal doses of the three neonicotinoids tested either block the retrieval of exploratory navigation memory or alter this form of navigation memory. These findings are discussed in the context of the application of neonicotinoids in plant protection.
In mammals, memory formation and stabilization requires polymerization of actin. Here, we show that, in the honeybee, inhibition of actin polymerization within the brain centres involved in memory formation, the mushroom bodies (MBs), enhances associative olfactory memory. Local application of inhibitors of actin polymerization (Cytochalasin D or Latrunculin A) to the MBs 1 h before induction of long-term memory increased memory retention 2 and 24 h after the onset of training. Post-training application of Cytochalasin D also enhanced retention, indicating that memory consolidation is facilitated by actin depolymerization. We conclude that certain aspects of memory mechanisms could have been established independently in mammals and insects.
memory; olfactory conditioning; actin; honeybee
Most neurons in peripheral sensory pathways initially respond vigorously when a preferred stimulus is presented, but adapt as stimulation continues. It is unclear how this phenomenon affects stimulus coding in the later stages of sensory processing. Here, we show that a temporally sparse and reliable stimulus representation develops naturally in sequential stages of a sensory network with adapting neurons. As a modeling framework we employ a mean-field approach together with an adaptive population density treatment, accompanied by numerical simulations of spiking neural networks. We find that cellular adaptation plays a critical role in the dynamic reduction of the trial-by-trial variability of cortical spike responses by transiently suppressing self-generated fast fluctuations in the cortical balanced network. This provides an explanation for a widespread cortical phenomenon by a simple mechanism. We further show that in the insect olfactory system cellular adaptation is sufficient to explain the emergence of the temporally sparse and reliable stimulus representation in the mushroom body. Our results reveal a generic, biophysically plausible mechanism that can explain the emergence of a temporally sparse and reliable stimulus representation within a sequential processing architecture.
Many lines of evidence suggest that few spikes carry the relevant stimulus information at later stages of sensory processing. Yet mechanisms for the emergence of a robust and temporally sparse sensory representation remain elusive. Here, we introduce an idea in which a temporal sparse and reliable stimulus representation develops naturally in spiking networks. It combines principles of signal propagation with the commonly observed mechanism of neuronal firing rate adaptation. Using a stringent numerical and mathematical approach, we show how a dense rate code at the periphery translates into a temporal sparse representation in the cortical network. At the same time, it dynamically suppresses trial-by-trial variability, matching experimental observations in sensory cortices. Computational modelling of the insects olfactory pathway suggests that the same principle underlies the prominent example of temporal sparse coding in the mushroom body. Our results reveal a computational principle that relates neuronal firing rate adaptation to temporal sparse coding and variability suppression in nervous systems.
Flumethrin has been widely used as an acaricide for the control of Varroa mites in commercial honeybee keeping throughout the world for many years. Here we test the mortality of the Asian honeybee Apis cerana cerana after treatment with flumethrin. We also ask (1) how bees react to the odor of flumethrin, (2) whether its odor induces an innate avoidance response, (3) whether its taste transmits an aversive reinforcing component in olfactory learning, and (4) whether its odor or taste can be associated with reward in classical conditioning. Our results show that flumethrin has a negative effect on Apis ceranàs lifespan, induces an innate avoidance response, acts as a punishing reinforcer in olfactory learning, and interferes with the association of an appetitive conditioned stimulus. Furthermore flumethrin uptake within the colony reduces olfactory learning over an extended period of time.
The honeybee Apis mellifera has a remarkable ability to detect and locate food sources during foraging, and to associate odor cues with food rewards. In the honeybee’s olfactory system, sensory input is first processed in the antennal lobe (AL) network. Uniglomerular projection neurons (PNs) convey the sensory code from the AL to higher brain regions via two parallel but anatomically distinct pathways, the lateral and the medial antenno-cerebral tract (l- and m-ACT). Neurons innervating either tract show characteristic differences in odor selectivity, concentration dependence, and representation of mixtures. It is still unknown how this differential stimulus representation is achieved within the AL network. In this contribution, we use a computational network model to demonstrate that the experimentally observed features of odor coding in PNs can be reproduced by varying lateral inhibition and gain control in an otherwise unchanged AL network. We show that odor coding in the l-ACT supports detection and accurate identification of weak odor traces at the expense of concentration sensitivity, while odor coding in the m-ACT provides the basis for the computation and following of concentration gradients but provides weaker discrimination power. Both coding strategies are mutually exclusive, which creates a tradeoff between detection accuracy and sensitivity. The development of two parallel systems may thus reflect an evolutionary solution to this problem that enables honeybees to achieve both tasks during bee foraging in their natural environment, and which could inspire the development of artificial chemosensory devices for odor-guided navigation in robots.
dual pathway odor coding; mixture coding; antennal lobe; computational model; honeybee foraging
confocal microscopy; neuron reconstruction; image registration; brain atlas; statistical shape model; neural networks; ontology; Apis mellifera
In reversal learning animals are first trained with a differential learning protocol, where they learn to respond to a reinforced odor (CS+) and not to respond to a non-reinforced odor (CS−). Once they respond correctly to this rule, the contingencies of the conditioned stimuli are reversed, and animals learn to adjust their response to the new rule. This study investigated the effect of a protein synthesis inhibitor (emetine) on the memory formed after reversal learning in the honeybee Apis mellifera. Two groups of bees were studied: summer bees and winter bees, each yielded different results. Blocking protein synthesis in summer bees inhibits consolidation of the excitatory learning following reversal learning whereas it blocked the consolidation of the inhibitory learning in winter bees. These findings suggest that excitatory and inhibitory learning may involve different molecular processes in bees, which are seasonally dependent.
olfactory learning; honey bee; season; protein synthesis inhibitor; reversal learning; memory
Gamma-aminobutyric acid immunoreactive feedback neurons of the protocerebral tract are a major component of the honeybee mushroom body. They have been shown to be subject to learning-related plasticity and provide putative inhibitory input to Kenyon cells and the pedunculus extrinsic neuron, PE1. We hypothesize, that learning-related modulation in these neurons is mediated by varying the amount of inhibition provided by feedback neurons. We performed Ca2+ imaging recordings of populations of neurons of the protocerebral-calycal tract (PCT) while the bees were conditioned in an appetitive olfactory paradigm and their behavioral responses were quantified using electromyographic recordings from M17, the muscle which controls the proboscis extension response. The results corroborate findings from electrophysiological studies showing that PCT neurons respond to sucrose and odor stimuli. The odor responses are concentration dependent. Odor and sucrose responses are modulated by repeated stimulus presentations. Furthermore, animals that learned to associate an odor with sucrose reward responded to the repeated presentations of the rewarded odor with less depression than they did to an unrewarded and a control odor.
mushroom body; GABA; plasticity; calcium imaging; feedback neurons
Learning of stimulus sequences is considered as a characteristic feature of episodic memory since it contains not only a particular item but also the experience of preceding and following events. In sensorimotor tasks resembling navigational performance, the serial order of objects is intimately connected with spatial order. Mammals and birds develop episodic(-like) memory in serial spatio-temporal tasks, and the honeybee learns spatio-temporal order when navigating between the nest and a food source. Here I examine the structure of the bees’ memory for a combined spatio-temporal task. I ask whether discrimination and generalization are based solely on simple forms of stimulus-reward learning or whether they require sequential configurations. Animals were trained to fly either left or right in a continuous T-maze. The correct choice was signaled by the sequence of colors (blue, yellow) at four positions in the access arm. If only one of the possible 4 signals is shown (either blue or yellow), the rank order of position salience is 1, 2 and 3 (numbered from T-junction). No learning is found if the signal appears at position 4. If two signals are shown, differences at positions 1 and 2 are learned best, those at position 3 at a low level, and those at position 4 not at all. If three or more signals are shown these results are corroborated. This salience rank order again appeared in transfer tests, but additional configural phenomena emerged. Most of the results can be explained with a simple model based on the assumption that the four positions are equipped with different salience scores and that these add up independently. However, deviations from the model are interpreted by assuming stimulus configuration of sequential patterns. It is concluded that, under the conditions chosen, bees rely most strongly on memories developed during simple forms of associative reward learning, but memories of configural serial patterns contribute, too.
We use the moth Heliothis virescens as model organism for studying the neural network involved in chemosensory coding and learning. The constituent neurons are characterised by intracellular recordings combined with staining, resulting in a single neuron identified in each brain preparation. In order to spatially relate the neurons of different preparations a common brain framework was required. We here present an average shaped atlas of the moth brain. It is based on 11 female brain preparations, each stained with a fluorescent synaptic marker and scanned in confocal laser-scanning microscope. Brain neuropils of each preparation were manually reconstructed in the computer software Amira, followed by generating the atlas using the Iterative Shape Average Procedure. To demonstrate the application of the atlas we have registered two olfactory and two gustatory interneurons, as well as the axonal projections of gustatory receptor neurons into the atlas, visualising their spatial relationships. The olfactory interneurons, showing the typical morphology of inner-tract antennal lobe projection neurons, projected in the calyces of the mushroom body and laterally in the protocerebral lobe. The two gustatory interneurons, responding to sucrose and quinine respectively, projected in different areas of the brain. The wide projections of the quinine responding neuron included a lateral area adjacent to the projections of the olfactory interneurons. The sucrose responding neuron was confined to the suboesophageal ganglion with dendritic arborisations overlapping the axonal projections of the gustatory receptor neurons on the proboscis. By serving as a tool for the integration of neurons, the atlas offers visual access to the spatial relationship between the neurons in three dimensions, and thus facilitates the study of neuronal networks in the Heliothis virescens brain. The moth standard brain is accessible at http://www.ntnu.no/biolog/english/neuroscience/brain
insect; taste; olfaction; neuron; three-dimensional reconstruction
An important component in understanding central olfactory processing and coding in the insect brain relates to the characterization of the functional divisions between morphologically distinct types of projection neurons (PN). Using calcium imaging, we investigated how the identity, concentration and mixtures of odors are represented in axon terminals (boutons) of two types of PNs – lPN and mPN. In lPN boutons we found less concentration dependence, narrow tuning profiles at a high concentration, which may be optimized for fine, concentration-invariant odor discrimination. In mPN boutons, however, we found clear rising concentration dependence, broader tuning profiles at a high concentration, which may be optimized for concentration coding. In addition, we found more mixture suppression in lPNs than in mPNs, indicating lPNs better adaptation for synthetic mixture processing. These results suggest a functional division of odor processing in both PN types.
calcium imaging; olfaction; projection neuron; mushroom body; parallel processing; functional division; insect
We asked whether and how a sequence of a honeybee's experience with different reward magnitudes changes its subsequent unconditioned proboscis extension response (PER) to sucrose stimulation of the antennae, 24 hours after training, in the absence of reward, and under otherwise similar circumstances. We found that the bees that had experienced an increasing reward schedule extended their probosces earlier and during longer periods in comparison to bees that had experienced either decreasing or constant reward schedules, and that these effects at a later time depend upon the activation of memories formed on the basis of a specific property of the experienced reward, namely, that its magnitude increased over time. An anticipatory response to reward is typically thought of as being rooted in a subject's expectations of reward. Therefore our results make us wonder to what extent a long-term ‘anticipatory’ adjustment of a honeybee's PER is based upon an expectation of reward. Further experiments will aim to elucidate the neural substrates underlying reward anticipation in harnessed honeybees.
In their natural environment, many insects need to identify and evaluate behaviorally relevant odorants on a rich and dynamic olfactory background. Behavioral studies have demonstrated that bees recognize learned odors within <200 ms, indicating a rapid processing of olfactory input in the sensory pathway. We studied the role of the honeybee antennal lobe network in constructing a fast and reliable code of odor identity using in vivo intracellular recordings of individual projection neurons (PNs) and local interneurons (LNs). We found a complementary ensemble code where odor identity is encoded in the spatio-temporal pattern of response latencies as well as in the pattern of activated and inactivated PN firing. This coding scheme rapidly reaches a stable representation within 50–150 ms after stimulus onset. Testing an odor mixture versus its individual compounds revealed different representations in the two morphologically distinct types of lateral- and median PNs (l- and m-PNs). Individual m-PNs mixture responses were dominated by the most effective compound (elemental representation) whereas l-PNs showed suppressed responses to the mixture but not to its individual compounds (synthetic representation). The onset of inhibition in the membrane potential of l-PNs coincided with the responses of putative inhibitory interneurons that responded significantly faster than PNs. Taken together, our results suggest that processing within the LN network of the AL is an essential component of constructing the antennal lobe population code.
antennal lobe; Apis mellifera; latency code; local interneurons; olfaction; odor mixture; projection neurons; temporal coding
The insect mushroom bodies are higher-order brain centers and critical for odor learning. We investigated experience dependent plasticity of their intrinsic neurons, the Kenyon cells (KCs). Using calcium imaging, we recorded KC responses and investigated non-associative plasticity by applying repeated odor stimuli. Associative plasticity was examined by performing appetitive odor learning experiments. Olfactory, gustatory and tactile antennal stimuli evoked phasic calcium transients in sparse ensembles of responding KCs. Repeated stimulation with an odor led to a decrease in KCs' response strength. The pairing of an odor (conditioned stimulus, CS) with a sucrose reward (unconditioned stimulus) induced a prolongation of KC responses. After conditioning, KC responses to a rewarded odor (CS+) recovered from repetition-induced decrease, while the responses to a non-rewarded odor (CS−) decreased further. The spatio-temporal pattern of activated KCs changed for both odors when compared with the response before conditioning but the change was stronger for the CS−. These results demonstrate that KC responses are subject to non-associative plasticity during odor repetition and undergo associative plasticity after appetitive odor learning.
odor learning; mushroom body; neural plasticity; insect; honeybee; calcium imaging