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Long-term behavioral changes related to learning and experience have been shown to be associated with structural remodeling in the brain. Leaf-cutting ants learn to avoid previously preferred plants after they have proved harmful for their symbiotic fungus, a process that involves long-term olfactory memory. We studied the dynamics of brain microarchitectural changes after long-term olfactory memory formation following avoidance learning in Acromyrmex ambiguus. After performing experiments to control for possible neuronal changes related to age and body size, we quantified synaptic complexes (microglomeruli, MG) in olfactory regions of the mushroom bodies (MB) at different times after learning. Long-term avoidance memory formation was associated with a transient change in MG densities. Two days after learning, MG density was higher than before learning. At days 4 and 15 after learning when ants still showed plant avoidance MG densities had decreased to the initial state. The structural reorganization of MG triggered by long-term avoidance memory formation clearly differed from changes promoted by pure exposure to and collection of novel plants with distinct odors. Sensory exposure by the simultaneous collection of several, instead of one, non-harmful plant species resulted in a decrease in MG densities in the olfactory lip. We hypothesize that while sensory exposure leads to MG pruning in the MB olfactory lip, the formation of long-term avoidance memory involves an initial growth of new MG followed by subsequent pruning.
Long-term behavioral changes related to learning and experience have been shown to be associated with structural remodeling in the brain. Leaf-cutting ants learn to avoid previously preferred plants after they have proved harmful for their symbiotic fungus, a process that involves long-term olfactory memory. We studied the dynamics of brain microarchitectural changes after long-term olfactory memory formation following avoidance learning in Acromyrmex ambiguus. After performing experiments to control for possible neuronal changes related to age and body size, we quantified synaptic complexes (microglomeruli, MG) in olfactory regions of the mushroom bodies (MBs) at different times after learning. Long-term avoidance memory formation was associated with a transient change in MG densities. Two days after learning, MG density was higher than before learning. At days 4 and 15 after learning—when ants still showed plant avoidance—MG densities had decreased to the initial state. The structural reorganization of MG triggered by long-term avoidance memory formation clearly differed from changes promoted by pure exposure to and collection of novel plants with distinct odors. Sensory exposure by the simultaneous collection of several, instead of one, non-harmful plant species resulted in a decrease in MG densities in the olfactory lip. We hypothesize that while sensory exposure leads to MG pruning in the MB olfactory lip, the formation of long-term avoidance memory involves an initial growth of new MG followed by subsequent pruning.
All animals learn in order to cope with challenges imposed on them by their environment. This is true also for both larval and adult fruit flies as exemplified in pavlovian conditioning. The focus of this Thesis is on various aspects of the fruit flies learning ability. My main project deals with two types of learning which we call punishment-learning and pain-relief learning. Punishment learning happens when fruit flies are exposed to an odour which is followed by electric shock. After such training, flies have learned that that odour signals pain and consequently will avoid it in the future. If the sequence of the two stimuli is reversed such that odour follows shock, flies learn the odour as a signal for relief and will later on approach it. I first report a series of experiments investigating qualitative and parametric features of relief-learning; I find that (i) relief learning does result from true associative conditioning, (ii) it requires a relatively high number of training trials, (iii) context-shock training is ineffective for subsequent shock-odour learning. A further question is whether punishment-learning and pain-relief learning share genetic determinants. In terms of genetics, I test a synapsin mutant strain, which lacks all Synapsin protein, in punishment and relief-learning. Punishment learning is significantly reduced, and relief-learning is abolished. Pan-neuronal RNAi-mediated knock-down of Synapsin results in mutant-like phenotypes, confirming the attribution of the phenotype to lack of Synapsin. Also, a rescue of Synapsin in the mushroom body of syn97 mutants restores both punishment- and relief-learning fully, suggesting the sufficiency of Synapsin in the mushroom body for both these kinds of learning. I also elucidate the relationship between perception and physiology in adult fruit flies. I use odour-shock conditioning experiments to identify degrees of similarity between odours; I find that those similarity measures are consistent across generalization and discrimination tasks of diverse difficulty. Then, as collaborator of T. Völler and A. Fiala, I investigate how such behavioural similarity/dissimilarity is reflected at the physiological level. I combine the behaviour data with calcium imaging data obtained by measuring the activity patterns of those odours in either the sensory neurons or the projection neurons at the antennal lobe. Our interpretation of the results is that the odours perceptual similarity is organized by antennal lobe interneurons. In another project I investigate the effect of gustatory stimuli on reflexive behaviour as well as their role as reinforcer in larval learning. Drosophila larvae greatly alter their behaviour in presence of sodium chloride. Increasing salt concentration modulates choice behaviour from weakly appetitive to strongly aversive. A similar concentration-behaviour function is also found for feeding: larval feeding is slightly enhanced in presence of low salt concentrations, and strongly decreased in the presence of high salt concentrations. Regarding learning, relatively weak salt concentrations function as appetitive reinforcer, whereas high salt concentrations function as aversive reinforcer. Interestingly, the behaviour-concentration curves are shifted towards higher concentrations from reflexive behaviour (choice behaviour, feeding) as compared to associative learning. This dissociation may reflect a different sensitivity in the respective sensory-motor circuitry.
It has been known for a long time that Drosophila can learn to discriminate not only between different odorants but also between different concentrations of the same odor. Olfactory associative learning has been described as a pairing between odorant and electric shock and since then, most of the experiments conducted in this respect have largely neglected the dual properties of odors: quality and intensity. For odorant-coupled short-term memory, a biochemical model has been proposed that mainly relies on the known cAMP signaling pathway. Mushroom bodies (MB) have been shown to be necessary and sufficient for this type of memory, and the MB-model of odor learning and short-term memory was established. Yet, theoretically, based on the MB-model, flies should not be able to learn concentrations if trained to the lower of the two concentrations in the test. In this thesis, I investigate the role of concentration-dependent learning, establishment of a concentration-dependent memory and their correlation to the standard two-odor learning as described by the MB-model. In order to highlight the difference between learning of quality and learning of intensity of the same odor I have tried to characterize the nature of the stimulus that is actually learned by the flies, leading to the conclusion that during the training flies learn all possible cues that are presented at the time. The type of the following test seems to govern the usage of the information available. This revealed a distinction between what flies learned and what is actually measured. Furthermore, I have shown that learning of concentration is associative and that it is symmetrical between high and low concentrations. I have also shown how the subjective quality perception of an odor changes with changing intensity, suggesting that one odor can have more than one scent. There is no proof that flies perceive a range of concentrations of one odorant as one (odor) quality. Flies display a certain level of concentration invariance that is limited and related to the particular concentration. Learning of concentration is relevant only to a limited range of concentrations within the boundaries of concentration invariance. Moreover, under certain conditions, two chemically distinct odorants could smell sufficiently similarly such, that they can be generalized between each other like if they would be of the same quality. Therefore, the abilities of the fly to identify the difference in quality or in intensity of the stimuli need to be distinguished. The way how the stimulus is analyzed and processed speaks in favor of a concept postulating the existence of two separated memories. To follow this concept, I have proposed a new form of memory called odor intensity memory (OIM), characterized it and compared it to other olfactory memories. OIM is independent of some members of the known cAMP signaling pathway and very likely forms the rutabaga-independent component of the standard two-odor memory. The rutabaga-dependent odor memory requires qualitatively different olfactory stimuli. OIM is revealed within the limits of concentration invariance where the memory test gives only sub-optimal performance for the concentration differences but discrimination of odor quality is not possible at all. Based on the available experimental tools, OIM seems to require the mushroom bodies the same as odor-quality memory but its properties are different. Flies can memorize the quality of several odorants at a given time but a newly formed memory of one odor interferes with the OIM stored before. In addition, the OIM lasts only 1 to 3 hours - much shorter than the odor-quality memory.
In their natural environment animals face complex and highly dynamic olfactory input. This requires fast and reliable processing of olfactory information, in vertebrates as well as invertebrates. Parallel processing has been shown to improve processing speed and power in other sensory systems like auditory or visual. In the olfactory system less is known about olfactory coding in general and parallel processing in particular. With its elaborated olfactory system and due to their specialized neuroanatomy, honeybees are well-suited model organism to study parallel olfactory processing. The honeybee possesses a unique neuronal architecture - a dual olfactory pathway. Two mirror-imaged output projection neuron (PN) pathways connect the first olfactory processing stage, the antennal lobe (analog to the vertebrates olfactory bulb, OB), with the second, the mushroom body (MB) known to be involved in orientation and learning and memory, and the lateral horn (LH). The medial antennal lobe-protocerebral tract (m-APT) first innervates the MB and thereafter the LH, while the other, the lateral-APT (l-APT) projects in opposite direction. The neuroanatomy and evolution of these pathways has been analyzed, yet little is known about its physiology. To analyze the function of the dual olfactory pathway a new established recording method was designed and is described in the first chapter of this thesis (multi-unit-recordings). This is now the first time where odor response from several PNs of both tracts is recorded simultaneously and with high temporal precision. In the second chapter the PN odor responses are analyzed. The major findings are: both tracts responded to all tested odors but with differing characteristics. Since recent studies describe the input to the two tracts being rather similar, the results now indicate differential odor processing along the tracts, therefore this is a good indicator for parallel processing. PNs of the m-APT process odors in a sparse manner with delayed response latencies, but with high odor-specificity. PNs of the l-APT in contrast respond to several odor stimuli and respond in general faster. In some PN originating from both tracts, characteristics of odor-identity coding via response latencies were found. Analyzing the over-all dynamic range of the PNs both l- and m-APT PNs were tested over a large odor concentration range (10-6 to 10-2) (3. chapter). The PNs responded with linear and non-linear correlation of the response strength to the odor concentration. In most cases the l-APT is comparatively more sensitive to low odor concentrations. Response latency decreases with increasing odor concentration in both tracts. Alternative coding principles and elaboration on the hypothesis whether the dual olfactory pathway may contribute coincidental innervation to the next higher-order neurons, the Kenyon cells (KC), is subject of the 4. chapter. Cross-correlations and synchronous responses of both tracts show that in principle odors may be coded via temporal coding. Results suggest that odor processing is enhanced if both tracts contribute to olfactory coding together. In another project the distribution of the inhibitory neurotransmitter GABA (gamma-aminobutyric acid) was measured in the bee’s MB during adult maturation (5. chapter). GABAergic inhibition is of high importance in odor coding. An almost threefold decrease in the total amount of GABAergic innervation was found during adult maturation in the l- and m-APT target region, in particular at the change in division of labor during the transition from a young nurse bee to an older forager bee. The results fit well into the current understanding of brain development in the honeybee and other social insects during adult maturation, which was described as presynaptic pruning and KC dendritic outgrowth. Combining anatomical and functional properties of the bee’s dual olfactory pathway suggests that both rate and temporal coding are implemented along two parallel streams. Comparison with recent work on analog output pathways of the vertebrate’s OB indicates that parallel processing of olfactory information may be a common principle across distant taxa.
The behavior of honeybees and bumblebees relies on a constant sensory integration of abiotic or biotic stimuli. As eusocial insects, a sophisticated intraspecific communication as well as the processing of multisensory cues during foraging is of utter importance. To tackle the arising challenges, both honeybees and bumblebees have evolved a sophisticated olfactory and visual processing system.
In both organisms, olfactory reception starts at the antennae, where olfactory sensilla cover the antennal surface in a sex-specific manner. These sensilla house olfactory receptor neurons (ORN) that express olfactory receptors. ORNs send their axons via four tracts to the antennal lobe (AL), the prime olfactory processing center in the bee brain. Here, ORNs specifically innervate spheroidal structures, so-called glomeruli, in which they form synapses with local interneurons and projection neurons (PN). PNs subsequently project the olfactory information via two distinct tracts, the medial and the lateral antennal-lobe tract, to the mushroom body (MB), the main center of sensory integration and memory formation. In the honeybee calyx, the sensory input region of the MB, PNs synapse on Kenyon cells (KC), the principal neuron type of the MB. Olfactory PNs mainly innervate the lip and basal ring layer of the calyx. In addition, the basal ring receives input from visual PNs, making it the first site of integration of visual and olfactory information. Visual PNs, carrying sensory information from the optic lobes, send their terminals not only to the to the basal ring compartment but also to the collar of the calyx. Receiving olfactory or visual input, KCs send their axons along the MB peduncle and terminate in the main output regions of the MB, the medial and the vertical lobe (VL) in a layer-specific manner. In the MB lobes, KCs synapse onto mushroom body output neurons (MBON). In so far barely understood processes, multimodal information is integrated by the MBONs and then relayed further into the protocerebral lobes, the contralateral brain hemisphere, or the central brain among others.
This dissertation comprises a dichotomous structure that (i) aims to gain more insight into the olfactory processing in bumblebees and (ii) sets out to broaden our understanding of visual processing in honeybee MBONs.
The first manuscript examines the olfactory processing of Bombus terrestris and specifically investigates sex-specific differences. We used behavioral (absolute conditioning) and electrophysiological approaches to elaborate the processing of ecologically relevant odors (components of plant odors and pheromones) at three distinct levels, in the periphery, in the AL and during olfactory conditioning. We found both sexes to form robust memories after absolute conditioning and to generalize towards the carbon chain length of the presented odors. On the contrary, electroantennographic (EAG) activity showed distinct stimulus and sex-specific activity, e.g. reduced activity towards citronellol in drones. Interestingly, extracellular multi-unit recordings in the AL confirmed stimulus and sex-specific differences in olfactory processing, but did not reflect the differences previously found in the EAG. Here, farnesol and 2,3-dihydrofarnesol, components of sex-specific pheromones, show a distinct representation, especially in workers, corroborating the results of a previous study. This explicitly different representation suggests that the peripheral stimulus representation is an imperfect indication for neuronal representation in high-order neuropils and ecological importance of a specific odor.
The second manuscript investigates MBONs in honeybees to gain more insights into visual processing in the VL. Honeybee MBONs can be categorized into visually responsive, olfactory responsive and multimodal. To clarify which visual features are represented at this high-order integration center, we used extracellular multi-unit recordings in combination with visual and olfactory stimulation. We show for the first time that information about brightness and wavelength is preserved in the VL. Furthermore, we defined three specific classes of visual MBONs that distinctly encode the intensity, identity or simply the onset of a stimulus. The identity-subgroup exhibits a specific tuning towards UV light. These results support the view of the MB as the center of multimodal integration that categorizes sensory input and subsequently channels this information into specific MBON populations.
Finally, I discuss differences between the peripheral representations of stimuli and their distinct processing in high-order neuropils. The unique activity of farnesol in manuscript 1 or the representation of UV light in manuscript 2 suggest that the peripheral representation of a stimulus is insufficient as a sole indicator for its neural activity in subsequent neuropils or its putative behavioral importance. In addition, I discuss the influence of hard-wired concepts or plasticity induced changes in the sensory pathways on the processing of such key stimuli in the peripheral reception as well as in high-order centers like the AL or the MB. The MB as the center of multisensory integration has been broadly examined for its olfactory processing capabilities and receives increasing interest about its visual coding properties. To further unravel its role of sensory integration and to include neglected modalities, future studies need to combine additional approaches and gain more insights on the multimodal aspects in both the input and output region.