Neural Correlates of Odor Learning in the Presynaptic Microglomerular Circuitry in the Honeybee Mushroom Body Calyx

Behavioral and genetic correlates of heterogeneity in learning performance in individual honeybees, Apis mellifera

Learning an olfactory discrimination task leads to heterogeneous results in honeybees with some bees performing very well and others at low rates. Here we investigated this behavioral heterogeneity and asked whether it was associated with particular gene expression patterns in the bee's brain. Bees were individually conditioned using a sequential conditioning protocol involving several phases of olfactory learning and retention tests. A cumulative score was used to differentiate the tested bees into high and low performers. The rate of CS+ odor learning was found to correlate most strongly with a cumulative performance score extracted from all learning and retention tests. Microarray analysis of gene expression in the mushroom body area of the brains of these bees identified a number of differentially expressed genes between high and low performers. These genes are associated with diverse biological functions, such as neurotransmission, memory formation, cargo trafficking and development.

Experience-dependent tuning of the olfactory system

Insects rely on their sense of smell to navigate complex environments and make decisions regarding food and reproduction. However, in natural settings, the odors that convey this information may come mixed with environmental odors that can obscure their perception. Therefore, recognizing the presence of informative odors involves generalization and discrimination processes, which can be facilitated when there is a high contrast between stimuli, or the internal representation of the odors of interest outcompetes that of concurrent ones. The first two layers of the olfactory system, which involve the detection of odorants by olfactory receptor neurons and their encoding by the first postsynaptic partners in the antennal lobe, are critical for achieving such optimal representation. In this review, we summarize evidence indicating that experience-dependent changes adjust these two levels of the olfactory system. These changes are discussed in the context of the advantages they provide for detection of informative odors.

Octopaminergic neurons function in appetitive but not aversive olfactory learning and memory in Bactrocera dorsalis

The biogenic amine octopamine (OA, invertebrate counterpart of noradrenaline) plays critical roles in the regulation of olfactory behavior. Historically, OA has been thought to mediate appetitive but not aversive learning in honeybees, fruit flies (Drosophila), and crickets. However, this viewpoint has recently been challenged because OA activity through a β-adrenergic-like receptor drives both appetitive and aversive learning. Here, we explored the roles of OA neurons in olfactory learning and memory retrieval in Bactrocera dorsalis. We trained flies to associate an orange odor with a sucrose reward or to associate methyl eugenol, a male lure, with N,N-diethyl-3-methyl benzoyl amide (DEET) punishment. We then treated flies with OA receptor antagonists before appetitive or aversive conditioning and a memory retention test. Injection of OA receptor antagonist mianserin or epinastine into the abdomen of flies led to impaired of appetitive learning and memory retention with a sucrose reward, while aversive learning and memory retention with DEET punishment remained intact. Our results suggest that the OA signaling participates in appetitive but not aversive learning and memory retrieval in B. dorsalis through OA receptors.

In Search for the Retrievable Memory Trace in an Insect Brain

The search strategy for the memory trace and its semantics is exemplified for the case of olfactory learning in the honeybee brain. The logic of associative learning is used to guide the experimental approach into the brain by identifying the anatomical and functional convergence sites of the conditioned stimulus and unconditioned stimulus pathways. Two of the several convergence sites are examined in detail, the antennal lobe as the first-order sensory coding area, and the input region of the mushroom body as a higher order integration center. The memory trace is identified as the pattern of associative changes on the level of synapses. The synapses are recruited, drop out, and change the transmission properties for both specifically associated stimulus and the non-associated stimulus. Several rules extracted from behavioral studies are found to be mirrored in the patterns of synaptic change. The strengths and the weaknesses of the honeybee as a model for the search for the memory trace are addressed in a comparison with Drosophila. The question is discussed whether the memory trace exists as a hidden pattern of change if it is not retrieved and whether an external reading of the content of the memory trace may ever be possible. Doubts are raised on the basis that the retrieval circuits are part of the memory trace. The concept of a memory trace existing beyond retrieval is defended by referring to two well-documented processes also in the honeybee, memory consolidation during sleep, and transfer of memory across brain areas.

A Mechanistic Model for Reward Prediction and Extinction Learning in the Fruit Fly

Extinction learning, the ability to update previously learned information by integrating novel contradictory information, is of high clinical relevance for therapeutic approaches to the modulation of maladaptive memories. Insect models have been instrumental in uncovering fundamental processes of memory formation and memory update. Recent experimental results in Drosophila melanogaster suggest that, after the behavioral extinction of a memory, two parallel but opposing memory traces coexist, residing at different sites within the mushroom body (MB). Here, we propose a minimalistic circuit model of the Drosophila MB that supports classical appetitive and aversive conditioning and memory extinction. The model is tailored to the existing anatomic data and involves two circuit motives of central functional importance. It employs plastic synaptic connections between Kenyon cells (KCs) and MB output neurons (MBONs) in separate and mutually inhibiting appetitive and aversive learning pathways. Recurrent modulation of plasticity through projections from MBONs to reinforcement-mediating dopaminergic neurons (DAN) implements a simple reward prediction mechanism. A distinct set of four MBONs encodes odor valence and predicts behavioral model output. Subjecting our model to learning and extinction protocols reproduced experimental results from recent behavioral and imaging studies. Simulating the experimental blocking of synaptic output of individual neurons or neuron groups in the model circuit confirmed experimental results and allowed formulation of testable predictions. In the temporal domain, our model achieves rapid learning with a step-like increase in the encoded odor value after a single pairing of the conditioned stimulus (CS) with a reward or punishment, facilitating single-trial learning.

Circuit reorganization in the Drosophila mushroom body calyx accompanies memory consolidation

The formation and consolidation of memories are complex phenomena involving synaptic plasticity, microcircuit reorganization, and the formation of multiple representations within distinct circuits. To gain insight into the structural aspects of memory consolidation, we focus on the calyx of the Drosophila mushroom body. In this essential center, essential for olfactory learning, second- and third-order neurons connect through large synaptic microglomeruli, which we dissect at the electron microscopy level. Focusing on microglomeruli that respond to a specific odor, we reveal that appetitive long-term memory results in increased numbers of precisely those functional microglomeruli responding to the conditioned odor. Hindering memory consolidation by non-coincident presentation of odor and reward, by blocking protein synthesis, or by including memory mutants suppress these structural changes, revealing their tight correlation with the process of memory consolidation. Thus, olfactory long-term memory is associated with input-specific structural modifications in a high-order center of the fly brain.

Learning-dependent plasticity in the antennal lobe improves discrimination and recognition of odors in the honeybee

Honeybees are extensively used to study olfactory learning and memory processes thanks to their ability to discriminate and remember odors and because of their advantages for optophysiological recordings of the circuits involved in memory and odor perception. There are evidences that the encoding of odors in areas of primary sensory processing is not rigid, but undergoes changes caused by olfactory experience. The biological meaning of these changes is focus of intense discussions. Along this review, we present evidences of plasticity related to different forms of learning and discuss its function in the context of olfactory challenges that honeybees have to solve. So far, results in honeybees are consistent with a model in which changes in early olfactory processing contributes to the ability of an animal to recognize the presence of relevant odors and facilitates the discrimination of odors in a way adjusted to its own experience.

Olfactory coding in honeybees

With less than a million neurons, the western honeybee Apis mellifera is capable of complex olfactory behaviors and provides an ideal model for investigating the neurophysiology of the olfactory circuit and the basis of olfactory perception and learning. Here, we review the most fundamental aspects of honeybee's olfaction: first, we discuss which odorants dominate its environment, and how bees use them to communicate and regulate colony homeostasis; then, we describe the neuroanatomy and the neurophysiology of the olfactory circuit; finally, we explore the cellular and molecular mechanisms leading to olfactory memory formation. The vastity of histological, neurophysiological, and behavioral data collected during the last century, together with new technological advancements, including genetic tools, confirm the honeybee as an attractive research model for understanding olfactory coding and learning.

Plasticity and modulation of olfactory circuits in insects

Olfactory circuits change structurally and physiologically during development and adult life. This allows insects to respond to olfactory cues in an appropriate and adaptive way according to their physiological and behavioral state, and to adapt to their specific abiotic and biotic natural environment. We highlight here findings on olfactory plasticity and modulation in various model and non-model insects with an emphasis on moths and social Hymenoptera. Different categories of plasticity occur in the olfactory systems of insects. One type relates to the reproductive or feeding state, as well as to adult age. Another type of plasticity is context-dependent and includes influences of the immediate sensory and abiotic environment, but also environmental conditions during postembryonic development, periods of adult behavioral maturation, and short- and long-term sensory experience. Finally, plasticity in olfactory circuits is linked to associative learning and memory formation. The vast majority of the available literature summarized here deals with plasticity in primary and secondary olfactory brain centers, but also peripheral modulation is treated. The described molecular, physiological, and structural neuronal changes occur under the influence of neuromodulators such as biogenic amines, neuropeptides, and hormones, but the mechanisms through which they act are only beginning to be analyzed.

A spiking neural program for sensorimotor control during foraging in flying insects

Foraging is a vital behavioral task for living organisms. Behavioral strategies and abstract mathematical models thereof have been described in detail for various species. To explore the link between underlying neural circuits and computational principles, we present how a biologically detailed neural circuit model of the insect mushroom body implements sensory processing, learning, and motor control. We focus on cast and surge strategies employed by flying insects when foraging within turbulent odor plumes. Using a spike-based plasticity rule, the model rapidly learns to associate individual olfactory sensory cues paired with food in a classical conditioning paradigm. We show that, without retraining, the system dynamically recalls memories to detect relevant cues in complex sensory scenes. Accumulation of this sensory evidence on short time scales generates cast-and-surge motor commands. Our generic systems approach predicts that population sparseness facilitates learning, while temporal sparseness is required for dynamic memory recall and precise behavioral control. Our work successfully combines biological computational principles with spike-based machine learning. It shows how knowledge transfer from static to arbitrary complex dynamic conditions can be achieved by foraging insects and may serve as inspiration for agent-based machine learning.

Circuit and Cellular Mechanisms Facilitate the Transformation from Dense to Sparse Coding in the Insect Olfactory System

Transformations between sensory representations are shaped by neural mechanisms at the cellular and the circuit level. In the insect olfactory system, the encoding of odor information undergoes a transition from a dense spatiotemporal population code in the antennal lobe to a sparse code in the mushroom body. However, the exact mechanisms shaping odor representations and their role in sensory processing are incompletely identified. Here, we investigate the transformation from dense to sparse odor representations in a spiking model of the insect olfactory system, focusing on two ubiquitous neural mechanisms: spike frequency adaptation at the cellular level and lateral inhibition at the circuit level. We find that cellular adaptation is essential for sparse representations in time (temporal sparseness), while lateral inhibition regulates sparseness in the neuronal space (population sparseness). The interplay of both mechanisms shapes spatiotemporal odor representations, which are optimized for the discrimination of odors during stimulus onset and offset. Response pattern correlation across different stimuli showed a nonmonotonic dependence on the strength of lateral inhibition with an optimum at intermediate levels, which is explained by two counteracting mechanisms. In addition, we find that odor identity is stored on a prolonged timescale in the adaptation levels but not in the spiking activity of the principal cells of the mushroom body, providing a testable hypothesis for the location of the so-called odor trace.

Opponent processes in visual memories: A model of attraction and repulsion in navigating insects' mushroom bodies

Solitary foraging insects display stunning navigational behaviours in visually complex natural environments. Current literature assumes that these insects are mostly driven by attractive visual memories, which are learnt when the insect's gaze is precisely oriented toward the goal direction, typically along its familiar route or towards its nest. That way, an insect could return home by simply moving in the direction that appears most familiar. Here we show using virtual reconstructions of natural environments that this principle suffers from fundamental drawbacks, notably, a given view of the world does not provide information about whether the agent should turn or not to reach its goal. We propose a simple model where the agent continuously compares its current view with both goal and anti-goal visual memories, which are treated as attractive and repulsive respectively. We show that this strategy effectively results in an opponent process, albeit not at the perceptual level-such as those proposed for colour vision or polarisation detection-but at the level of the environmental space. This opponent process results in a signal that strongly correlates with the angular error of the current body orientation so that a single view of the world now suffices to indicate whether the agent should turn or not. By incorporating this principle into a simple agent navigating in reconstructed natural environments, we show that it overcomes the usual shortcomings and produces a step-increase in navigation effectiveness and robustness. Our findings provide a functional explanation to recent behavioural observations in ants and why and how so-called aversive and appetitive memories must be combined. We propose a likely neural implementation based on insects' mushroom bodies' circuitry that produces behavioural and neural predictions contrasting with previous models.

Adult neurogenesis in the mushroom bodies of red flour beetles (Tribolium castaneum, HERBST) is influenced by the olfactory environment

Several studies showed adult persisting neurogenesis in insects, including the red flour beetle Tribolium castaneum, while it is absent in honeybees, carpenter ants, and vinegar flies. In our study, we focus on cell proliferation in the adult mushroom bodies of T. castaneum. We reliably labelled the progenies of the adult persisting mushroom body neuroblasts and determined the proliferation rate under several olfactory conditions within the first week after adult eclosion. We found at least two phases of Kenyon cell proliferation in the early adult beetle. Our results suggest that the generation of Kenyon cells during the first three days after adult eclosion is mainly genetically predetermined and a continuation of the developmental processes (nature), whereas from day four on proliferation seems to be mainly dependent on the odour environment (nurture). Considering that the mushroom bodies are linked to learning and memory, neurogenesis in the mushroom bodies is part of the remodelling of neuronal circuits leading to the adaption to the environment and optimization of behaviour.

Cockroaches Show Individuality in Learning and Memory During Classical and Operant Conditioning

Animal personality and individuality are intensively researched in vertebrates and both concepts are increasingly applied to behavioral science in insects. However, only few studies have looked into individuality with respect to performance in learning and memory tasks. In vertebrates, individual learning capabilities vary considerably with respect to learning speed and learning rate. Likewise, honeybees express individual learning abilities in a wide range of classical conditioning protocols. Here, we study individuality in the learning and memory performance of cockroaches, both in classical and operant conditioning tasks. We implemented a novel classical (olfactory) conditioning paradigm where the conditioned response is established in the maxilla-labia response (MLR). Operant spatial learning was investigated in a forced two-choice task using a T-maze. Our results confirm individual learning abilities in classical conditioning of cockroaches that was reported for honeybees and vertebrates but contrast long-standing reports on stochastic learning behavior in fruit flies. In our experiments, most learners expressed a correct behavior after only a single learning trial showing a consistent high performance during training and test. We can further show that individual learning differences in insects are not limited to classical conditioning but equally appear in operant conditioning of the cockroach.

Analysis of Synaptic Microcircuits in the Mushroom Bodies of the Honeybee

Mushroom bodies (MBs) are multisensory integration centers in the insect brain involved in learning and memory formation. In the honeybee, the main sensory input region (calyx) of MBs is comparatively large and receives input from mainly olfactory and visual senses, but also from gustatory/tactile modalities. Behavioral plasticity following differential brood care, changes in sensory exposure or the formation of associative long-term memory (LTM) was shown to be associated with structural plasticity in synaptic microcircuits (microglomeruli) within olfactory and visual compartments of the MB calyx. In the same line, physiological studies have demonstrated that MB-calyx microcircuits change response properties after associative learning. The aim of this review is to provide an update and synthesis of recent research on the plasticity of microcircuits in the MB calyx of the honeybee, specifically looking at the synaptic connectivity between sensory projection neurons (PNs) and MB intrinsic neurons (Kenyon cells). We focus on the honeybee as a favorable experimental insect for studying neuronal mechanisms underlying complex social behavior, but also compare it with other insect species for certain aspects. This review concludes by highlighting open questions and promising routes for future research aimed at understanding the causal relationships between neuronal and behavioral plasticity in this charismatic social insect.

Courtship behavior induced by appetitive olfactory memory

Reinforcement signals such as food reward and noxious punishment can change diverse behaviors. This holds true in fruit flies, Drosophila melanogaster, which can be conditioned by an odor and sugar reward or electric shock punishment. Despite a wide variety of behavior modulated by learning, conditioned responses have been traditionally measured by altered odor preference in a choice, and other memory-guided behaviors have been only scarcely investigated. Here, we analyzed detailed conditioned odor responses of flies after sugar associative learning by employing a video recording and semi-automated processing pipeline. Trajectory analyses revealed that multiple behavioral components were altered along with conditioned approach to the rewarded odor. Notably, we found that lateral wing extension, a hallmark of courtship behavior of D. melanogaster, was robustly increased specifically in the presence of the rewarded odor. Strikingly, genetic disruption of the mushroom body output did not impair conditioned courtship increase, while markedly weakening conditioned odor approach. Our results highlight the complexity of conditioned responses and their distinct regulatory mechanisms that may underlie coordinated yet complex memory-guided behaviors in flies.