Functional feedback from mushroom bodies to antennal lobes in the Drosophila olfactory pathway

Common principles for odour coding across vertebrates and invertebrates

The olfactory system is an ideal and tractable system for exploring how the brain transforms sensory inputs into behaviour. The basic tasks of any olfactory system include odour detection, discrimination and categorization. The challenge for the olfactory system is to transform the high-dimensional space of olfactory stimuli into the much smaller space of perceived objects and valence that endows odours with meaning. Our current understanding of how neural circuits address this challenge has come primarily from observations of the mechanisms of the brain for processing other sensory modalities, such as vision and hearing, in which optimized deep hierarchical circuits are used to extract sensory features that vary along continuous physical dimensions. The olfactory system, by contrast, contends with an ill-defined, high-dimensional stimulus space and discrete stimuli using a circuit architecture that is shallow and parallelized. Here, we present recent observations in vertebrate and invertebrate systems that relate the statistical structure and state-dependent modulation of olfactory codes to mechanisms of perception and odour-guided behaviour.

Olfactory Critical Periods: How Odor Exposure Shapes the Developing Brain in Mice and Flies

Neural networks have an extensive ability to change in response to environmental stimuli. This flexibility peaks during restricted windows of time early in life called critical periods. The ubiquitous occurrence of this form of plasticity across sensory modalities and phyla speaks to the importance of critical periods for proper neural development and function. Extensive investigation into visual critical periods has advanced our knowledge of the molecular events and key processes that underlie the impact of early-life experience on neuronal plasticity. However, despite the importance of olfaction for the overall survival of an organism, the cellular and molecular basis of olfactory critical periods have not garnered extensive study compared to visual critical periods. Recent work providing a comprehensive mapping of the highly organized olfactory neuropil and its development has in turn attracted a growing interest in how these circuits undergo plasticity during critical periods. Here, we perform a comparative review of olfactory critical periods in fruit flies and mice to provide novel insight into the importance of early odor exposure in shaping neural circuits and highlighting mechanisms found across sensory modalities.

Reducing Catastrophic Forgetting With Associative Learning: A Lesson From Fruit Flies

Catastrophic forgetting remains an outstanding challenge in continual learning. Recently, methods inspired by the brain, such as continual representation learning and memory replay, have been used to combat catastrophic forgetting. Associative learning (retaining associations between inputs and outputs, even after good representations are learned) plays an important function in the brain; however, its role in continual learning has not been carefully studied. Here, we identified a two-layer neural circuit in the fruit fly olfactory system that performs continual associative learning between odors and their associated valences. In the first layer, inputs (odors) are encoded using sparse, high-dimensional representations, which reduces memory interference by activating nonoverlapping populations of neurons for different odors. In the second layer, only the synapses between odor-activated neurons and the odor's associated output neuron are modified during learning; the rest of the weights are frozen to prevent unrelated memories from being overwritten. We prove theoretically that these two perceptron-like layers help reduce catastrophic forgetting compared to the original perceptron algorithm, under continual learning. We then show empirically on benchmark data sets that this simple and lightweight architecture outperforms other popular neural-inspired algorithms when also using a two-layer feedforward architecture. Overall, fruit flies evolved an efficient continual associative learning algorithm, and circuit mechanisms from neuroscience can be translated to improve machine computation.

Tyramine and its Amtyr1 receptor modulate attention in honey bees (Apis mellifera)

Animals must learn to ignore stimuli that are irrelevant to survival and attend to ones that enhance survival. When a stimulus regularly fails to be associated with an important consequence, subsequent excitatory learning about that stimulus can be delayed, which is a form of nonassociative conditioning called 'latent inhibition'. Honey bees show latent inhibition toward an odor they have experienced without association with food reinforcement. Moreover, individual honey bees from the same colony differ in the degree to which they show latent inhibition, and these individual differences have a genetic basis. To investigate the mechanisms that underly individual differences in latent inhibition, we selected two honey bee lines for high and low latent inhibition, respectively. We crossed those lines and mapped a Quantitative Trait Locus for latent inhibition to a region of the genome that contains the tyramine receptor gene Amtyr1 [We use Amtyr1 to denote the gene and AmTYR1 the receptor throughout the text.]. We then show that disruption of Amtyr1 signaling either pharmacologically or through RNAi qualitatively changes the expression of latent inhibition but has little or slight effects on appetitive conditioning, and these results suggest that AmTYR1 modulates inhibitory processing in the CNS. Electrophysiological recordings from the brain during pharmacological blockade are consistent with a model that AmTYR1 indirectly regulates at inhibitory synapses in the CNS. Our results therefore identify a distinct Amtyr1-based modulatory pathway for this type of nonassociative learning, and we propose a model for how Amtyr1 acts as a gain control to modulate hebbian plasticity at defined synapses in the CNS. We have shown elsewhere how this modulation also underlies potentially adaptive intracolonial learning differences among individuals that benefit colony survival. Finally, our neural model suggests a mechanism for the broad pleiotropy this gene has on several different behaviors.

The Relationship between Cognition and Brain Size or Neuron Number

The comparative approach is a powerful way to explore the relationship between brain structure and cognitive function. Thus far, the field has been dominated by the assumption that a bigger brain somehow means better cognition. Correlations between differences in brain size or neuron number between species and differences in specific cognitive abilities exist, but these correlations are very noisy. Extreme differences exist between clades in the relationship between either brain size or neuron number and specific cognitive abilities. This means that correlations become weaker, not stronger, as the taxonomic diversity of sampled groups increases. Cognition is the outcome of neural networks. Here we propose that considering plausible neural network models will advance our understanding of the complex relationships between neuron number and different aspects of cognition. Computational modelling of networks suggests that adding pathways, or layers, or changing patterns of connectivity in a network can all have different specific consequences for cognition. Consequently, models of computational architecture can help us hypothesise how and why differences in neuron number might be related to differences in cognition. As methods in connectomics continue to improve and more structural information on animal brains becomes available, we are learning more about natural network structures in brains, and we can develop more biologically plausible models of cognitive architecture. Natural animal diversity then becomes a powerful resource to both test the assumptions of these models and explore hypotheses for how neural network structure and network size might delimit cognitive function.

Delineating Purinergic Signaling in Drosophila

Simplistic models can aid in discovering what is important in the context of normal and pathological behavior. First recognized as a genetic model more than 100 years ago, to date, fruit flies (Drosophila melanogaster) still remain an astonishingly good laboratory stand-in for scientists to study development and physiology and to investigate the molecular mechanisms of human diseases. This is because fruit flies indeed represent a simplistic model. Furthermore, about 75% of human disease-related genes have their counterparts in the Drosophila genome, added to the fact that fruit flies are inexpensive and extremely easy to maintain, being invertebrates and, moreover, lacking any ethical concern issues. Purinergic signaling is, by definition, mediated by extracellular purinergic ligands, among which ATP represents the prototype molecule. A key feature that has progressively emerged when dissecting the purinergic mechanisms is the multilayer and dynamic nature of the signaling sustained by purinergic ligands. Indeed, these last are sequentially metabolized by several different ectonucleotidases, which generate the ligands that simultaneously activate several different purinergic receptors. Since significant purinergic actions have also been described in Drosophila, the aim of the present work is to provide a comprehensive picture of the purinergic events occurring in fruit flies.

Input-timing-dependent plasticity at incoming synapses of the mushroom body facilitates olfactory learning in Drosophila

Aversive olfactory conditioning in Drosophila is a valuable model for elucidating the mechanism of associative learning. Much effort has centered around the role of neuroplasticity at the mushroom body (MB)-mushroom body output neuron (MBON) synapses in mapping odors to specific behaviors. By electrophysiological recordings from MB neurons, we discovered a form of input-timing-dependent plasticity at the incoming synapses from projection neurons that controls the efficacy of aversive olfactory memory formation. Importantly, this plasticity is facilitated by the neural activity of PPL1, the neuronal cluster that also modulates MB-MBON connections at the output stage of MB. Unlike the MB-MBON synapses that probably utilize dopamine D1-like receptors, this neuroplasticity is dependent on D2-like receptors that are expressed mainly by γ Kenyon cells noticeably in their somato-dendritic region. The D2-like receptors recruit voltage-gated calcium channels, leading to calcium influx in the soma and dendrites of γ neurons. Together, our results reveal a previously unrecognized synaptic component of the MB circuit architecture that not only could increase the salience of a conditioning odor but also couples the process of memory encoding and valency mapping to drive-associative learning.

Different Binding Affinities of Three General Odorant-Binding Proteins in Grapholita funebrana (Treitscheke) (Lepidoptera: Tortricidae) to Sex Pheromones, Host Plant Volatiles, and Insecticides

Insect general odorant-binding proteins (GOBPs) play irreplaceable roles in filtering, binding, and transporting host odorants to olfactory receptors. Grapholita funebrana (Treitscheke) (Lepidoptera: Tortricidae), an economically important pest of fruit crops, uses fruit volatiles as cues to locate host plants. However, the functions of GOBPs in G. funebrana are still unknown. Three GOBP genes, namely, GfunGOBP1, GfunGOBP2, and GfunGOBP3, were cloned, and their expression profiles in different tissues were detected by the method of real-time quantitative PCR (RT-qPCR). The binding properties of recombinant GfunGOBPs (rGfunGOBPs) to various ligands were investigated via fluorescence binding assays. The three GfunGOBPs were mainly expressed in the antennae of both male and female moths. All these three rGfunGOBPs could bind to sex pheromones, while having varying affinities toward these pheromones. The three rGfunGOBPs also displayed a wide range of ligand-binding spectrums with tested host odorants. The rGfunGOBP1, rGfunGOBP2, and rGfunGOBP3 bound to 34, 33, and 30 out of the 41 tested odorants, respectively. Three rGfunGOBPs had overlapping binding activities to β-myrcene, (-)-α-phellandrene, and ethyl isovalerate with the Ki less than 3.0 μM. The rGfunGOBP1 and rGfunGOBP3 could selectively bind to several insecticides, whereas rGfunGOBP2 could not. Three rGfunGOBPs had the dual functions of selectively binding to sex pheromones and host odorants. Moreover, the rGfunGOBP1 and rGfunGOBP3 can also serve as 'signal proteins' and bind to different insecticides. This study contributed to elucidating the potential molecular mechanism of the olfaction for G. funebrana, and thereby promotes the development of effective botanical attractants or pheromone synergists to control G. funebrana.

Dopamine activity in projection neurons regulates short-lasting olfactory approach memory in Drosophila

Survival in many animals requires the ability to associate certain cues with danger and others with safety. In a Drosophila melanogaster aversive olfactory conditioning paradigm, flies are exposed to two odours, one presented coincidentally with electrical shocks, and a second presented 45 s after shock cessation. When flies are later given a choice between these two odours, they avoid the shock‐paired odour and prefer the unpaired odour. While many studies have examined how flies learn to avoid the shock‐paired odour through formation of odour‐fear associations, here we demonstrate that conditioning also causes flies to actively approach the second odour. In contrast to fear memories, which are longer lasting and requires activity of D1‐like dopamine receptors only in the mushroom bodies, approach memory is short‐lasting and requires activity of D1‐like dopamine receptors in projection neurons originating from the antennal lobes, primary olfactory centers. Further, while recall of fear memories requires activity of the mushroom bodies, recall of approach memories does not. Our data suggest that olfactory approach memory is formed using different mechanisms in different brain locations compared to aversive and appetitive olfactory memories.

Novelty detection in early olfactory processing of the honey bee, Apis mellifera

Animals are constantly bombarded with stimuli, which presents a fundamental problem of sorting among pervasive uninformative stimuli and novel, possibly meaningful stimuli. We evaluated novelty detection behaviorally in honey bees as they position their antennae differentially in an air stream carrying familiar or novel odors. We then characterized neuronal responses to familiar and novel odors in the first synaptic integration center in the brain-the antennal lobes. We found that the neurons that exhibited stronger initial responses to the odor that was to be familiarized are the same units that later distinguish familiar and novel odors, independently of chemical identities. These units, including both tentative projection neurons and local neurons, showed a decreased response to the familiar odor but an increased response to the novel odor. Our results suggest that the antennal lobe may represent familiarity or novelty to an odor stimulus in addition to its chemical identity code. Therefore, the mechanisms for novelty detection may be present in early sensory processing, either as a result of local synaptic interaction or via feedback from higher brain centers.

Choline Transporter regulates olfactory habituation via a neuronal triad of excitatory, inhibitory and mushroom body neurons

Choline is an essential component of Acetylcholine (ACh) biosynthesis pathway which requires high-affinity Choline transporter (ChT) for its uptake into the presynaptic terminals of cholinergic neurons. Previously, we had reported a predominant expression of ChT in memory processing and storing region of the Drosophila brain called mushroom bodies (MBs). It is unknown how ChT contributes to the functional principles of MB operation. Here, we demonstrate the role of ChT in Habituation, a non-associative form of learning. Odour driven habituation traces are laid down in ChT dependent manner in antennal lobes (AL), projection neurons (PNs), and MBs. We observed that reduced habituation due to knock-down of ChT in MBs causes hypersensitivity towards odour, suggesting that ChT also regulates incoming stimulus suppression. Importantly, we show for the first time that ChT is not unique to cholinergic neurons but is also required in inhibitory GABAergic neurons to drive habituation behaviour. Our results support a model in which ChT regulates both habituation and incoming stimuli through multiple circuit loci via an interplay between excitatory and inhibitory neurons. Strikingly, the lack of ChT in MBs shows characteristics similar to the major reported features of Autism spectrum disorders (ASD), including attenuated habituation, sensory hypersensitivity as well as defective GABAergic signalling. Our data establish the role of ChT in habituation and suggest that its dysfunction may contribute to neuropsychiatric disorders like ASD.

Localized inhibition in the Drosophila mushroom body

Many neurons show compartmentalized activity, in which activity does not spread readily across the cell, allowing input and output to occur locally. However, the functional implications of compartmentalized activity for the wider neural circuit are often unclear. We addressed this problem in the Drosophila mushroom body, whose principal neurons, Kenyon cells, receive feedback inhibition from a non-spiking interneuron called the anterior paired lateral (APL) neuron. We used local stimulation and volumetric calcium imaging to show that APL inhibits Kenyon cells’ dendrites and axons, and that both activity in APL and APL’s inhibitory effect on Kenyon cells are spatially localized (the latter somewhat less so), allowing APL to differentially inhibit different mushroom body compartments. Applying these results to the Drosophila hemibrain connectome predicts that individual Kenyon cells inhibit themselves via APL more strongly than they inhibit other individual Kenyon cells. These findings reveal how cellular physiology and detailed network anatomy can combine to influence circuit function.

High-performance FRET biosensors for single-cell and in vivo lead detection

Forms of lead (Pb) have been insidiously invading human life for thousands of years without obvious signs of their considerable danger to human health. Blood lead level (BLL) is the routine measure used for diagnosing the degree of lead intoxication, although it is unclear whether there is any safe range of BLL. To develop a practical detection tool for living organisms, we engineered a genetically encoded fluorescence resonance energy transfer (FRET)-based Pb²⁺ biosensor, 'Met-lead 1.44 M1', with excellent performance. Met-lead 1.44 M1 has an apparent dissociation constant (K_d) of 25.97 nM, a detection limit (LOD) of 10 nM (2.0 ppb/0.2 μg/dL), and an enhancement dynamic ratio of nearly ~ 5-fold upon Pb²⁺ binding. The 10 nM sensitivity of Met-lead 1.44 M1 is five times below the World Health Organization-permitted level of lead in tap water (10 ppb; WHO, 2017), and fifteen times lower than the maximum BLL for children (3 μg/dL). We deployed Met-lead 1.44 M1 to measure Pb²⁺ concentrations in different living models, including two general human cell lines and one specific line, induced pluripotent stem cell (iPSC)-derived cardiomyocytes, as well as in widely used model species in plant (Arabidopsis thaliana) and animal (Drosophila melanogaster) research. Our results suggest that this new biosensor is suitable for lead toxicological research in vitro and in vivo, and will pave the way toward potential applications for both low BLL measures and rapid detection of environmental lead in its divalent form.

Monitoring the Heavy Metal Lead Inside Living Drosophila with a FRET-Based Biosensor

The harmful impact of the heavy metal lead on human health has been known for years. However, materials that contain lead remain in the environment. Measuring the blood lead level (BLL) is the only way to officially evaluate the degree of exposure to lead. The so-called "safe value" of the BLL seems to unreliably represent the secure threshold for children. In general, lead's underlying toxicological mechanism remains unclear and needs to be elucidated. Therefore, we developed a novel genetically encoded fluorescence resonance energy transfer (FRET)-based lead biosensor, Met-lead, and applied it to transgenic Drosophila to perform further investigations. We combined Met-lead with the UAS-GAL4 system to the sensor protein specifically expressed within certain regions of fly brains. Using a suitable imaging platform, including a fast epifluorescent or confocal laser-scanning/two-photon microscope with high resolution, we recorded the changes in lead content inside fly brains ex vivo and in vivo and at different life stages. The blood-brain barrier was found to play an important role in the protection of neurons in the brain against damage due to the heavy metal lead, either through food or microinjection into the abdomen. Met-lead has the potential to be a powerful tool for the sensing of lead within living organisms by employing either a fast epi-FRET microscope or high-resolution brain imaging.

Distributed plasticity in ant visual pathways following colour learning

Colour processing at early stages of visual pathways is a topic of intensive study both in vertebrate and invertebrate species. However, it is still unclear how colour learning and memory formation affects an insect brain in the peripheral processing stages and high-order integration centres, and whether associative colour experiences are reflected in plasticity of underlying neuronal circuits. To address this issue, we used Camponotus blandus ants as their proven colour learning and memory capabilities, precisely controllable age and experience, and already known central visual pathways offer unique access to analyse plasticity in neuronal circuits for colour vision in a miniature brain. The potential involvement of distinct neuropils-optic lobes (OLs), mushroom body (MB) input (collar) and output (vertical lobe), anterior optic tubercle (AOTU) and central complex (CX)-in associative colour experiences was assessed by quantification of volumetric and synaptic changes (MB collar) directly after colour conditioning and, 3 days later, after the establishment of long-term memory (LTM). To account for potential effects of non-associative light exposure, we compared neuronal changes in the brain of colour-naive foragers with those of foragers that had been exposed to light in a non-associative way. The results clearly show that the OLs, AOTU, and CX respond with plastic changes after colour learning and LTM formation. This suggests a complex neuronal network for colour learning and memory formation involving multiple brain levels. Such a colour-processing network probably represents an efficient design promoting fast and accurate behavioural decisions during orientation and navigation.

Visual-Olfactory Integration in the Human Disease Vector Mosquito Aedes aegypti

Mosquitoes rely on the integration of multiple sensory cues, including olfactory, visual, and thermal stimuli, to detect, identify, and locate their hosts [1-4]. Although we increasingly know more about the role of chemosensory behaviors in mediating mosquito-host interactions [1], the role of visual cues is comparatively less studied [3], and how the combination of olfactory and visual information is integrated in the mosquito brain remains unknown. In the present study, we used a tethered-flight light-emitting diode (LED) arena, which allowed for quantitative control over the stimuli, and a control theoretic model to show that CO₂ modulates mosquito steering responses toward vertical bars. To gain insight into the neural basis of this olfactory and visual coupling, we conducted two-photon microscopy experiments in a new GCaMP6s-expressing mosquito line. Imaging revealed that neuropil regions within the lobula exhibited strong responses to objects, such as a bar, but showed little response to a large-field motion. Approximately 20% of the lobula neuropil we imaged were modulated when CO₂ preceded the presentation of a moving bar. By contrast, responses in the antennal (olfactory) lobe were not modulated by visual stimuli presented before or after an olfactory stimulus. Together, our results suggest that asymmetric coupling between these sensory systems provides enhanced steering responses to discrete objects.

Contribution of non-circadian neurons to the temporal organization of locomotor activity

In the fruit fly, Drosophila melanogaster, the daily cycle of rest and activity is a rhythmic behavior that relies on the activity of a small number of neurons. The small ventral lateral neurons (sLNvs) are considered key in the control of locomotor rhythmicity. Previous work from our laboratory has showed that these neurons undergo structural remodeling on their axonal projections on a daily basis. Such remodeling endows sLNvs with the possibility to make synaptic contacts with different partners at different times throughout the day, as has been previously described. By using different genetic tools to alter membrane excitability of the sLNv putative postsynaptic partners, we tested their functional role in the control of locomotor activity. We also used optical imaging to test the functionality of these contacts. We found that these different neuronal groups affect the consolidation of rhythmic activity, suggesting that non-circadian cells are part of the circuit that controls locomotor activity. Our results suggest that new neuronal groups, in addition to the well-characterized clock neurons, contribute to the operations of the circadian network that controls locomotor activity in D. melanogaster.

Summary: Here we characterized the impact of different putative postsynaptic partners of the sLNvs on the control of rhythmic locomotor behavior. We found that some of these novel neuronal clusters are relevant for the control of locomotor activity.

Building a functional connectome of the Drosophila central complex

The central complex is a highly conserved insect brain region composed of morphologically stereotyped neurons that arborize in distinctively shaped substructures. The region is implicated in a wide range of behaviors and several modeling studies have explored its circuit computations. Most studies have relied on assumptions about connectivity between neurons based on their overlap in light microscopy images. Here, we present an extensive functional connectome of Drosophila melanogaster's central complex at cell-type resolution. Using simultaneous optogenetic stimulation, calcium imaging and pharmacology, we tested the connectivity between 70 presynaptic-to-postsynaptic cell-type pairs. We identified numerous inputs to the central complex, but only a small number of output channels. Additionally, the connectivity of this highly recurrent circuit appears to be sparser than anticipated from light microscopy images. Finally, the connectivity matrix highlights the potentially critical role of a class of bottleneck interneurons. All data are provided for interactive exploration on a website.

The interruptive effect of electric shock on odor response requires mushroom bodies in Drosophila melanogaster

Nociceptive stimulus involuntarily interrupts concurrent activities. This interruptive effect is related to the protective function of nociception that is believed to be under stringent evolutionary pressure. To determine whether such interruptive effect is conserved in invertebrate and potentially uncover underlying neural circuits, we examined Drosophila melanogaster. Electric shock (ES) is a commonly used nociceptive stimulus for nociception related research in Drosophila. Here, we showed that background noxious ES dramatically interrupted odor response behaviors in a T-maze, which is termed blocking odor response by electric shock (BOBE). The interruptive effect is not odor specific. ES could interrupt both odor avoidance and odor approach. To identify involved brain areas, we focused on the odor avoidance to 3-OCT. By spatially abolishing neurotransmission with temperature sensitive Shibire^TS1 , we found that mushroom bodies (MBs) are necessary for BOBE. Among the 3 major MB Kenyon cell (KCs) subtypes, α/β neurons and γ neurons but not α'/β' neurons are required for normal BOBE. Specifically, abolishing the neurotransmission of either α/β surface (α/β_s ), α/β core (α/β_c ) or γ dorsal (γ_d ) neurons alone is sufficient to abrogate BOBE. This pattern of MB subset requirement is distinct from that of aversive olfactory learning, indicating a specialized BOBE pathway. Consistent with this idea, BOBE was not diminished in several associative memory mutants and noxious ES interrupted both innate and learned odor avoidance. Overall, our results suggest that MB α/β and γ neurons are parts of a previously unappreciated central neural circuit that processes the interruptive effect of nociception.

Olfactory coding in the turbulent realm

Long-distance olfactory search behaviors depend on odor detection dynamics. Due to turbulence, olfactory signals travel as bursts of variable concentration and spacing and are characterized by long-tail distributions of odor/no-odor events, challenging the computing capacities of olfactory systems. How animals encode complex olfactory scenes to track the plume far from the source remains unclear. Here we focus on the coding of the plume temporal dynamics in moths. We compare responses of olfactory receptor neurons (ORNs) and antennal lobe projection neurons (PNs) to sequences of pheromone stimuli either with white-noise patterns or with realistic turbulent temporal structures simulating a large range of distances (8 to 64 m) from the odor source. For the first time, we analyze what information is extracted by the olfactory system at large distances from the source. Neuronal responses are analyzed using linear-nonlinear models fitted with white-noise stimuli and used for predicting responses to turbulent stimuli. We found that neuronal firing rate is less correlated with the dynamic odor time course when distance to the source increases because of improper coding during long odor and no-odor events that characterize large distances. Rapid adaptation during long puffs does not preclude however the detection of puff transitions in PNs. Individual PNs but not individual ORNs encode the onset and offset of odor puffs for any temporal structure of stimuli. A higher spontaneous firing rate coupled to an inhibition phase at the end of PN responses contributes to this coding property. This allows PNs to decode the temporal structure of the odor plume at any distance to the source, an essential piece of information moths can use in their tracking behavior.

Serotonergic Modulation Enables Pathway-Specific Plasticity in a Developing Sensory Circuit in Drosophila

How experiences during development cause long-lasting changes in sensory circuits and affect behavior in mature animals are poorly understood. Here we establish a novel system for mechanistic analysis of the plasticity of developing neural circuits by showing that sensory experience during development alters nociceptive behavior and circuit physiology in Drosophila larvae. Despite the convergence of nociceptive and mechanosensory inputs on common second-order neurons (SONs), developmental noxious input modifies transmission from nociceptors to their SONs, but not from mechanosensors to the same SONs, which suggests striking sensory pathway specificity. These SONs activate serotonergic neurons to inhibit nociceptor-to-SON transmission; stimulation of nociceptors during development sensitizes nociceptor presynapses to this feedback inhibition. Our results demonstrate that, unlike associative learning, which involves inputs from two sensory pathways, sensory pathway-specific plasticity in the Drosophila nociceptive circuit is in part established through feedback modulation. This study elucidates a novel mechanism that enables pathway-specific plasticity in sensory systems. VIDEO ABSTRACT.

Olfactory learning without the mushroom bodies: Spiking neural network models of the honeybee lateral antennal lobe tract reveal its capacities in odour memory tasks of varied complexities

The honeybee olfactory system is a well-established model for understanding functional mechanisms of learning and memory. Olfactory stimuli are first processed in the antennal lobe, and then transferred to the mushroom body and lateral horn through dual pathways termed medial and lateral antennal lobe tracts (m-ALT and l-ALT). Recent studies reported that honeybees can perform elemental learning by associating an odour with a reward signal even after lesions in m-ALT or blocking the mushroom bodies. To test the hypothesis that the lateral pathway (l-ALT) is sufficient for elemental learning, we modelled local computation within glomeruli in antennal lobes with axons of projection neurons connecting to a decision neuron (LHN) in the lateral horn. We show that inhibitory spike-timing dependent plasticity (modelling non-associative plasticity by exposure to different stimuli) in the synapses from local neurons to projection neurons decorrelates the projection neurons' outputs. The strength of the decorrelations is regulated by global inhibitory feedback within antennal lobes to the projection neurons. By additionally modelling octopaminergic modification of synaptic plasticity among local neurons in the antennal lobes and projection neurons to LHN connections, the model can discriminate and generalize olfactory stimuli. Although positive patterning can be accounted for by the l-ALT model, negative patterning requires further processing and mushroom body circuits. Thus, our model explains several-but not all-types of associative olfactory learning and generalization by a few neural layers of odour processing in the l-ALT. As an outcome of the combination between non-associative and associative learning, the modelling approach allows us to link changes in structural organization of honeybees' antennal lobes with their behavioural performances over the course of their life.

Neonicotinoid-induced impairment of odour coding in the honeybee

Exposure to neonicotinoid pesticides is considered one of the possible causes of honeybee (Apis mellifera) population decline. At sublethal doses, these chemicals have been shown to negatively affect a number of behaviours, including performance of olfactory learning and memory, due to their interference with acetylcholine signalling in the mushroom bodies. Here we provide evidence that neonicotinoids can affect odour coding upstream of the mushroom bodies, in the first odour processing centres of the honeybee brain, i.e. the antennal lobes (ALs). In particular, we investigated the effects of imidacloprid, the most common neonicotinoid, in the AL glomeruli via in vivo two-photon calcium imaging combined with pulsed odour stimulation. Following acute imidacloprid treatment, odour-evoked calcium response amplitude in single glomeruli decreases, and at the network level the representations of different odours are no longer separated. This demonstrates that, under neonicotinoid influence, olfactory information might reach the mushroom bodies in a form that is already incorrect. Thus, some of the impairments in olfactory learning and memory caused by neonicotinoids could, in fact, arise from the disruption in odor coding and olfactory discrimination ability of the honey bees.

Synaptic circuitry of identified neurons in the antennal lobe of Drosophila melanogaster

In Drosophila melanogaster olfactory sensory neurons (OSNs) establish synapses with projection neurons (PNs) and local interneurons within antennal lobe (AL) glomeruli. Substantial knowledge regarding this circuitry has been obtained by functional studies, whereas ultrastructural evidence of synaptic contacts is scarce. To fill this gap, we studied serial sections of three glomeruli using electron microscopy. Ectopic expression of a membrane-bound peroxidase allowed us to map synaptic sites along PN dendrites. Our data prove for the first time that each of the three major types of AL neurons is both pre- and postsynaptic to the other two types, as previously indicated by functional studies. PN dendrites carry a large proportion of output synapses, with approximately one output per every three input synapses. Detailed reconstructions of PN dendrites showed that these synapses are distributed unevenly, with input and output sites partially segregated along a proximal-distal gradient and the thinnest branches carrying solely input synapses. Moreover, our data indicate synapse clustering, as we found evidence of dendritic tiling of PN dendrites. PN output synapses exhibited T-shaped presynaptic densities, mostly arranged as tetrads. In contrast, output synapses from putative OSNs showed elongated presynaptic densities in which the T-bar platform was supported by several pedestals and contacted as many as 20 postsynaptic profiles. We also discovered synaptic contacts between the putative OSNs. The average synaptic density in the glomerular neuropil was about two synapses/µm(3) . These results are discussed with regard to current models of olfactory glomerular microcircuits across species.

Multimodal interaction in the insect brain

Background

The magnitude of multimodal enhancement in the brain is believed to depend on the stimulus intensity and timing. Such an effect has been found in many species, but has not been previously investigated in insects.

Results

We investigated the responses to multimodal stimuli consisting of an odour and a colour in the antennal lobe and mushroom body of the moth Manduca sexta. The mushroom body shows enhanced responses for multimodal stimuli consisting of a general flower odour and a blue colour. No such effect was seen for a bergamot odour. The enhancement shows an inverse effectiveness where the responses to weaker multimodal stimuli are amplified more than those to stronger stimuli. Furthermore, the enhancement depends on the precise timing of the two stimulus components.

Conclusions

Insect multimodal processing show both the principle of inverse effectiveness and the existence of an optimal temporal window.

Electronic supplementary material

The online version of this article (doi:10.1186/s12868-016-0258-7) contains supplementary material, which is available to authorized users.

Light, heat, action: neural control of fruit fly behaviour

The fruit fly Drosophila melanogaster has emerged as a popular model to investigate fundamental principles of neural circuit operation. The sophisticated genetics and small brain permit a cellular resolution understanding of innate and learned behavioural processes. Relatively recent genetic and technical advances provide the means to specifically and reproducibly manipulate the function of many fly neurons with temporal resolution. The same cellular precision can also be exploited to express genetically encoded reporters of neural activity and cell-signalling pathways. Combining these approaches in living behaving animals has great potential to generate a holistic view of behavioural control that transcends the usual molecular, cellular and systems boundaries. In this review, we discuss these approaches with particular emphasis on the pioneering studies and those involving learning and memory.

Modelling Odor Decoding in the Antennal Lobe by Combining Sequential Firing Rate Models with Bayesian Inference

The olfactory information that is received by the insect brain is encoded in the form of spatiotemporal patterns in the projection neurons of the antennal lobe. These dense and overlapping patterns are transformed into a sparse code in Kenyon cells in the mushroom body. Although it is clear that this sparse code is the basis for rapid categorization of odors, it is yet unclear how the sparse code in Kenyon cells is computed and what information it represents. Here we show that this computation can be modeled by sequential firing rate patterns using Lotka-Volterra equations and Bayesian online inference. This new model can be understood as an ‘intelligent coincidence detector’, which robustly and dynamically encodes the presence of specific odor features. We found that the model is able to qualitatively reproduce experimentally observed activity in both the projection neurons and the Kenyon cells. In particular, the model explains mechanistically how sparse activity in the Kenyon cells arises from the dense code in the projection neurons. The odor classification performance of the model proved to be robust against noise and time jitter in the observed input sequences. As in recent experimental results, we found that recognition of an odor happened very early during stimulus presentation in the model. Critically, by using the model, we found surprising but simple computational explanations for several experimental phenomena.

Odor recognition in the insect brain is amazingly fast but still not fully understood. It is known that recognition is performed in three stages. In the first stage, the sensors respond to an odor by displaying a reproducible neuronal pattern. This code is turned, in the second and third stages, into a sparse code, that is, only relatively few neurons activate over hundreds of milliseconds. It is generally assumed that the insect brain uses this temporal code to recognize an odor. We propose a new model of how this temporal code emerges using sequential activation of groups of neurons. We show that these sequential activations underlie a fast and accurate recognition which is highly robust against neuronal or sensory noise. This model replicates several key experimental findings and explains how the insect brain achieves both speed and robustness of odor recognition as observed in experiments.

Decision-making and action selection in insects: inspiration from vertebrate-based theories

Effective decision-making, one of the most crucial functions of the brain, entails the analysis of sensory information and the selection of appropriate behavior in response to stimuli. Here, we consider the current state of knowledge on the mechanisms of decision-making and action selection in the insect brain, with emphasis on the olfactory processing system. Theoretical and computational models of decision-making emphasize the importance of using inhibitory connections to couple evidence-accumulating pathways; this coupling allows for effective discrimination between competing alternatives and thus enables a decision maker to reach a stable unitary decision. Theory also shows that the coupling of pathways can be implemented using a variety of different mechanisms and vastly improves the performance of decision-making systems. The vertebrate basal ganglia appear to resolve stable action selection by being a point of convergence for multiple excitatory and inhibitory inputs such that only one possible response is selected and all other alternatives are suppressed. Similar principles appear to operate within the insect brain. The insect lateral protocerebrum (LP) serves as a point of convergence for multiple excitatory and inhibitory channels of olfactory information to effect stable decision and action selection, at least for olfactory information. The LP is a rather understudied region of the insect brain, yet this premotor region may be key to effective resolution of action section. We argue that it may be beneficial to use models developed to explore the operation of the vertebrate brain as inspiration when considering action selection in the invertebrate domain. Such an approach may facilitate the proposal of new hypotheses and furthermore frame experimental studies for how decision-making and action selection might be achieved in insects.

Characterization of dopamine releasable and reserve pools in Drosophila larvae using ATP/P2X2 -mediated stimulation

Dopaminergic signaling pathways are conserved between mammals and Drosophila, but the factors important for maintaining the functional pool of synaptic dopamine are not fully understood in Drosophila. In this study, we characterized the releasable and reserve dopamine pools in Drosophila larvae using ATP/P2X2 -mediated stimulation. Dopamine release was stable with stimulations performed at least every 5 min but decayed with stimulations performed 2 min apart or less, indicating the replenishment of the releasable pool occurred on a time scale between 2 and 5 min. Dopamine synthesis or uptake was pharmacologically inhibited with 3-iodotyrosine and cocaine, respectively, to evaluate their contributions to maintain the releasable dopamine pool. We found that both synthesis and uptake were needed to maintain the releasable dopamine pool, with synthesis playing a major part in long-term replenishment and uptake being more important for short-term replenishment. These effects of synthesis and uptake on different time scales in Drosophila are analogous to mammals. However, unlike in mammals, cocaine did not activate a reserve pool of dopamine in Drosophila when using P2X2 stimulations. Our study shows that both synthesis and uptake replenish the releasable pool, providing a better understanding of dopamine regulation in Drosophila. The maintenance of the releasable dopamine pool was examined in Drosophila larva. Both synthesis and uptake were needed to maintain the releasable dopamine pool, with synthesis being most important on a longer time scale and uptake on a shorter time scale. Dopamine release was stimulated by applying ATP which activated P2X2 channels specifically expressed in dopaminergic neurons.

Identification of motor neurons and a mechanosensitive sensory neuron in the defecation circuitry of Drosophila larvae

Defecation allows the body to eliminate waste, an essential step in food processing for animal survival. In contrast to the extensive studies of feeding, its obligate counterpart, defecation, has received much less attention until recently. In this study, we report our characterizations of the defecation behavior of Drosophila larvae and its neural basis. Drosophila larvae display defecation cycles of stereotypic frequency, involving sequential contraction of hindgut and anal sphincter. The defecation behavior requires two groups of motor neurons that innervate hindgut and anal sphincter, respectively, and can excite gut muscles directly. These two groups of motor neurons fire sequentially with the same periodicity as the defecation behavior, as revealed by in vivo Ca(2+) imaging. Moreover, we identified a single mechanosensitive sensory neuron that innervates the anal slit and senses the opening of the intestine terminus. This anus sensory neuron relies on the TRP channel NOMPC but not on INACTIVE, NANCHUNG, or PIEZO for mechanotransduction.

Epigenetic control of learning and memory in Drosophila by Tip60 HAT action

Disruption of epigenetic gene control mechanisms in the brain causes significant cognitive impairment that is a debilitating hallmark of most neurodegenerative disorders, including Alzheimer's disease (AD). Histone acetylation is one of the best characterized of these epigenetic mechanisms that is critical for regulating learning- and memory- associated gene expression profiles, yet the specific histone acetyltransferases (HATs) that mediate these effects have yet to be fully characterized. Here, we investigate an epigenetic role for the HAT Tip60 in learning and memory formation using the Drosophila CNS mushroom body (MB) as a well-characterized cognition model. We show that Tip60 is endogenously expressed in the Kenyon cells, the intrinsic neurons of the MB, and in the MB axonal lobes. Targeted loss of Tip60 HAT activity in the MB causes thinner and shorter axonal lobes while increasing Tip60 HAT levels cause no morphological defects. Functional consequences of both loss and gain of Tip60 HAT levels in the MB are evidenced by defects in immediate-recall memory. Our ChIP-Seq analysis reveals that Tip60 target genes are enriched for functions in cognitive processes, and, accordingly, key genes representing these pathways are misregulated in the Tip60 HAT mutant fly brain. Remarkably, we find that both learning and immediate-recall memory deficits that occur under AD-associated, amyloid precursor protein (APP)-induced neurodegenerative conditions can be effectively rescued by increasing Tip60 HAT levels specifically in the MB. Together, our findings uncover an epigenetic transcriptional regulatory role for Tip60 in cognitive function and highlight the potential of HAT activators as a therapeutic option for neurodegenerative disorders.

Network plasticity in adaptive filtering and behavioral habituation

The ability of organisms to seamlessly ignore familiar, inconsequential stimuli improves their selective attention and response to salient features of the environment. Here, I propose that this fundamental but unexplained phenomenon substantially derives from the ability of any pattern of neural excitation to create an enhanced inhibitory (or "negative") image of itself through target-specific scaling of inhibitory inputs onto active excitatory neurons. Familiar stimuli encounter strong negative images and are therefore less likely to be transmitted to higher brain centers. Integrating historical and recent observations, the negative-image model described here provides a mechanistic framework for understanding habituation, which is connected to ideas on dynamic predictive coding. In addition, it suggests insights for understanding autism spectrum disorders.

Azadirachtin blocks the calcium channel and modulates the cholinergic miniature synaptic current in the central nervous system of Drosophila

BACKGROUND

Azadirachtin is a botanical pesticide, which possesses conspicuous biological actions such as insecticidal, anthelmintic, antifeedancy, antimalarial effects as well as insect growth regulation. Deterrent for chemoreceptor functions appears to be the main mechanism involved in the potent biological actions of Azadirachtin, although the cytotoxicity and subtle changes to skeletal muscle physiology may also contribute to its insecticide responses. In order to discover the effects of Azadirachtin on the central nervous system (CNS), patch-clamp recording was applied to Drosophila melanogaster, which has been widely used in neurological research.

RESULTS

Here, we describe the electrophysiological properties of a local neuron located in the suboesophageal ganglion region of D. melanogaster using the whole brain. The patch-clamp recordings suggested that Azadirachtin modulates the properties of cholinergic miniature excitatory postsynaptic current (mEPSC) and calcium currents, which play important roles in neural activity of the CNS. The frequency of mEPSC and the peak amplitude of the calcium currents significantly decreased after application of Azadirachtin.

CONCLUSION

Our study indicates that Azadirachtin can interfere with the insect's CNS via inhibition of excitatory cholinergic transmission and partly blocking the calcium channel.

Multisensory integration of colors and scents: insights from bees and flowers

Karl von Frisch's studies of bees' color vision and chemical senses opened a window into the perceptual world of a species other than our own. A century of subsequent research on bees' visual and olfactory systems has developed along two productive but independent trajectories, leaving the questions of how and why bees use these two senses in concert largely unexplored. Given current interest in multimodal communication and recently discovered interplay between olfaction and vision in humans and Drosophila, understanding multisensory integration in bees is an opportunity to advance knowledge across fields. Using a classic ethological framework, we formulate proximate and ultimate perspectives on bees' use of multisensory stimuli. We discuss interactions between scent and color in the context of bee cognition and perception, focusing on mechanistic and functional approaches, and we highlight opportunities to further explore the development and evolution of multisensory integration. We argue that although the visual and olfactory worlds of bees are perhaps the best-studied of any non-human species, research focusing on the interactions between these two sensory modalities is vitally needed.

Olfactory coding in the insect brain: data and conjectures

Much progress has been made recently in understanding how olfactory coding works in insect brains. Here, I propose a wiring diagram for the major steps from the first processing network (the antennal lobe) to behavioral readout. I argue that the sequence of lateral inhibition in the antennal lobe, non-linear synapses, threshold-regulating gated spring network, selective lateral inhibitory networks across glomeruli, and feedforward inhibition to the lateral protocerebrum cover most of the experimental results from different research groups and model species. I propose that the main difference between mushroom bodies and the lateral protocerebrum is not about learned vs. innate behavior. Rather, mushroom bodies perform odor identification, whereas the lateral protocerebrum performs odor evaluation (both learned and innate). I discuss the concepts of labeled line and combinatorial coding and postulate that, under restrictive experimental conditions, these networks lead to an apparent existence of 'labeled line' coding for special odors. Modulatory networks are proposed as switches between different evaluating systems in the lateral protocerebrum. A review of experimental data and theoretical conjectures both contribute to this synthesis, creating new hypotheses for future research.

Odor memories regulate olfactory receptor expression in the sensory periphery

Odor learning induces structural and functional modifications throughout the olfactory system, but it is currently unknown whether this plasticity extends to the olfactory receptors (Or) in the sensory periphery. Here, we demonstrate that odor learning induces plasticity in olfactory receptor expression in the honeybee, Apis mellifera. Using quantitative RT-PCR analysis, we show that six putative floral scent receptors were differentially expressed in the bee antennae depending on the scent environment that the bees experienced. Or151, which we characterized using an in vitro cell expression system as a broadly tuned receptor binding floral odorants such as linalool, and Or11, the specific receptor for the queen pheromone 9-oxo-decenoic acid, were significantly down-regulated after honeybees were conditioned with the respective odorants in an olfactory learning paradigm. Electroantennogram recordings showed that the neural response of the antenna was similarly reduced after odor learning. Long-term odor memory was essential for inducing these changes, suggesting that the molecular mechanisms involved in olfactory memory also regulate olfactory receptor expression. Our study demonstrates for the first time that olfactory receptor expression is experience-dependent and modulated by scent conditioning, providing novel insight into how molecular regulation at the periphery contributes to plasticity in the olfactory system.

Sparse, decorrelated odor coding in the mushroom body enhances learned odor discrimination

Sparse coding may be a general strategy of neural systems to augment memory capacity. In Drosophila, sparse odor coding by the Kenyon cells of the mushroom body is thought to generate a large number of precisely addressable locations for the storage of odor-specific memories. However, it remains untested how sparse coding relates to behavioral performance. Here we demonstrate that sparseness is controlled by a negative feedback circuit between Kenyon cells and the GABAergic anterior paired lateral (APL) neuron. Systematic activation and blockade of each leg of this feedback circuit show that Kenyon cells activate APL and APL inhibits Kenyon cells. Disrupting the Kenyon cell-APL feedback loop decreases the sparseness of Kenyon cell odor responses, increases inter-odor correlations, and prevents flies from learning to discriminate similar, but not dissimilar, odors. These results suggest that feedback inhibition suppresses Kenyon cell activity to maintain sparse, decorrelated odor coding and thus the odor-specificity of memories.

Olfactory habituation in Drosophila-odor encoding and its plasticity in the antennal lobe

A ubiquitous feature of an animal's response to an odorant is that it declines when the odorant is frequently or continuously encountered. This decline in olfactory response, termed olfactory habituation, can have temporally or mechanistically different forms. The neural circuitry of the fruit fly Drosophila melanogaster's olfactory system is well defined in terms of component cells, which are readily accessible to functional studies and genetic manipulation. This makes it a particularly useful preparation for the investigation of olfactory habituation. In addition, the insect olfactory system shares many architectural and functional similarities with mammalian olfactory systems, suggesting that olfactory mechanisms in insects may be broadly relevant. In this chapter, we discuss the likely mechanisms of olfactory habituation in context of the participating cell types, their connectivity, and their roles in sensory processing. We overview the structure and function of key cell types, the mechanisms that stimulate them, and how they transduce and process odor signals. We then consider how each stage of olfactory processing could potentially contribute to behavioral habituation. After this, we overview a variety of recent mechanistic studies that point to an important role for potentiation of inhibitory synapses in the primary olfactory processing center, the antennal lobe, in driving the reduced response to familiar odorants. Following the discussion of mechanisms for short- and long-term olfactory habituation, we end by considering how these mechanisms may be regulated by neuromodulators, which likely play key roles in the induction, gating, or suppression of habituated behavior, and speculate on the relevance of these processes for other forms of learning and memory.

Evolution of the techniques used in studying associative olfactory learning and memory in adult Drosophila in vivo: a historical and technical perspective

Drosophila melanogaster behavioral mutants have been isolated in which the ability to form associative olfactory memories has been disrupted primarily by altering cyclic adenosine monophosphate signal transduction. Unfortunately, the small size of the fruit fly and its neurons has made the application of neurobiological techniques typically used to investigate the physiology underlying these behaviors daunting. However, the realization that adult fruit flies could tolerate a window in the head capsule allowing access to the central structures thought to be involved plus the development of genetically expressed reporters of neuronal function has allowed a meteoric expansion of this field over the last decade. This review attempts to summarize the evolution of the techniques involved from the first use of a window to access these brain areas thought to be involved in associative olfactory learning and memory, the mushroom bodies and antennal lobes, to the current refinements which allow both high-resolution multiphoton imaging and patch clamping of identified neurons while applying the stimuli used in the behavioral protocols. This area of research now appears poised to reveal some very exciting mechanisms underlying behavior.

Local interneurons and projection neurons in the antennal lobe from a spiking point of view

Local computation in microcircuits is an essential feature of distributed information processing in vertebrate and invertebrate brains. The insect antennal lobe represents a spatially confined local network that processes high-dimensional and redundant peripheral input to compute an efficient odor code. Social insects can rely on a particularly rich olfactory receptor repertoire, and they exhibit complex odor-guided behaviors. This corresponds with a high anatomical complexity of their antennal lobe network. In the honeybee, a large number of glomeruli that receive sensory input are interconnected by a dense network of local interneurons (LNs). Uniglomerular projection neurons (PNs) integrate sensory and recurrent local network input into an efficient spatio-temporal odor code. To investigate the specific computational roles of LNs and PNs, we measured several features of sub- and suprathreshold single-cell responses to in vivo odor stimulation. Using a semisupervised cluster analysis, we identified a combination of five characteristic features as sufficient to separate LNs and PNs from each other, independent of the applied odor-stimuli. The two clusters differed significantly in all these five features. PNs showed a higher spontaneous subthreshold activation, assumed higher peak response rates and a more regular spiking pattern. LNs reacted considerably faster to the onset of a stimulus, and their responses were more reliable across stimulus repetitions. We discuss possible mechanisms that can explain our results, and we interpret cell-type-specific characteristics with respect to their functional relevance.

Multichannel brain recordings in behaving Drosophila reveal oscillatory activity and local coherence in response to sensory stimulation and circuit activation

Neural networks in vertebrates exhibit endogenous oscillations that have been associated with functions ranging from sensory processing to locomotion. It remains unclear whether oscillations may play a similar role in the insect brain. We describe a novel "whole brain" readout for Drosophila melanogaster using a simple multichannel recording preparation to study electrical activity across the brain of flies exposed to different sensory stimuli. We recorded local field potential (LFP) activity from >2,000 registered recording sites across the fly brain in >200 wild-type and transgenic animals to uncover specific LFP frequency bands that correlate with: 1) brain region; 2) sensory modality (olfactory, visual, or mechanosensory); and 3) activity in specific neural circuits. We found endogenous and stimulus-specific oscillations throughout the fly brain. Central (higher-order) brain regions exhibited sensory modality-specific increases in power within narrow frequency bands. Conversely, in sensory brain regions such as the optic or antennal lobes, LFP coherence, rather than power, best defined sensory responses across modalities. By transiently activating specific circuits via expression of TrpA1, we found that several circuits in the fly brain modulate LFP power and coherence across brain regions and frequency domains. However, activation of a neuromodulatory octopaminergic circuit specifically increased neuronal coherence in the optic lobes during visual stimulation while decreasing coherence in central brain regions. Our multichannel recording and brain registration approach provides an effective way to track activity simultaneously across the fly brain in vivo, allowing investigation of functional roles for oscillations in processing sensory stimuli and modulating behavior.

Consolidated and labile odor memory are separately encoded within the Drosophila brain

Memories are classified as consolidated (stable) or labile according to whether they withstand amnestic treatment, or not. In contrast to the general prevalence of this classification, its neuronal and molecular basis is poorly understood. Here, we focused on consolidated and labile memories induced after a single cycle training in the Drosophila aversive olfactory conditioning paradigm and we used mutants to define the impact of cAMP signals. At the biochemical level we report that cAMP signals misrelated in either rutabaga (rut) or dunce (dnc) mutants separate between consolidated anesthesia-resistant memory (ARM) and labile anesthesia-sensitive memory (ASM). Those functionally distinct cAMP signals act within different neuronal populations: while rut-dependent cAMP signals act within Kenyon cells (KCs) of the mushroom bodies to support ASM, dnc-sensitive cAMP signals support ARM within antennal lobe local neurons (LNs) and KCs. Collectively, different key positions along the olfactory circuitry seem to get modified during storage of ARM or ASM independently. A precise separation between those functionally distinct cAMP signals seems mandatory to allocate how they support appropriate memories.

Modeling the insect mushroom bodies: application to a delayed match-to-sample task

Despite their small brains, insects show advanced capabilities in learning and task solving. Flies, honeybees and ants are becoming a reference point in neuroscience and a main source of inspiration for autonomous robot design issues and control algorithms. In particular, honeybees demonstrate to be able to autonomously abstract complex associations and apply them in tasks involving different sensory modalities within the insect brain. Mushroom Bodies (MBs) are worthy of primary attention for understanding memory and learning functions in insects. In fact, even if their main role regards olfactory conditioning, they are involved in many behavioral achievements and learning capabilities, as has been shown in honeybees and flies. Owing to the many neurogenetic tools, the fruit fly Drosophila became a source of information for the neuroarchitecture and biochemistry of the MBs, although the MBs of flies are by far simpler in organization than their honeybee orthologs. Electrophysiological studies, in turn, became available on the MBs of locusts and honeybees. In this paper a novel bio-inspired neural architecture is presented, which represents a generalized insect MB with the basic features taken from fruit fly neuroanatomy. By mimicking a number of different MB functions and architecture, we can replace and improve formerly used artificial neural networks. The model is a multi-layer spiking neural network where key elements of the insect brain, the antennal lobes, the lateral horn region, the MBs, and their mutual interactions are modeled. In particular, the model is based on the role of parts of the MBs named MB-lobes, where interesting processing mechanisms arise on the basis of spatio-temporal pattern formation. The introduced network is able to model learning mechanisms like olfactory conditioning seen in honeybees and flies and was found able also to perform more complex and abstract associations, like the delayed matching-to-sample tasks known only from honeybees. A biological basis of the proposed model is presented together with a detailed description of the architecture. Simulation results and remarks on the biological counterpart are also reported to demonstrate the possible applications of the designed computational model. Such neural architecture, able to autonomously learn complex associations is envisaged to be a suitable basis for an immediate implementation within an robot control architecture.

Ensemble response in mushroom body output neurons of the honey bee outpaces spatiotemporal odor processing two synapses earlier in the antennal lobe

Neural representations of odors are subject to computations that involve sequentially convergent and divergent anatomical connections across different areas of the brains in both mammals and insects. Furthermore, in both mammals and insects higher order brain areas are connected via feedback connections. In order to understand the transformations and interactions that this connectivity make possible, an ideal experiment would compare neural responses across different, sequential processing levels. Here we present results of recordings from a first order olfactory neuropile – the antennal lobe (AL) – and a higher order multimodal integration and learning center – the mushroom body (MB) – in the honey bee brain. We recorded projection neurons (PN) of the AL and extrinsic neurons (EN) of the MB, which provide the outputs from the two neuropils. Recordings at each level were made in different animals in some experiments and simultaneously in the same animal in others. We presented two odors and their mixture to compare odor response dynamics as well as classification speed and accuracy at each neural processing level. Surprisingly, the EN ensemble significantly starts separating odor stimuli rapidly and before the PN ensemble has reached significant separation. Furthermore the EN ensemble at the MB output reaches a maximum separation of odors between 84–120 ms after odor onset, which is 26 to 133 ms faster than the maximum separation at the AL output ensemble two synapses earlier in processing. It is likely that a subset of very fast PNs, which respond before the ENs, may initiate the rapid EN ensemble response. We suggest therefore that the timing of the EN ensemble activity would allow retroactive integration of its signal into the ongoing computation of the AL via centrifugal feedback.

Nonassociative plasticity alters competitive interactions among mixture components in early olfactory processing

Experience-related plasticity is an essential component of networks involved in early olfactory processing. However, the mechanisms and functions of plasticity in these neural networks are not well understood. We studied nonassociative plasticity by evaluating responses to two pure odors (A and X) and their binary mixture using calcium imaging of odor-elicited activity in output neurons of the honey bee antennal lobe. Unreinforced exposure to A or X produced no change in the neural response elicited by the pure odors. However, exposure to one odor (e.g. A) caused the response to the mixture to become more similar to that of the other component (X). We also show in behavioral analyses that unreinforced exposure to A caused the mixture to become perceptually more similar to X. These results suggest that nonassociative plasticity modifies neural networks in such a way that it affects local competitive interactions among mixture components. We used a computational model to evaluate the most likely targets for modification. Hebbian modification of synapses from inhibitory local interneurons to projection neurons most reliably produced the observed shift in response to the mixture. These results are consistent with a model in which the antennal lobe acts to filter olfactory information according to its relevance for performing a particular task.

Plasticity of recurrent inhibition in the Drosophila antennal lobe

Recurrent inhibition, wherein excitatory principal neurons stimulate inhibitory interneurons that feedback on the same principal cells, occurs ubiquitously in the brain. However, the regulation and function of recurrent inhibition are poorly understood in terms of the contributing interneuron subtypes as well as their effect on neural and cognitive outputs. In the Drosophila olfactory system, odorants activate olfactory sensory neurons (OSNs), which stimulate projection neurons (PNs) in the antennal lobe. Both OSNs and PNs activate local inhibitory neurons (LNs) that provide either feedforward or recurrent/feedback inhibition in the lobe. During olfactory habituation, prior exposure to an odorant selectively decreases the animal's subsequent response to the odorant. We show here that habituation occurs in response to feedback from PNs. Output from PNs is necessary for olfactory habituation and, in the absence of odorant, direct PN activation is sufficient to induce the odorant-selective behavioral attenuation characteristic of olfactory habituation. PN-induced habituation occludes further odor-induced habituation and similarly requires GABA(A)Rs and NMDARs in PNs, as well as VGLUT and cAMP signaling in the multiglomerular inhibitory local interneurons (LN1) type of LN. Thus, PN output is monitored by an LN subtype whose resultant plasticity underlies behavioral habituation. We propose that recurrent inhibitory motifs common in neural circuits may similarly underlie habituation to other complex stimuli.