Oscillations and sparsening of odor representations in the mushroom body

Olfactory imprinting is triggered by MHC peptide ligands

Olfactory imprinting on environmental, population- and kin-specific cues is a specific form of life-long memory promoting homing of salmon to their natal rivers and the return of coral reef fish to natal sites. Despite its ecological significance, natural chemicals for olfactory imprinting have not been identified yet. Here, we show that MHC peptides function as chemical signals for olfactory imprinting in zebrafish. We found that MHC peptides consisting of nine amino acids elicit olfactory imprinting and subsequent kin recognition depending on the MHC genotype of the fish. In vivo calcium imaging shows that some olfactory bulb neurons are highly sensitive to MHC peptides with a detection threshold at 1 pM or lower, indicating that MHC peptides are potent olfactory stimuli. Responses to MHC peptides overlapped spatially with responses to kin odour but not food odour, consistent with the hypothesis that MHC peptides are natural signals for olfactory imprinting.

Mushroom body miscellanea: transgenic Drosophila strains expressing anatomical and physiological sensor proteins in Kenyon cells

The fruit fly Drosophila melanogaster represents a key model organism for analyzing how neuronal circuits regulate behavior. The mushroom body in the central brain is a particularly prominent brain region that has been intensely studied in several insect species and been implicated in a variety of behaviors, e.g., associative learning, locomotor activity, and sleep. Drosophila melanogaster offers the advantage that transgenes can be easily expressed in neuronal subpopulations, e.g., in intrinsic mushroom body neurons (Kenyon cells). A number of transgenes has been described and engineered to visualize the anatomy of neurons, to monitor physiological parameters of neuronal activity, and to manipulate neuronal function artificially. To target the expression of these transgenes selectively to specific neurons several sophisticated bi- or even multipartite transcription systems have been invented. However, the number of transgenes that can be combined in the genome of an individual fly is limited in practice. To facilitate the analysis of the mushroom body we provide a compilation of transgenic fruit flies that express transgenes under direct control of the Kenyon-cell specific promoter, mb247. The transgenes expressed are fluorescence reporters to analyze neuroanatomical aspects of the mushroom body, proteins to restrict ectopic gene expression to mushroom bodies, or fluorescent sensors to monitor physiological parameters of neuronal activity of Kenyon cells. Some of the transgenic animals compiled here have been published already, whereas others are novel and characterized here for the first time. Overall, the collection of transgenic flies expressing sensor and reporter genes in Kenyon cells facilitates combinations with binary transcription systems and might, ultimately, advance the physiological analysis of mushroom body function.

Synchronous firing of antennal-lobe projection neurons encodes the behaviorally effective ratio of sex-pheromone components in male Manduca sexta

Olfactory stimuli that are essential to an animal's survival and reproduction are often complex mixtures of volatile organic compounds in characteristic proportions. Here, we investigated how these proportions are encoded in the primary olfactory processing center, the antennal lobe, of male Manduca sexta moths. Two key components of the female's sex pheromone, present in an approximately 2:1 ratio, are processed in each of two neighboring glomeruli in the macroglomerular complex (MGC) of males of this species. In wind-tunnel flight experiments, males exhibited behavioral selectivity for ratios approximating the ratio released by conspecific females. The ratio between components was poorly represented, however, in the firing-rate output of uniglomerular MGC projection neurons (PNs). PN firing rate was mostly insensitive to the ratio between components, and individual PNs did not exhibit a preference for a particular ratio. Recording simultaneously from pairs of PNs in the same glomerulus, we found that the natural ratio between components elicited the most synchronous spikes, and altering the proportion of either component decreased the proportion of synchronous spikes. The degree of synchronous firing between PNs in the same glomerulus thus selectively encodes the natural ratio that most effectively evokes the natural behavioral response to pheromone.

Imaging a population code for odor identity in the Drosophila mushroom body

The brain represents sensory information in the coordinated activity of neuronal ensembles. Although the microcircuits underlying olfactory processing are well characterized in Drosophila, no studies to date have examined the encoding of odor identity by populations of neurons and related it to the odor specificity of olfactory behavior. Here we used two-photon Ca(2+) imaging to record odor-evoked responses from >100 neurons simultaneously in the Drosophila mushroom body (MB). For the first time, we demonstrate quantitatively that MB population responses contain substantial information on odor identity. Using a series of increasingly similar odor blends, we identified conditions in which odor discrimination is difficult behaviorally. We found that MB ensemble responses accounted well for olfactory acuity in this task. Kenyon cell ensembles with as few as 25 cells were sufficient to match behavioral discrimination accuracy. Using a generalization task, we demonstrated that the MB population code could predict the flies' responses to novel odors. The degree to which flies generalized a learned aversive association to unfamiliar test odors depended upon the relative similarity between the odors' evoked MB activity patterns. Discrimination and generalization place different demands on the animal, yet the flies' choices in these tasks were reliably predicted based on the amount of overlap between MB activity patterns. Therefore, these different behaviors can be understood in the context of a single physiological framework.

Concentric zones for pheromone components in the mushroom body calyx of the moth brain

The spatial distribution of input and output neurons in the mushroom body (MB) calyx was investigated in the silkmoth Bombyx mori. In Lepidoptera, the brain has a specialized system for processing sex pheromones. How individual pheromone components are represented in the MB has not yet been elucidated. Toward this end, we first compared the distribution of the presynaptic boutons of antennal lobe projection neurons (PNs), which transfer odor information from the antennal lobe to the MB calyx. The axons of PNs that innervate pheromonal glomeruli were confined to a relatively small area within the calyx. In contrast, the axons of PNs that innervate nonpheromonal glomeruli were more widely distributed. PN axons for the minor pheromone component covered a larger area than those for the major pheromone component and partially overlapped with those innervating nonpheromonal glomeruli, suggesting the integration of the minor pheromone component with plant odors. Overall, we found that PN axons innervating pheromonal and nonpheromonal glomeruli were organized into concentric zones. We then analyzed the dendritic fields of Kenyon cells (KCs), which receive inputs from PNs. Despite the strong regional localization of axons of different PN classes, the dendrites of KCs were less well classified. Finally, we estimated the connectivity between PNs and KCs and suggest that the dendritic field may be organized to receive different amounts of pheromonal and nonpheromonal inputs. PNs for multiple pheromone components and plant odors enter the calyx in a concentric fashion, and they are read out by the elaborate dendritic field of KCs.

Invertebrate learning and cognition: relating phenomena to neural substrate

Diverse invertebrate species have been used for studies of learning and comparative cognition. Although we have gained invaluable information from this, in this study we argue that our approach to comparative learning research is rather deficient. Generally invertebrate learning research has focused mainly on arthropods, and most of that within the Hymenoptera and Diptera. Any true comparative analysis of the distribution of comparative cognitive abilities across phyla is hampered by this bias, and more fundamentally by a reporting bias toward positive results. To understand the limits of learning and cognition for a species, knowing what animals cannot do is at least as important as reporting what they can. Finally, much more effort needs to be focused on the neurobiological analysis of different types of learning to truly understand the differences and similarities of learning types. In this review, we first give a brief overview of the various forms of learning in invertebrates. We also suggest areas where further study is needed for a more comparative understanding of learning. Finally, using what is known of learning in honeybees and the well-studied honeybee brain, we present a model of how various complex forms of learning may be accounted for with the same neural circuitry required for so-called simple learning types. At the neurobiological level, different learning phenomena are unlikely to be independent, and without considering this it is very difficult to correctly interpret the phylogenetic distribution of learning and cognitive abilities. WIREs Cogn Sci 2013, 4:561-582. doi: 10.1002/wcs.1248 For further resources related to this article, please visit the WIREs website.

Linking oscillations in cerebellar circuits

In many neuroscience fields, the study of local and global rhythmicity has been receiving increasing attention. These network influences could directly impact on how neuronal groups interact together, organizing for different contexts. The cerebellar cortex harbors a variety of such local circuit rhythms, from the rhythms in the cerebellar cortex per se, or those dictated from important afferents. We present here certain cerebellar oscillatory phenomena that have been recorded in rodents and primates. Those take place in a range of frequencies: from the more known oscillations in the 4-25 Hz band, such as the olivocerebellar oscillatory activity and the granule cell layer oscillations, to the more recently reported slow (<1 Hz oscillations), and the fast (>150 Hz) activity in the Purkinje cell layer. Many of these oscillations appear spontaneously in the circuits, and are modulated by behavioral imperatives. We review here how those oscillations are recorded, some of their modulatory mechanisms, and also identify some of the cerebellar nodes where they could interact. A particular emphasis has been placed on how these oscillations could be modulated by movement and certain neuropathological manifestations. Many of those oscillations could have a definite impact on the way information is processed in the cerebellum and how it interacts with other structures in a variety of contexts.

Gain control network conditions in early sensory coding

Gain control is essential for the proper function of any sensory system. However, the precise mechanisms for achieving effective gain control in the brain are unknown. Based on our understanding of the existence and strength of connections in the insect olfactory system, we analyze the conditions that lead to controlled gain in a randomly connected network of excitatory and inhibitory neurons. We consider two scenarios for the variation of input into the system. In the first case, the intensity of the sensory input controls the input currents to a fixed proportion of neurons of the excitatory and inhibitory populations. In the second case, increasing intensity of the sensory stimulus will both, recruit an increasing number of neurons that receive input and change the input current that they receive. Using a mean field approximation for the network activity we derive relationships between the parameters of the network that ensure that the overall level of activity of the excitatory population remains unchanged for increasing intensity of the external stimulation. We find that, first, the main parameters that regulate network gain are the probabilities of connections from the inhibitory population to the excitatory population and of the connections within the inhibitory population. Second, we show that strict gain control is not achievable in a random network in the second case, when the input recruits an increasing number of neurons. Finally, we confirm that the gain control conditions derived from the mean field approximation are valid in simulations of firing rate models and Hodgkin-Huxley conductance based models.

Transformation of odor selectivity from projection neurons to single mushroom body neurons mapped with dual-color calcium imaging

Although the response properties of most neurons are, to a large extent, determined by the presynaptic inputs that they receive, comprehensive functional characterization of the presynaptic inputs of a single neuron remains elusive. Toward this goal, we introduce a dual-color calcium imaging approach that simultaneously monitors the responses of a single postsynaptic neuron together with its presynaptic axon terminal inputs in vivo. As a model system, we applied the strategy to the feed-forward connections from the projection neurons (PNs) to the Kenyon cells (KCs) in the mushroom body of Drosophila and functionally mapped essentially all PN inputs for some of the KCs. We found that the output of single KCs could be well predicted by a linear summation of the PN input signals, indicating that excitatory PN inputs play the major role in generating odor-selective responses in KCs. When odors failed to activate KC output, local calcium transients restricted to individual postsynaptic sites could be observed in the KC dendrites. The response amplitudes of the local transients often correlated linearly with the presynaptic response amplitudes, allowing direct assay of the strength of single synaptic sites. Furthermore, we found a scaling relationship between the total number of PN terminals that a single KC received and the average synaptic strength of these PN-KC synapses. Our strategy provides a unique perspective on the process of information transmission and integration in a model neural circuit and may be broadly applicable for the study of the origin of neuronal response properties.

Odor-specific, olfactory marker protein-mediated sparsening of primary olfactory input to the brain after odor exposure

Long-term plasticity in sensory systems is usually conceptualized as changing the interpretation of the brain of sensory information, not an alteration of how the sensor itself responds to external stimuli. However, here we demonstrate that, in the adult mouse olfactory system, a 1-week-long exposure to an artificially odorized environment narrows the range of odorants that can induce neurotransmitter release from olfactory sensory neurons (OSNs) and reduces the total transmitter release from responsive neurons. In animals heterozygous for the olfactory marker protein (OMP), this adaptive plasticity was strongest in the populations of OSNs that originally responded to the exposure odorant (an ester) and also observed in the responses to a similar odorant (another ester) but had no effect on the responses to odorants dissimilar to the exposure odorant (a ketone and an aldehyde). In contrast, in OMP knock-out mice, odorant exposure reduced the number and amplitude of OSN responses evoked by all four types of odorants equally. The effect of this plasticity is to preferentially sparsen the primary neural representations of common olfactory stimuli, which has the computational benefit of increasing the number of distinct sensory patterns that could be represented in the circuit and might thus underlie the improvements in olfactory discrimination often observed after odorant exposure (Mandairon et al., 2006a). The absence of odorant specificity in this adaptive plasticity in OMP knock-out mice suggests a potential role for this protein in adaptively reshaping OSN responses to function in different environments.

Neuronal computations in the olfactory system of zebrafish

The main olfactory system encodes information about molecules in a combinatorial fashion by distributed spatiotemporal activity patterns. As activity propagates from sensory neurons to the olfactory bulb and to higher brain areas, odor information is processed by multiple transformations of these activity patterns. This review discusses neuronal computations associated with such transformations in the olfactory system of zebrafish, a small vertebrate that offers advantages for the quantitative analysis and manipulation of neuronal activity in the intact brain. The review focuses on pattern decorrelation in the olfactory bulb and on the readout of multiplexed sensory representations in the telencephalic area Dp, the homolog of the olfactory cortex. These computations are difficult to study in larger species and may provide insights into general information-processing strategies in the brain.

Millisecond stimulus onset-asynchrony enhances information about components in an odor mixture

Airborne odorants rarely occur as pure, isolated stimuli. In a natural environment, odorants that intermingle from multiple sources create mixtures in which the onset and offset of odor components are asynchronous. Odor mixtures are known to elicit interactions in both behavioral and physiological responses, changing the perceptive quality of mixtures compared with the components. However, relevant odors need to be segregated from a distractive background. Honeybees (Apis mellifera) can use stimulus onset asynchrony of as little as 6 ms to segregate learned odor components within a mixture. Using in vivo calcium imaging of projection neurons in the honeybee, we studied neuronal mechanisms of odor-background segregation based on stimulus onset asynchrony in the antennal lobe. We found that asynchronous mixtures elicit response patterns that are different from their synchronous counterpart: the responses to asynchronous mixtures contain more information about the constituent components. With longer onset shifts, more features of the components were present in the mixture response patterns. Moreover, we found that the processing of asynchronous mixtures activated more inhibitory interactions than the processing of synchronous mixtures. This study provides evidence of neuronal mechanisms that underlie odor-object segregation on a timescale much faster than found for mammals.

A computational framework for understanding decision making through integration of basic learning rules

Nonassociative and associative learning rules simultaneously modify neural circuits. However, it remains unclear how these forms of plasticity interact to produce conditioned responses. Here we integrate nonassociative and associative conditioning within a uniform model of olfactory learning in the honeybee. Honeybees show a fairly abrupt increase in response after a number of conditioning trials. The occurrence of this abrupt change takes many more trials after exposure to nonassociative trials than just using associative conditioning. We found that the interaction of unsupervised and supervised learning rules is critical for explaining latent inhibition phenomenon. Associative conditioning combined with the mutual inhibition between the output neurons produces an abrupt increase in performance despite smooth changes of the synaptic weights. The results show that an integrated set of learning rules implemented using fan-out connectivities together with neural inhibition can explain the broad range of experimental data on learning behaviors.

Olfactory cortical neurons read out a relative time code in the olfactory bulb

Odor stimulation evokes complex spatiotemporal activity in the olfactory bulb, suggesting that the identity of activated neurons as well as the timing of their activity convey information about odors. However, whether and how downstream neurons decipher these temporal patterns remains debated. We addressed this question by measuring the spiking activity of downstream neurons while optogenetically stimulating two foci in the olfactory bulb with varying relative timing in mice. We found that the overall spike rates of piriform cortex neurons were sensitive to the relative timing of activation. Posterior piriform cortex neurons showed higher sensitivity to relative input times than neurons in the anterior piriform cortex. In contrast, olfactory bulb neurons rarely showed such sensitivity. Thus, the brain can transform a relative time code in the periphery into a firing-rate-based representation in central brain areas, providing evidence for the relevance of relative time-based code in the olfactory bulb.

Population coding is essential for rapid information processing in the moth antennal lobe

We investigated how odorant information is transmitted by neurons in the moth antennal lobe (AL). The neurons were repeatedly stimulated by three different odorants and their activity was intracellularly recorded. First, the response properties of single neurons were analyzed. The neurons exhibited highly reliable responses to the odorants and 43% of AL neurons responded to two or three odorants. The population distribution of firing rates in response to odorant stimulation was relatively broad in moth AL neurons, which is consistent across insects. Second, we attempted to decode the odorant identity from the activity of the recorded neurons using the maximum likelihood method. The decoding performance rapidly improves with increasing the number of neurons. Notably, an increase in the size of neural population results in faster transfer of information and increased the duration to retain odorant information. In conclusion, the AL neurons encode odorant information reliably and the population coding can transmit odorant information to olfactory centers. Population coding allows AL to encode and transmit olfactory information faster than the discrimination latency demonstrated in behavioral experiments. This article is part of a Special Issue entitled Neural Coding 2012.

Mixture and odorant processing in the olfactory systems of insects: a comparative perspective

Natural olfactory stimuli are often complex mixtures of volatiles, of which the identities and ratios of constituents are important for odor-mediated behaviors. Despite this importance, the mechanism by which the olfactory system processes this complex information remains an area of active study. In this review, we describe recent progress in how odorants and mixtures are processed in the brain of insects. We use a comparative approach toward contrasting olfactory coding and the behavioral efficacy of mixtures in different insect species, and organize these topics around four sections: (1) Examples of the behavioral efficacy of odor mixtures and the olfactory environment; (2) mixture processing in the periphery; (3) mixture coding in the antennal lobe; and (4) evolutionary implications and adaptations for olfactory processing. We also include pertinent background information about the processing of individual odorants and comparative differences in wiring and anatomy, as these topics have been richly investigated and inform the processing of mixtures in the insect olfactory system. Finally, we describe exciting studies that have begun to elucidate the role of the processing of complex olfactory information in evolution and speciation.

Coding of odors by temporal binding within a model network of the locust antennal lobe

The locust olfactory system interfaces with the external world through antennal receptor neurons (ORNs), which represent odors in a distributed, combinatorial manner. ORN axons bundle together to form the antennal nerve, which relays sensory information centrally to the antennal lobe (AL). Within the AL, an odor generates a dynamically evolving ensemble of active cells, leading to a stimulus-specific temporal progression of neuronal spiking. This experimental observation has led to the hypothesis that an odor is encoded within the AL by a dynamically evolving trajectory of projection neuron (PN) activity that can be decoded piecewise to ascertain odor identity. In order to study information coding within the locust AL, we developed a scaled-down model of the locust AL using Hodgkin-Huxley-type neurons and biologically realistic connectivity parameters and current components. Using our model, we examined correlations in the precise timing of spikes across multiple neurons, and our results suggest an alternative to the dynamic trajectory hypothesis. We propose that the dynamical interplay of fast and slow inhibition within the locust AL induces temporally stable correlations in the spiking activity of an odor-dependent neural subset, giving rise to a temporal binding code that allows rapid stimulus detection by downstream elements.

Parallel processing in the honeybee olfactory pathway: structure, function, and evolution

Animals face highly complex and dynamic olfactory stimuli in their natural environments, which require fast and reliable olfactory processing. Parallel processing is a common principle of sensory systems supporting this task, for example in visual and auditory systems, but its role in olfaction remained unclear. Studies in the honeybee focused on a dual olfactory pathway. Two sets of projection neurons connect glomeruli in two antennal-lobe hemilobes via lateral and medial tracts in opposite sequence with the mushroom bodies and lateral horn. Comparative studies suggest that this dual-tract circuit represents a unique adaptation in Hymenoptera. Imaging studies indicate that glomeruli in both hemilobes receive redundant sensory input. Recent simultaneous multi-unit recordings from projection neurons of both tracts revealed widely overlapping response profiles strongly indicating parallel olfactory processing. Whereas lateral-tract neurons respond fast with broad (generalistic) profiles, medial-tract neurons are odorant specific and respond slower. In analogy to “what-” and “where” subsystems in visual pathways, this suggests two parallel olfactory subsystems providing “what-” (quality) and “when” (temporal) information. Temporal response properties may support across-tract coincidence coding in higher centers. Parallel olfactory processing likely enhances perception of complex odorant mixtures to decode the diverse and dynamic olfactory world of a social insect.

Selective and efficient neural coding of communication signals depends on early acoustic and social environment

Previous research has shown that postnatal exposure to simple, synthetic sounds can affect the sound representation in the auditory cortex as reflected by changes in the tonotopic map or other relatively simple tuning properties, such as AM tuning. However, their functional implications for neural processing in the generation of ethologically-based perception remain unexplored. Here we examined the effects of noise-rearing and social isolation on the neural processing of communication sounds such as species-specific song, in the primary auditory cortex analog of adult zebra finches. Our electrophysiological recordings reveal that neural tuning to simple frequency-based synthetic sounds is initially established in all the laminae independent of patterned acoustic experience; however, we provide the first evidence that early exposure to patterned sound statistics, such as those found in native sounds, is required for the subsequent emergence of neural selectivity for complex vocalizations and for shaping neural spiking precision in superficial and deep cortical laminae, and for creating efficient neural representations of song and a less redundant ensemble code in all the laminae. Our study also provides the first causal evidence for ‘sparse coding’, such that when the statistics of the stimuli were changed during rearing, as in noise-rearing, that the sparse or optimal representation for species-specific vocalizations disappeared. Taken together, these results imply that a layer-specific differential development of the auditory cortex requires patterned acoustic input, and a specialized and robust sensory representation of complex communication sounds in the auditory cortex requires a rich acoustic and social environment.

Perceptual decision making "through the eyes" of a large-scale neural model of v1

Sparse coding has been posited as an efficient information processing strategy employed by sensory systems, particularly visual cortex. Substantial theoretical and experimental work has focused on the issue of sparse encoding, namely how the early visual system maps the scene into a sparse representation. In this paper we investigate the complementary issue of sparse decoding, for example given activity generated by a realistic mapping of the visual scene to neuronal spike trains, how do downstream neurons best utilize this representation to generate a “decision.” Specifically we consider both sparse (L1-regularized) and non-sparse (L2 regularized) linear decoding for mapping the neural dynamics of a large-scale spiking neuron model of primary visual cortex (V1) to a two alternative forced choice (2-AFC) perceptual decision. We show that while both sparse and non-sparse linear decoding yield discrimination results quantitatively consistent with human psychophysics, sparse linear decoding is more efficient in terms of the number of selected informative dimension.

Organization of antennal lobe-associated neurons in adult Drosophila melanogaster brain

The primary olfactory centers of both vertebrates and insects are characterized by glomerular structure. Each glomerulus receives sensory input from a specific type of olfactory sensory neurons, creating a topographic map of the odor quality. The primary olfactory center is also innervated by various types of neurons such as local neurons, output projection neurons (PNs), and centrifugal neurons from higher brain regions. Although recent studies have revealed how olfactory sensory input is conveyed to each glomerulus, it still remains unclear how the information is integrated and conveyed to other brain areas. By using the GAL4 enhancer-trap system, we conducted a systematic mapping of the neurons associated with the primary olfactory center of Drosophila, the antennal lobe (AL). We identified in total 29 types of neurons, among which 13 are newly identified in the present study. Analyses of arborizations of these neurons in the AL revealed how glomeruli are linked with each other, how different PNs link these glomeruli with multiple secondary sites, and how these secondary sites are organized by the projections of the AL-associated neurons.

Parallel processing via a dual olfactory pathway in the honeybee

In their natural environment, animals face complex and highly dynamic olfactory input. Thus vertebrates as well as invertebrates require fast and reliable processing of olfactory information. Parallel processing has been shown to improve processing speed and power in other sensory systems and is characterized by extraction of different stimulus parameters along parallel sensory information streams. Honeybees possess an elaborate olfactory system with unique neuronal architecture: a dual olfactory pathway comprising a medial projection-neuron (PN) antennal lobe (AL) protocerebral output tract (m-APT) and a lateral PN AL output tract (l-APT) connecting the olfactory lobes with higher-order brain centers. We asked whether this neuronal architecture serves parallel processing and employed a novel technique for simultaneous multiunit recordings from both tracts. The results revealed response profiles from a high number of PNs of both tracts to floral, pheromonal, and biologically relevant odor mixtures tested over multiple trials. PNs from both tracts responded to all tested odors, but with different characteristics indicating parallel processing of similar odors. Both PN tracts were activated by widely overlapping response profiles, which is a requirement for parallel processing. The l-APT PNs had broad response profiles suggesting generalized coding properties, whereas the responses of m-APT PNs were comparatively weaker and less frequent, indicating higher odor specificity. Comparison of response latencies within and across tracts revealed odor-dependent latencies. We suggest that parallel processing via the honeybee dual olfactory pathway provides enhanced odor processing capabilities serving sophisticated odor perception and olfactory demands associated with a complex olfactory world of this social insect.

Caffeine in floral nectar enhances a pollinator's memory of reward

Plant defense compounds occur in floral nectar, but their ecological role is not well understood. We provide evidence that plant compounds pharmacologically alter pollinator behavior by enhancing their memory of reward. Honeybees rewarded with caffeine, which occurs naturally in nectar of Coffea and Citrus species, were three times as likely to remember a learned floral scent as were honeybees rewarded with sucrose alone. Caffeine potentiated responses of mushroom body neurons involved in olfactory learning and memory by acting as an adenosine receptor antagonist. Caffeine concentrations in nectar did not exceed the bees' bitter taste threshold, implying that pollinators impose selection for nectar that is pharmacologically active but not repellent. By using a drug to enhance memories of reward, plants secure pollinator fidelity and improve reproductive success.

Suppression of inhibitory GABAergic transmission by cAMP signaling pathway: alterations in learning and memory mutants

The cAMP signaling pathway mediates synaptic plasticity and is essential for memory formation in both vertebrates and invertebrates. In the fruit fly Drosophila melanogaster, mutations in the cAMP pathway lead to impaired olfactory learning. These mutant genes are preferentially expressed in the mushroom body (MB), an anatomical structure essential for learning. While cAMP-mediated synaptic plasticity is known to be involved in facilitation at the excitatory synapses, little is known about its function in GABAergic synaptic plasticity and learning. In this study, using whole-cell patch-clamp techniques on Drosophila primary neuronal cultures, we demonstrate that focal application of an adenylate cyclase activator forskolin (FSK) suppressed inhibitory GABAergic postsynaptic currents (IPSCs). We observed a dual regulatory role of FSK on GABAergic transmission, where it increases overall excitability at GABAergic synapses, while simultaneously acting on postsynaptic GABA receptors to suppress GABAergic IPSCs. Further, we show that cAMP decreased GABAergic IPSCs in a PKA-dependent manner through a postsynaptic mechanism. PKA acts through the modulation of ionotropic GABA receptor sensitivity to the neurotransmitter GABA. This regulation of GABAergic IPSCs is altered in the cAMP pathway and short-term memory mutants dunce and rutabaga, with both showing altered GABA receptor sensitivity. Interestingly, this effect is also conserved in the MB neurons of both these mutants. Thus, our study suggests that alterations in cAMP-mediated GABAergic plasticity, particularly in the MB neurons of cAMP mutants, account for their defects in olfactory learning.

Multi-unit recording methods to characterize neural activity in the locust (Schistocerca americana) olfactory circuits

Detection and interpretation of olfactory cues are critical for the survival of many organisms. Remarkably, species across phyla have strikingly similar olfactory systems suggesting that the biological approach to chemical sensing has been optimized over evolutionary time. In the insect olfactory system, odorants are transduced by olfactory receptor neurons (ORN) in the antenna, which convert chemical stimuli into trains of action potentials. Sensory input from the ORNs is then relayed to the antennal lobe (AL; a structure analogous to the vertebrate olfactory bulb). In the AL, neural representations for odors take the form of spatiotemporal firing patterns distributed across ensembles of principal neurons (PNs; also referred to as projection neurons). The AL output is subsequently processed by Kenyon cells (KCs) in the downstream mushroom body (MB), a structure associated with olfactory memory and learning. Here, we present electrophysiological recording techniques to monitor odor-evoked neural responses in these olfactory circuits. First, we present a single sensillum recording method to study odor-evoked responses at the level of populations of ORNs. We discuss the use of saline filled sharpened glass pipettes as electrodes to extracellularly monitor ORN responses. Next, we present a method to extracellularly monitor PN responses using a commercial 16-channel electrode. A similar approach using a custom-made 8-channel twisted wire tetrode is demonstrated for Kenyon cell recordings. We provide details of our experimental setup and present representative recording traces for each of these techniques.

Illuminating vertebrate olfactory processing

The olfactory system encodes information about molecules by spatiotemporal patterns of activity across distributed populations of neurons and extracts information from these patterns to control specific behaviors. Recent studies used in vivo recordings, optogenetics, and other methods to analyze the mechanisms by which odor information is encoded and processed in the olfactory system, the functional connectivity within and between olfactory brain areas, and the impact of spatiotemporal patterning of neuronal activity on higher-order neurons and behavioral outputs. The results give rise to a faceted picture of olfactory processing and provide insights into fundamental mechanisms underlying neuronal computations. This review focuses on some of this work presented in a Mini-Symposium at the Annual Meeting of the Society for Neuroscience in 2012.

Network architecture underlying maximal separation of neuronal representations

One of the most basic and general tasks faced by all nervous systems is extracting relevant information from the organism's surrounding world. While physical signals available to sensory systems are often continuous, variable, overlapping, and noisy, high-level neuronal representations used for decision-making tend to be discrete, specific, invariant, and highly separable. This study addresses the question of how neuronal specificity is generated. Inspired by experimental findings on network architecture in the olfactory system of the locust, I construct a highly simplified theoretical framework which allows for analytic solution of its key properties. For generalized feed-forward systems, I show that an intermediate range of connectivity values between source- and target-populations leads to a combinatorial explosion of wiring possibilities, resulting in input spaces which are, by their very nature, exquisitely sparsely populated. In particular, connection probability ½, as found in the locust antennal-lobe-mushroom-body circuit, serves to maximize separation of neuronal representations across the target Kenyon cells (KCs), and explains their specific and reliable responses. This analysis yields a function expressing response specificity in terms of lower network parameters; together with appropriate gain control this leads to a simple neuronal algorithm for generating arbitrarily sparse and selective codes and linking network architecture and neural coding. I suggest a straightforward way to construct ecologically meaningful representations from this code.

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.

Neuronal organization of the hemiellipsoid body of the land hermit crab, Coenobita clypeatus: correspondence with the mushroom body ground pattern

Malacostracan crustaceans and dicondylic insects possess large second-order olfactory neuropils called, respectively, hemiellipsoid bodies and mushroom bodies. Because these centers look very different in the two groups of arthropods, it has been debated whether these second-order sensory neuropils are homologous or whether they have evolved independently. Here we describe the results of neuroanatomical observations and experiments that resolve the neuronal organization of the hemiellipsoid body in the terrestrial Caribbean hermit crab, Coenobita clypeatus, and compare this organization with the mushroom body of an insect, the cockroach Periplaneta americana. Comparisons of the morphology, ultrastructure, and immunoreactivity of the hemiellipsoid body of C. clypeatus and the mushroom body of the cockroach P. americana reveal in both a layered motif provided by rectilinear arrangements of extrinsic and intrinsic neurons as well as a microglomerular organization. Furthermore, antibodies raised against DC0, the major catalytic subunit of protein kinase A, specifically label both the crustacean hemiellipsoid bodies and insect mushroom bodies. In crustaceans lacking eyestalks, where the entire brain is contained within the head, this antibody selectively labels hemiellipsoid bodies, the superior part of which approximates a mushroom body's calyx in having large numbers of microglomeruli. We propose that these multiple correspondences indicate homology of the crustacean hemiellipsoid body and insect mushroom body and discuss the implications of this with respect to the phylogenetic history of arthropods. We conclude that crustaceans, insects, and other groups of arthropods share an ancestral neuronal ground pattern that is specific to their second-order olfactory centers.

Efficient "communication through coherence" requires oscillations structured to minimize interference between signals

The ‘communication through coherence’ (CTC) hypothesis proposes that selective communication among neural networks is achieved by coherence between firing rate oscillation in a sending region and gain modulation in a receiving region. Although this hypothesis has stimulated extensive work, it remains unclear whether the mechanism can in principle allow reliable and selective information transfer. Here we use a simple mathematical model to investigate how accurately coherent gain modulation can filter a population-coded target signal from task-irrelevant distracting inputs. We show that selective communication can indeed be achieved, although the structure of oscillatory activity in the target and distracting networks must satisfy certain previously unrecognized constraints. Firstly, the target input must be differentiated from distractors by the amplitude, phase or frequency of its oscillatory modulation. When distracting inputs oscillate incoherently in the same frequency band as the target, communication accuracy is severely degraded because of varying overlap between the firing rate oscillations of distracting inputs and the gain modulation in the receiving region. Secondly, the oscillatory modulation of the target input must be strong in order to achieve a high signal-to-noise ratio relative to stochastic spiking of individual neurons. Thus, whilst providing a quantitative demonstration of the power of coherent oscillatory gain modulation to flexibly control information flow, our results identify constraints imposed by the need to avoid interference between signals, and reveal a likely organizing principle for the structure of neural oscillations in the brain.

Distributed regions of mammalian brains transiently engage in coherent oscillations, often at specific stages of behavioral or cognitive tasks. This activity may play a role in controlling information flow among connected regions, allowing the brain's connectivity structure to be flexibly reconfigured in response to changing task demands. We have used a computational model to investigate the conditions under which oscillations can generate selective communication through a mechanism in which the excitability of neurons in one region is modulated coherently with a firing rate oscillation in another region. Our results demonstrate that this mechanism is able to accurately and selectively control the flow of signals encoded as spatial patterns of firing rate. However, we found that the requirement to avoid interference between different signals imposes previously unrecognised constraints on the structures of oscillatory activity that can efficiently support this mechanism. These constraints may be an organizing principle for the structured oscillatory activity observed in vivo.

Long-term enhancement of synaptic transmission between antennal lobe and mushroom body in cultured Drosophila brain

In Drosophila, the mushroom body (MB) is a critical brain structure for olfactory associative learning. During aversive conditioning, the MBs are thought to associate odour signals, conveyed by projection neurons (PNs) from the antennal lobe (AL), with shock signals conveyed through ascending fibres of the ventral nerve cord (AFV). Although synaptic transmission between AL and MB might play a crucial role for olfactory associative learning, its physiological properties have not been examined directly. Using a cultured Drosophila brain expressing a Ca(2+) indicator in the MBs, we investigated synaptic transmission and plasticity at the AL-MB synapse. Following stimulation with a glass micro-electrode, AL-induced Ca(2+) responses in the MBs were mediated through Drosophila nicotinic acetylcholine receptors (dnAChRs), while AFV-induced Ca(2+) responses were mediated through Drosophila NMDA receptors (dNRs). AL-MB synaptic transmission was enhanced more than 2 h after the simultaneous 'associative-stimulation' of AL and AFV, and such long-term enhancement (LTE) was specifically formed at the AL-MB synapses but not at the AFV-MB synapses. AL-MB LTE was not induced by intense stimulation of the AL alone, and the LTE decays within 60 min after subsequent repetitive AL stimulation. These phenotypes of associativity, input specificity and persistence of AL-MB LTE are highly reminiscent of olfactory memory. Furthermore, similar to olfactory aversive memory, AL-MB LTE formation required activation of the Drosophila D1 dopamine receptor, DopR, along with dnAChR and dNR during associative stimulations. These physiological and genetic analogies indicate that AL-MB LTE might be a relevant cellular model for olfactory memory.

Activity in Neurons of a Putative Protocerebral Circuit Representing Information about a 10 Component Plant Odor Blend in Heliothis virescens

The olfactory pathway in the insect brain is anatomically well described from the antennal lobe (AL) to the mushroom bodies and the lateral protocerebrum (LP) in several species. Less is known about the further connections of the olfactory network in protocerebrum and how information about relevant plant odorants and mixtures are represented in this network, resulting in output information mediated by descending neurons. In the present study we have recorded intracellularly followed by dye injections from neurons in the LP and superior protocerebrum (SP) of the moth, Heliothis virescens. As relevant stimuli, we have used selected primary plant odorants and mixtures of them. The results provide the morphology and physiological responses of neurons involved in a putative circuit connecting the mushroom body lobes, the SP, and the LP, as well as input to SP and LP by one multiglomerular AL neuron and output from the LP by one descending neuron. All neurons responded to a particular mixture of ten primary plant odorants, some of them also to single odorants of the mixture. Altogether, the physiological data indicate integration in protocerebral neurons of information from several of the receptor neuron types functionally described in this species.

Functional analysis of a higher olfactory center, the lateral horn

The lateral horn (LH) of the insect brain is thought to play several important roles in olfaction, including maintaining the sparseness of responses to odors by means of feedforward inhibition, and encoding preferences for innately meaningful odors. Yet relatively little is known of the structure and function of LH neurons (LHNs), making it difficult to evaluate these ideas. Here we surveyed >250 LHNs in locusts using intracellular recordings to characterize their responses to sensory stimuli, dye-fills to characterize their morphologies, and immunostaining to characterize their neurotransmitters. We found a great diversity of LHNs, suggesting this area may play multiple roles. Yet, surprisingly, we found no evidence to support a role for these neurons in the feedforward inhibition proposed to mediate olfactory response sparsening; instead, it appears that another mechanism, feedback inhibition from the giant GABAergic neuron, serves this function. Further, all LHNs we observed responded to all odors we tested, making it unlikely these LHNs serve as labeled lines mediating specific behavioral responses to specific odors. Our results rather point to three other possible roles of LHNs: extracting general stimulus features such as odor intensity; mediating bilateral integration of sensory information; and integrating multimodal sensory stimuli.

Odor representations in olfactory cortex: distributed rate coding and decorrelated population activity

VIDEO ABSTRACT

How information encoded in neuronal spike trains is used to guide sensory decisions is a fundamental question. In olfaction, a single sniff is sufficient for fine odor discrimination but the neural representations on which olfactory decisions are based are unclear. Here, we recorded neural ensemble activity in the anterior piriform cortex (aPC) of rats performing an odor mixture categorization task. We show that odors evoke transient bursts locked to sniff onset and that odor identity can be better decoded using burst spike counts than by spike latencies or temporal patterns. Surprisingly, aPC ensembles also exhibited near-zero noise correlations during odor stimulation. Consequently, fewer than 100 aPC neurons provided sufficient information to account for behavioral speed and accuracy, suggesting that behavioral performance limits arise downstream of aPC. These findings demonstrate profound transformations in the dynamics of odor representations from the olfactory bulb to cortex and reveal likely substrates for odor-guided decisions.

Plant odour stimuli reshape pheromonal representation in neurons of the antennal lobe macroglomerular complex of a male moth

Male moths are confronted with complex odour mixtures in a natural environment when flying towards a female-emitted sex pheromone source. Whereas synergistic effects of sex pheromones and plant odours have been observed at the behavioural level, most investigations at the peripheral level have shown an inhibition of pheromone responses by plant volatiles, suggesting a potential role of the central nervous system in reshaping the peripheral information. We thus investigated the interactions between sex pheromone and a behaviourally active plant volatile, heptanal, and their effects on responses of neurons in the pheromone-processing centre of the antennal lobe, the macroglomerular complex, in the moth Agrotis ipsilon. Our results show that most of these pheromone-sensitive neurons responded to the plant odour. Most neurons responded to the pheromone with a multiphasic pattern and were anatomically identified as projection neurons. They responded either with excitation or pure inhibition to heptanal, and the response to the mixture pheromone + heptanal was generally weaker than to the pheromone alone, showing a suppressive effect of heptanal. However, these neurons responded with a better resolution to pulsed stimuli. The other neurons with either purely excitatory or inhibitory responses to all three stimuli did not exhibit significant differences in responses between stimuli. Although the suppression of the pheromone responses in AL neurons by the plant odour is counter-intuitive at first glance, the observed better resolution of pulsed stimuli is probably more important than high sensitivity to the localization of a calling female.

Olfactory coding: tagging and tuning odor-activated synapses for memory

A recent study in the locust olfactory system shows how neuromodulators can alter the rules of synaptic plasticity to form associative memories through the use of 'tagged' synapses.

Spatio-temporal activity patterns of odor-induced synchronized potentials revealed by voltage-sensitive dye imaging and intracellular recording in the antennal lobe of the cockroach

In animals, odor qualities are represented as both spatial activity patterns of glomeruli and temporal patterns of synchronized oscillatory signals in the primary olfactory centers. By optical imaging of a voltage-sensitive dye (VSD) and intracellular recording from secondary olfactory interneurons, we examined possible neural correlates of the spatial and temporal odor representations in the primary olfactory center, the antennal lobe (AL), of the cockroach Periplaneta americana. Voltage-sensitive dye imaging revealed that all used odorants induced odor-specific temporal patterns of depolarizing potentials in specific combinations of anterior glomeruli of the AL. The depolarizing potentials evoked by different odorants were temporally synchronized across glomeruli and were termed "synchronized potentials." These observations suggest that odor qualities are represented by spatio-temporal activity patterns of the synchronized potentials across glomeruli. We also performed intracellular recordings and stainings from secondary olfactory interneurons, namely projection neurons and local interneurons. We analyzed the temporal structures of enanthic acid-induced action potentials of secondary olfactory interneurons using simultaneous paired intracellular recording from two given neurons. Our results indicated that the multiple local interneurons synchronously fired in response to the olfactory stimulus. In addition, all stained enanthic acid-responsive projection neurons exhibited dendritic arborizations within the glomeruli where the synchronized potentials were evoked. Since multiple local interneurons are known to synapse to a projection neuron in each glomerulus in the cockroach AL, converging inputs from local interneurons to the projection neurons appear to contribute the odorant specific spatio-temporal activity patterns of the synchronized potentials.

Concept cells: the building blocks of declarative memory functions

Intracranial recordings in subjects suffering from intractable epilepsy - made during their evaluation for an eventual surgical removal of the epileptic focus - have allowed the extraordinary opportunity to study the firing of multiple single neurons in awake and behaving human subjects. These studies have shown that neurons in the human medial temporal lobe respond in a remarkably selective and abstract manner to particular persons or objects, such as Jennifer Aniston, Luke Skywalker or the Tower of Pisa. These neurons have been named 'Jennifer Aniston neurons' or, more recently, 'concept cells'. I argue that the sparse, explicit and abstract representation of these neurons is crucial for memory functions, such as the creation of associations and the transition between related concepts that leads to episodic memories and the flow of consciousness.

Long-term memory and response generalization in mushroom body extrinsic neurons in the honeybee Apis mellifera

Honeybees learn to associate an odor with sucrose reward under conditions that allow the monitoring of neural activity by imaging Ca(2+) transients in morphologically identified neurons. Here we report such recordings from mushroom body extrinsic neurons - which belong to a recurrent tract connecting the output of the mushroom body with its input, potentially providing inhibitory feedback - and other extrinsic neurons. The neurons' responses to the learned odor and two novel control odors were measured 24 h after learning. We found that calcium responses to the learned odor and an odor that was strongly generalized with it were enhanced compared with responses to a weakly generalized control. Thus, the physiological responses measured in these extrinsic neurons accurately reflect what is observed in behavior. We conclude that the recorded recurrent neurons feed information back to the mushroom body about the features of learned odor stimuli. Other extrinsic neurons may signal information about learned odors to different brain regions.