A computational model of the response of honey bee antennal lobe circuitry to odor mixtures: overshadowing, blocking and unblocking can arise from lateral inhibition

Plasticity in inhibitory networks improves pattern separation in early olfactory processing

Distinguishing between nectar and non-nectar odors is challenging for animals due to shared compounds and changing ratios in complex mixtures. Changes in nectar production throughout the day and potentially many times within a forager's lifetime add to the complexity. The honeybee olfactory system, containing less than 1000 principal neurons in the early olfactory relay, the antennal lobe (AL), must learn to associate diverse volatile blends with rewards. Previous studies identified plasticity between AL neurons but its role in odor learning remains poorly understood. We used a computational network model and live imaging of the honeybee's AL to explore the neural mechanisms and functions of plasticity in the early olfactory system. Our findings revealed that when trained with a set of rewarded and unrewarded odors, the AL inhibitory network suppresses shared chemical compounds while enhancing responses to distinct compounds. This results in improved pattern separation and a more concise neural code. Our Calcium imaging data support these predictions. Analysis of a Graph Convolutional Network in machine learning performing an odor categorization task revealed a similar mechanism of contrast enhancement. Our model provides insights into how inhibitory plasticity in the early olfactory network reshapes coding for efficient learning of complex odors.

Significance Statement

By combining computational modeling, machine learning, and analysis of calcium imaging data, we demonstrate that associative and non-associative plasticity in the honeybee antennal lobe (AL) - first relay of the insect olfactory system - work together to enhance the contrast between rewarded and unrewarded odors. Training the AL's inhibitory network within specific odor environments enables the suppression of neural responses to common odor components, while amplifying responses to distinctive ones. This study sheds light on the olfactory system's ability to adapt and efficiently learn new odor-reward associations across varying environments, and it proposes innovative, energy-efficient principles applicable to artificial intelligence.

Geosmin suppresses defensive behaviour and elicits unusual neural responses in honey bees

Geosmin is an odorant produced by bacteria in moist soil. It has been found to be extraordinarily relevant to some insects, but the reasons for this are not yet fully understood. Here we report the first tests of the effect of geosmin on honey bees. A stinging assay showed that the defensive behaviour elicited by the bee's alarm pheromone component isoamyl acetate (IAA) is strongly suppressed by geosmin. Surprisingly, the suppression is, however, only present at very low geosmin concentrations, and disappears at higher concentrations. We investigated the underlying mechanisms at the level of the olfactory receptor neurons by means of electroantennography, finding the responses to mixtures of geosmin and IAA to be lower than to pure IAA, suggesting an interaction of both compounds at the olfactory receptor level. Calcium imaging of the antennal lobe (AL) revealed that neuronal responses to geosmin decreased with increasing concentration, correlating well with the observed behaviour. Computational modelling of odour transduction and coding in the AL suggests that a broader activation of olfactory receptor types by geosmin in combination with lateral inhibition could lead to the observed non-monotonic increasing-decreasing responses to geosmin and thus underlie the specificity of the behavioural response to low geosmin concentrations.

Non-synaptic interactions between olfactory receptor neurons, a possible key feature of odor processing in flies

When flies explore their environment, they encounter odors in complex, highly intermittent plumes. To navigate a plume and, for example, find food, they must solve several challenges, including reliably identifying mixtures of odorants and their intensities, and discriminating odorant mixtures emanating from a single source from odorants emitted from separate sources and just mixing in the air. Lateral inhibition in the antennal lobe is commonly understood to help solving these challenges. With a computational model of the Drosophila olfactory system, we analyze the utility of an alternative mechanism for solving them: Non-synaptic ("ephaptic") interactions (NSIs) between olfactory receptor neurons that are stereotypically co-housed in the same sensilla. We find that NSIs improve mixture ratio detection and plume structure sensing and do so more efficiently than the traditionally considered mechanism of lateral inhibition in the antennal lobe. The best performance is achieved when both mechanisms work in synergy. However, we also found that NSIs decrease the dynamic range of co-housed ORNs, especially when they have similar sensitivity to an odorant. These results shed light, from a functional perspective, on the role of NSIs, which are normally avoided between neurons, for instance by myelination.

Non-synaptic interactions between olfactory receptor neurons, a possible key feature of odor processing in flies.. [DOI: 10.1101/2020.07.23.217216]

When flies explore their environment, they encounter odors in complex, highly intermittent plumes. To navigate a plume and, for example, find food, they must solve several challenges, including reliably identifying mixtures of odorants and their intensities, and discriminating odorant mixtures emanating from a single source from odorants emitted from separate sources and just mixing in the air. Lateral inhibition in the antennal lobe is commonly understood to help solving these challenges. With a computational model of the Drosophila olfactory system, we analyze the utility of an alternative mechanism for solving them: Non-synaptic (“ephaptic”) interactions (NSIs) between olfactory receptor neurons that are stereotypically co-housed in the same sensilla.

We found that NSIs improve mixture ratio detection and plume structure sensing and they do so more efficiently than the traditionally considered mechanism of lateral inhibition in the antennal lobe. However, we also found that NSIs decrease the dynamic range of co-housed ORNs, especially when they have similar sensitivity to an odorant. These results shed light, from a functional perspective, on the role of NSIs, which are normally avoided between neurons, for instance by myelination.

Author summary

Myelin is important to isolate neurons and avoid disruptive electrical interference between them; it can be found in almost any neural assembly. However, there are a few exceptions to this rule and it remains unclear why. One particularly interesting case is the electrical interaction between olfactory sensory neurons co-housed in the sensilla of insects. Here, we created a computational model of the early stages of the Drosophila olfactory system and observed that the electrical interference between olfactory receptor neurons can be a useful trait that can help flies, and other insects, to navigate the complex plumes of odorants in their natural environment.

With the model we were able to shed new light on the trade-off of adopting this mechanism: We found that the non-synaptic interactions (NSIs) improve both the identification of the concentration ratio in mixtures of odorants and the discrimination of odorant mixtures emanating from a single source from odorants emitted from separate sources – both highly advantageous. However, they also decrease the dynamic range of the olfactory sensory neurons – a clear disadvantage.

Comparative study of chemical neuroanatomy of the olfactory neuropil in mouse, honey bee, and human

Despite divergent evolutionary origins, the organization of olfactory systems is remarkably similar across phyla. In both insects and mammals, sensory input from receptor cells is initially processed in synaptically dense regions of neuropil called glomeruli, where neural activity is shaped by local inhibition and centrifugal neuromodulation prior to being sent to higher-order brain areas by projection neurons. Here we review both similarities and several key differences in the neuroanatomy of the olfactory system in honey bees, mice, and humans, using a combination of literature review and new primary data. We have focused on the chemical identity and the innervation patterns of neuromodulatory inputs in the primary olfactory system. Our findings show that serotonergic fibers are similarly distributed across glomeruli in all three species. Octopaminergic/tyraminergic fibers in the honey bee also have a similar distribution, and possibly a similar function, to noradrenergic fibers in the mammalian OBs. However, preliminary evidence suggests that human OB may be relatively less organized than its counterparts in honey bee and mouse.

Organization of the Drosophila larval visual circuit

Visual systems transduce, process and transmit light-dependent environmental cues. Computation of visual features depends on photoreceptor neuron types (PR) present, organization of the eye and wiring of the underlying neural circuit. Here, we describe the circuit architecture of the visual system of Drosophila larvae by mapping the synaptic wiring diagram and neurotransmitters. By contacting different targets, the two larval PR-subtypes create two converging pathways potentially underlying the computation of ambient light intensity and temporal light changes already within this first visual processing center. Locally processed visual information then signals via dedicated projection interneurons to higher brain areas including the lateral horn and mushroom body. The stratified structure of the larval optic neuropil (LON) suggests common organizational principles with the adult fly and vertebrate visual systems. The complete synaptic wiring diagram of the LON paves the way to understanding how circuits with reduced numerical complexity control wide ranges of behaviors.

An insect-inspired model for visual binding I: learning objects and their characteristics

Visual binding is the process of associating the responses of visual interneurons in different visual submodalities all of which are responding to the same object in the visual field. Recently identified neuropils in the insect brain termed optic glomeruli reside just downstream of the optic lobes and have an internal organization that could support visual binding. Working from anatomical similarities between optic and olfactory glomeruli, we have developed a model of visual binding based on common temporal fluctuations among signals of independent visual submodalities. Here we describe and demonstrate a neural network model capable both of refining selectivity of visual information in a given visual submodality, and of associating visual signals produced by different objects in the visual field by developing inhibitory neural synaptic weights representing the visual scene. We also show that this model is consistent with initial physiological data from optic glomeruli. Further, we discuss how this neural network model may be implemented in optic glomeruli at a neuronal level.

An insect-inspired model for visual binding II: functional analysis and visual attention

We have developed a neural network model capable of performing visual binding inspired by neuronal circuitry in the optic glomeruli of flies: a brain area that lies just downstream of the optic lobes where early visual processing is performed. This visual binding model is able to detect objects in dynamic image sequences and bind together their respective characteristic visual features-such as color, motion, and orientation-by taking advantage of their common temporal fluctuations. Visual binding is represented in the form of an inhibitory weight matrix which learns over time which features originate from a given visual object. In the present work, we show that information represented implicitly in this weight matrix can be used to explicitly count the number of objects present in the visual image, to enumerate their specific visual characteristics, and even to create an enhanced image in which one particular object is emphasized over others, thus implementing a simple form of visual attention. Further, we present a detailed analysis which reveals the function and theoretical limitations of the visual binding network and in this context describe a novel network learning rule which is optimized for visual binding.

Learning about natural variation of odor mixtures enhances categorization in early olfactory processing

Natural odors are typically mixtures of several chemical components. Mixtures vary in composition among odor objects that have the same meaning. Therefore a central 'categorization' problem for an animal as it makes decisions about odors in natural contexts is to correctly identify odor variants that have the same meaning and avoid variants that have a different meaning. We propose that identified mechanisms of associative and non-associative plasticity in early sensory processing in the insect antennal lobe and mammalian olfactory bulb are central to solving this problem. Accordingly, this plasticity should work to improve categorization of odors that have the opposite meanings in relation to important events. Using synthetic mixtures designed to mimic natural odor variation among flowers, we studied how honey bees learn about and generalize among floral odors associated with food. We behaviorally conditioned honey bees on a difficult odor discrimination problem using synthetic mixtures that mimic natural variation among snapdragon flowers. We then used calcium imaging to measure responses of projection neurons of the antennal lobe, which is the first synaptic relay of olfactory sensory information in the brain, to study how ensembles of projection neurons change as a result of behavioral conditioning. We show how these ensembles become 'tuned' through plasticity to improve categorization of odors that have the different meanings. We argue that this tuning allows more efficient use of the immense coding space of the antennal lobe and olfactory bulb to solve the categorization problem. Our data point to the need for a better understanding of the 'statistics' of the odor space.

The wiring diagram of a glomerular olfactory system

The sense of smell enables animals to react to long-distance cues according to learned and innate valences. Here, we have mapped with electron microscopy the complete wiring diagram of the Drosophila larval antennal lobe, an olfactory neuropil similar to the vertebrate olfactory bulb. We found a canonical circuit with uniglomerular projection neurons (uPNs) relaying gain-controlled ORN activity to the mushroom body and the lateral horn. A second, parallel circuit with multiglomerular projection neurons (mPNs) and hierarchically connected local neurons (LNs) selectively integrates multiple ORN signals already at the first synapse. LN-LN synaptic connections putatively implement a bistable gain control mechanism that either computes odor saliency through panglomerular inhibition, or allows some glomeruli to respond to faint aversive odors in the presence of strong appetitive odors. This complete wiring diagram will support experimental and theoretical studies towards bridging the gap between circuits and behavior.

DOI:http://dx.doi.org/10.7554/eLife.14859.001

Our sense of smell can tell us about bread being baked faraway in the kitchen, or whether a leftover piece finally went bad. Similarly to the eyes, the nose enables us to make up a mental image of what lies at a distance. In mammals, the surface of the nose hosts a huge number of olfactory sensory cells, each of which is tuned to respond to a small set of scent molecules. The olfactory sensory cells communicate with a region of the brain called the olfactory bulb. Olfactory sensory cells of the same type converge onto the same small pocket of the olfactory bulb, forming a structure called a glomerulus. Similarly to how the retina generates an image, the combined activity of multiple glomeruli defines an odor.

A particular smell is the combination of many volatile compounds, the odorants. Therefore the interactions between different olfactory glomeruli are important for defining the nature of the perceived odor. Although the types of neurons involved in these interactions were known in insects, fish and mice, a precise wiring diagram of a complete set of glomeruli had not been described. In particular, the points of contact through which neurons communicate with each other – known as synapses – among all the neurons participating in an olfactory system were not known.

Berck, Khandelwal et al. have now taken advantage of the small size of the olfactory system of the larvae of Drosophila fruit flies to fully describe, using high-resolution imaging, all its neurons and their synapses. The results define the complete wiring diagram of the neural circuit that processes the signals sent by olfactory sensory neurons in the larva’s olfactory circuits.

In addition to the neurons that read out the activity of a single glomerulus and send it to higher areas of the brain for further processing, there are also numerous neurons that read out activity from multiple glomeruli. These neurons represent a system, encoded in the genome, for quickly extracting valuable olfactory information and then relaying it to other areas of the brain.

An essential aspect of sensation is the ability to stop noticing a stimulus if it doesn't change. This allows an animal to, for example, find food by moving in a direction that increases the intensity of an odor. Inhibition mediates some aspects of this capability. The discovery of structure in the inhibitory connections among glomeruli, together with prior findings on the inner workings of the olfactory system, enabled Berck, Khandelwal et al. to hypothesize how the olfactory circuits enable odor gradients to be navigated. Further investigation revealed more about how the circuits could detect slight changes in odor concentration regardless of whether the overall odor intensity is strong or faint. And, crucially, it revealed how the worst odors – which can signal danger – can still be perceived in the presence of very strong pleasant odors.

With the wiring diagram, theories about the sense of smell can now be tested using the genetic tools available for Drosophila, leading to an understanding of how neural circuits work.

DOI:http://dx.doi.org/10.7554/eLife.14859.002

Learning modifies odor mixture processing to improve detection of relevant components

Honey bees have a rich repertoire of olfactory learning behaviors, and they therefore are an excellent model to study plasticity in olfactory circuits. Recent behavioral, physiological, and molecular evidence suggested that the antennal lobe, the first relay of the olfactory system in insects and analog to the olfactory bulb in vertebrates, is involved in associative and nonassociative olfactory learning. Here we use calcium imaging to reveal how responses across antennal lobe projection neurons change after association of an input odor with appetitive reinforcement. After appetitive conditioning to 1-hexanol, the representation of an odor mixture containing 1-hexanol becomes more similar to this odor and less similar to the background odor acetophenone. We then apply computational modeling to investigate how changes in synaptic connectivity can account for the observed plasticity. Our study suggests that experience-dependent modulation of inhibitory interactions in the antennal lobe aids perception of salient odor components mixed with behaviorally irrelevant background odors.

The scent of mixtures: rules of odour processing in ants

Natural odours are complex blends of numerous components. Understanding how animals perceive odour mixtures is central to multiple disciplines. Here we focused on carpenter ants, which rely on odours in various behavioural contexts. We studied overshadowing, a phenomenon that occurs when animals having learnt a binary mixture respond less to one component than to the other, and less than when this component was learnt alone. Ants were trained individually with alcohols and aldehydes varying in carbon-chain length, either as single odours or binary mixtures. They were then tested with the mixture and the components. Overshadowing resulted from the interaction between chain length and functional group: alcohols overshadowed aldehydes, and longer chain lengths overshadowed shorter ones; yet, combinations of these factors could cancel each other and suppress overshadowing. Our results show how ants treat binary olfactory mixtures and set the basis for predictive analyses of odour perception in insects.

Computational models to understand decision making and pattern recognition in the insect brain

Odor stimuli reaching olfactory systems of mammals and insects are characterized by remarkable non-stationary and noisy time series. Their brains have evolved to discriminate subtle changes in odor mixtures and find meaningful variations in complex spatio-temporal patterns. Insects with small brains can effectively solve two computational tasks: identify the presence of an odor type and estimate the concentration levels of the odor. Understanding the learning and decision making processes in the insect brain can not only help us to uncover general principles of information processing in the brain, but it can also provide key insights to artificial chemical sensing. Both olfactory learning and memory are dominantly organized in the Antennal Lobe (AL) and the Mushroom Bodies (MBs). Current computational models yet fail to deliver an integrated picture of the joint computational roles of the AL and MBs. This review intends to provide an integrative overview of the computational literature analyzed in the context of the problem of classification (odor discrimination) and regression (odor concentration estimation), particularly identifying key computational ingredients necessary to solve pattern recognition.

Rapid and slow chemical synaptic interactions of cholinergic projection neurons and GABAergic local interneurons in the insect antennal lobe

The antennal lobe (AL) of insects constitutes the first synaptic relay and processing center of olfactory information, received from olfactory sensory neurons located on the antennae. Complex synaptic connectivity between olfactory neurons of the AL ultimately determines the spatial and temporal tuning profile of (output) projection neurons to odors. Here we used paired whole-cell patch-clamp recordings in the cockroach Periplaneta americana to characterize synaptic interactions between cholinergic uniglomerular projection neurons (uPNs) and GABAergic local interneurons (LNs), both of which are key components of the insect olfactory system. We found rapid, strong excitatory synaptic connections between uPNs and LNs. This rapid excitatory transmission was blocked by the nicotinic acetylcholine receptor blocker mecamylamine. IPSPs, elicited by synaptic input from a presynaptic LN, were recorded in both uPNs and LNs. IPSPs were composed of both slow, sustained components and fast, transient components which were coincident with presynaptic action potentials. The fast IPSPs were blocked by the GABAA receptor chloride channel blocker picrotoxin, whereas the slow sustained IPSPs were blocked by the GABAB receptor blocker CGP-54626. This is the first study to directly show the predicted dual fast- and slow-inhibitory action of LNs, which was predicted to be key in shaping complex odor responses in the AL of insects. We also provide the first direct characterization of rapid postsynaptic potentials coincident with presynaptic spikes between olfactory processing neurons in the AL.

Arc visualization of odor objects reveals experience-dependent ensemble sharpening, separation, and merging in anterior piriform cortex in adult rat

Visualization using the immediate early gene Arc revealed sparser and more robust odor representations in the anterior piriform cortex of adult rats when odor was associated with water reward over 2-3 d. Rewarded odor "mixtures" resulted in rats responding to either component odor similarly, and, correspondingly, the odor representations became more similar as indexed by increased overlap in piriform Arc-expressing (Arc(+)) pyramidal neurons. The increased overlap was consistent with the rats' generalization from component odors. Discriminating among highly similar odor mixtures for reward led to increased differentiation of the neural representations as indexed by a reduction in overlap for piriform Arc(+) pyramidal neurons after training. Similar odor mixture discrimination also required more trials to criterion. The visible reduction in the overlap of odor representations indexes pattern separation. The Arc visualization of odor representations in the anterior piriform network suggests that odor objects are widely distributed representations and can be rapidly modified by reward training in adult rats. We suggest that dynamic changes such as those observed here in piriform odor encoding are at the heart of perceptual learning and reflect the continuing plastic nature of mature associative cortex as an outcome of successful problem solving.

Chemical structure of odorants and perceptual similarity in ants

Animals are often immersed in a chemical world consisting of mixtures of many compounds rather than of single substances, and they constantly face the challenge of extracting relevant information out of the chemical landscape. To this purpose, the ability to discriminate among different stimuli with different valence is essential, but it is also important to be able to generalise, i.e. to treat different but similar stimuli as equivalent, as natural variation does not necessarily affect stimulus valence. Animals can thus extract regularities in their environment and make predictions, for instance about distribution of food resources. We studied perceptual similarity of different plant odours by conditioning individual carpenter ants to one odour, and subsequently testing their response to another, structurally different odour. We found that asymmetry in generalisation, where ants generalise from odour A to B, but not from B to A, is dependent on both chain length and functional group. By conditioning ants to a binary mixture, and testing their reaction to the individual components of the mixture, we show that overshadowing, where parts of a mixture are learned better than others, is rare. Additionally, generalisation is dependent not only on the structural similarity of odorants, but also on their functional value, which might play a crucial role. Our results provide insight into how ants make sense of the complex chemical world around them, for example in a foraging context, and provide a basis with which to investigate the neural mechanisms behind perceptual similarity.

Six networks on a universal neuromorphic computing substrate

In this study, we present a highly configurable neuromorphic computing substrate and use it for emulating several types of neural networks. At the heart of this system lies a mixed-signal chip, with analog implementations of neurons and synapses and digital transmission of action potentials. Major advantages of this emulation device, which has been explicitly designed as a universal neural network emulator, are its inherent parallelism and high acceleration factor compared to conventional computers. Its configurability allows the realization of almost arbitrary network topologies and the use of widely varied neuronal and synaptic parameters. Fixed-pattern noise inherent to analog circuitry is reduced by calibration routines. An integrated development environment allows neuroscientists to operate the device without any prior knowledge of neuromorphic circuit design. As a showcase for the capabilities of the system, we describe the successful emulation of six different neural networks which cover a broad spectrum of both structure and functionality.

Non-linear blend coding in the moth antennal lobe emerges from random glomerular networks

Neural responses to odor blends often exhibit non-linear interactions to blend components. The first olfactory processing center in insects, the antennal lobe (AL), exhibits a complex network connectivity. We attempt to determine if non-linear blend interactions can arise purely as a function of the AL network connectivity itself, without necessitating additional factors such as competitive ligand binding at the periphery or intrinsic cellular properties. To assess this, we compared blend interactions among responses from single neurons recorded intracellularly in the AL of the moth Manduca sexta with those generated using a population-based computational model constructed from the morphologically based connectivity pattern of projection neurons (PNs) and local interneurons (LNs) with randomized connection probabilities from which we excluded detailed intrinsic neuronal properties. The model accurately predicted most of the proportions of blend interaction types observed in the physiological data. Our simulations also indicate that input from LNs is important in establishing both the type of blend interaction and the nature of the neuronal response (excitation or inhibition) exhibited by AL neurons. For LNs, the only input that significantly impacted the blend interaction type was received from other LNs, while for PNs the input from olfactory sensory neurons and other PNs contributed agonistically with the LN input to shape the AL output. Our results demonstrate that non-linear blend interactions can be a natural consequence of AL connectivity, and highlight the importance of lateral inhibition as a key feature of blend coding to be addressed in future experimental and computational studies.

Parallel representation of stimulus identity and intensity in a dual pathway model inspired by the olfactory system of the honeybee

The honeybee Apis mellifera has a remarkable ability to detect and locate food sources during foraging, and to associate odor cues with food rewards. In the honeybee's olfactory system, sensory input is first processed in the antennal lobe (AL) network. Uniglomerular projection neurons (PNs) convey the sensory code from the AL to higher brain regions via two parallel but anatomically distinct pathways, the lateral and the medial antenno-cerebral tract (l- and m-ACT). Neurons innervating either tract show characteristic differences in odor selectivity, concentration dependence, and representation of mixtures. It is still unknown how this differential stimulus representation is achieved within the AL network. In this contribution, we use a computational network model to demonstrate that the experimentally observed features of odor coding in PNs can be reproduced by varying lateral inhibition and gain control in an otherwise unchanged AL network. We show that odor coding in the l-ACT supports detection and accurate identification of weak odor traces at the expense of concentration sensitivity, while odor coding in the m-ACT provides the basis for the computation and following of concentration gradients but provides weaker discrimination power. Both coding strategies are mutually exclusive, which creates a tradeoff between detection accuracy and sensitivity. The development of two parallel systems may thus reflect an evolutionary solution to this problem that enables honeybees to achieve both tasks during bee foraging in their natural environment, and which could inspire the development of artificial chemosensory devices for odor-guided navigation in robots.

Behavioral and neurophysiological study of olfactory perception and learning in honeybees

The honeybee Apis mellifera has been a central insect model in the study of olfactory perception and learning for more than a century, starting with pioneer work by Karl von Frisch. Research on olfaction in honeybees has greatly benefited from the advent of a range of behavioral and neurophysiological paradigms in the Lab. Here I review major findings about how the honeybee brain detects, processes, and learns odors, based on behavioral, neuroanatomical, and neurophysiological approaches. I first address the behavioral study of olfactory learning, from experiments on free-flying workers visiting artificial flowers to laboratory-based conditioning protocols on restrained individuals. I explain how the study of olfactory learning has allowed understanding the discrimination and generalization ability of the honeybee olfactory system, its capacity to grant special properties to olfactory mixtures as well as to retain individual component information. Next, based on the impressive amount of anatomical and immunochemical studies of the bee brain, I detail our knowledge of olfactory pathways. I then show how functional recordings of odor-evoked activity in the brain allow following the transformation of the olfactory message from the periphery until higher-order central structures. Data from extra- and intracellular electrophysiological approaches as well as from the most recent optical imaging developments are described. Lastly, I discuss results addressing how odor representation changes as a result of experience. This impressive ensemble of behavioral, neuroanatomical, and neurophysiological data available in the bee make it an attractive model for future research aiming to understand olfactory perception and learning in an integrative fashion.

Transient dynamics between displaced fixed points: an alternate nonlinear dynamical framework for olfaction

Significant insights into the dynamics of neuronal populations have been gained in the olfactory system where rich spatio-temporal dynamics is observed during, and following, exposure to odours. It is now widely accepted that odour identity is represented in terms of stimulus-specific rate patterning observed in the cells of the antennal lobe (AL). Here we describe a nonlinear dynamical framework inspired by recent experimental findings which provides a compelling account of both the origin and the function of these dynamics. We start by analytically reducing a biologically plausible conductance based model of the AL to a quantitatively equivalent rate model and construct conditions such that the rate dynamics are well described by a single globally stable fixed point (FP). We then describe the AL's response to an odour stimulus as rich transient trajectories between this stable baseline state (the single FP in absence of odour stimulation) and the odour-specific position of the single FP during odour stimulation. We show how this framework can account for three phenomena that are observed experimentally. First, for an inhibitory period often observed immediately after an odour stimulus is removed. Second, for the qualitative differences between the dynamics in the presence and the absence of odour. Lastly, we show how it can account for the invariance of a representation of odour identity to both the duration and intensity of an odour stimulus. We compare and contrast this framework with the currently prevalent nonlinear dynamical framework of 'winnerless competition' which describes AL dynamics in terms of heteroclinic orbits. This article is part of a Special Issue entitled "Neural Coding".

Associative conditioning tunes transient dynamics of early olfactory processing

Odors evoke complex spatiotemporal responses in the insect antennal lobe (AL) and mammalian olfactory bulb. However, the behavioral relevance of spatiotemporal coding remains unclear. In the present work we combined behavioral analyses with calcium imaging of odor induced activity in the honeybee AL to evaluate the relevance of this temporal dimension in the olfactory code. We used a new way for evaluation of odor similarity of binary mixtures in behavioral studies, which involved testing whether a match of odor-sampling time is necessary between training and testing conditions for odor recognition during associative learning. Using graded changes in the similarity of the mixture ratios, we found high correlations between the behavioral generalization across those mixtures and a gradient of activation in AL output. Furthermore, short odor stimuli of 500 ms or less affected how well odors were matched with a memory template, and this time corresponded to a shift from a sampling-time-dependent to a sampling-time-independent memory. Accordingly, 375 ms corresponded to the time required for spatiotemporal AL activity patterns to reach maximal separation according to imaging studies. Finally, we compared spatiotemporal representations of binary mixtures in trained and untrained animals. AL activity was modified by conditioning to improve separation of odor representations. These data suggest that one role of reinforcement is to "tune" the AL such that relevant odors become more discriminable.

Elemental and configural processing of odour mixtures in the newborn rabbit

The processing of odour mixtures by young organisms is poorly understood. Recently, the perception of an AB mixture, known to engage configural perception in adult humans, was suggested also to be partially configural in newborn rabbits. In particular, pups did not respond to AB after they had learned A or B. However, two alternative hypotheses might be suggested to explain this result: the presence in the mixture of a novel odorant that inhibits the response to the learned stimulus, and the unevenness of the sensory and cognitive processes engaged during the conditioning and the behavioural testing. We conducted four experiments to explore these alternative hypotheses. In experiment 1, the learning of A or B ended in responses to mixtures including a novel odorant (AC or BC). Experiment 2 pointed to the absence of overshadowing. Therefore, a novelty effect cannot explain the non-response to AB after the learning of A or B. In experiment 3,pups having learned A or B in AC or BC did not respond to AB. However, they generalized odour information acquired in AB to AC or BC in experiment 4. Thus, the balancing of the perceptual tasks between the conditioning and retention test does not enhance the response to the AB mixture. To sum up, the present experiments give concrete support to the partially configural perception of specific odour mixtures by newborn rabbits.

Using insect sniffing devices for detection

Emerging information about the ability of insects to detect and associatively learn has revealed that they could be used within chemical detection systems. Such systems have been developed around free-moving insects, such as honey bees. Alternatively, behavioral changes of contained insects can be interpreted by sampling air pumped over their olfactory organs. These organisms are highly sensitive, flexible, portable and cheap to reproduce, and it is easy to condition them to detect target odorants. However, insect-sensing systems are not widely studied or accepted as proven biological sensors. Further studies are needed to examine additional insect species and to develop better methods of using their olfactory system for detecting odorants of interest.

Stimulus control and compounding with ambient odor as a discriminative stimulus on a free-operant baseline

Previous experiments have demonstrated that the simultaneous presentation of independently established discriminative stimuli can control rates of operant responding substantially higher than the rates occasioned by the individual stimuli. This "additive summation" phenomenon has been shown with a variety of different reinforcers (e.g., food, water, shock avoidance, cocaine, and heroin). Discriminative stimuli previously used in such studies have been limited to the visual and auditory sensory modalities. The present experiment sought to (1) establish stimulus control on a free-operant baseline with an ambient olfactory discriminative stimulus, (2) compare olfactory control to that produced with an auditory discriminative stimulus, and (3) determine whether compounding independently established olfactory and auditory discriminative stimuli produces additive summation. Rats lever pressed for food on a variable-interval schedule in the presence of either a tone or an odor, with comparable control developed to each stimulus. In the absence of these stimuli responding was not reinforced. During stimulus compounding tests, the tone-plus-odor compound occasioned more than double the responses occasioned by either the tone or odor presented individually. Thus, the current study (1) established stimulus control with an ambient olfactory discriminative stimulus in a traditional free-operant setting and (2) extended the generality of stimulus-compounding effects by demonstrating additive summation when olfactory and auditory discriminative stimuli were presented simultaneously.

Computation in the olfactory system

Computational models are increasingly essential to systems neuroscience. Models serve as proofs of concept, tests of sufficiency, and as quantitative embodiments of working hypotheses and are important tools for understanding and interpreting complex data sets. In the olfactory system, models have played a particularly prominent role in framing contemporary theories and presenting novel hypotheses, a role that will only grow as the complexity and intricacy of experimental data continue to increase. This review will attempt to provide a comprehensive, functional overview of computational ideas in olfaction and outline a computational framework for olfactory processing based on the insights provided by these diverse models and their supporting data.

Olfactory blocking and odorant similarity in the honeybee

Blocking occurs when previous training with a stimulus A reduces (blocks) subsequent learning about a stimulus B, when A and B are trained in compound. The question of whether blocking exists in olfactory conditioning of proboscis extension reflex (PER) in honeybees is under debate. The last published accounts on blocking in honeybees state that blocking occurs when odors A and B are similar (the "similarity hypothesis"). We have tested this hypothesis using four odors (1-octanol, 1-nonanol, eugenol, and limonene) chosen on the basis of their chemical and physiological similarity (experiment 1). We established a generalization matrix that measured perceptual similarity. Bees in the "block group" were first trained with an odor A and, in the second phase, with the mixture AB. Bees in the "novel group" (control group) were first trained with an odor N and, in the second phase, with the mixture AB. After conditioning, bees in both groups were tested for their response to B. We assayed all 24 possible combinations for the four odors standing for A, B, and N. We found blocking in four cases, augmentation in two cases, and no difference in 18 cases; odor similarity could not account for these results. We also repeated the experiments with those six odor combinations that gave rise to the similarity hypothesis (experiment 2: 1-hexanol, 1-octanol, geraniol) and found augmentation in one and no effect in five cases. Thus, blocking is not a consistent phenomenon, nor does it depend on odor similarity.

Acetylcholine, GABA and glutamate induce ionic currents in cultured antennal lobe neurons of the honeybee, Apis mellifera

The honeybee, Apis mellifera, is a valuable model system for the study of olfactory coding and its learning and memory capabilities. In order to understand the synaptic organisation of olfactory information processing, the transmitter receptors of the antennal lobe need to be characterized. Using whole-cell patch-clamp recordings, we analysed the ligand-gated ionic currents of antennal lobe neurons in primary cell culture. Pressure applications of acetylcholine (ACh), gamma-amino butyric acid (GABA) or glutamate induced rapidly activating ionic currents. The ACh-induced current flows through a cation-selective ionotropic receptor with a nicotinic profile. The ACh-induced current is partially blocked by alpha-bungarotoxin. Epibatidine and imidacloprid are partial agonists. Our data indicate the existence of an ionotropic GABA receptor which is permeable to chloride ions and sensitive to picrotoxin (PTX) and the insecticide fipronil. We also identified the existence of a chloride current activated by pressure applications of glutamate. The glutamate-induced current is sensitive to PTX. Thus, within the honeybee antennal lobe, an excitatory cholinergic transmitter system and two inhibitory networks that use GABA or glutamate as their neurotransmitter were identified.

Perceptual and neural olfactory similarity in honeybees

The question of whether or not neural activity patterns recorded in the olfactory centres of the brain correspond to olfactory perceptual measures remains unanswered. To address this question, we studied olfaction in honeybees Apis mellifera using the olfactory conditioning of the proboscis extension response. We conditioned bees to odours and tested generalisation responses to different odours. Sixteen odours were used, which varied both in their functional group (primary and secondary alcohols, aldehydes and ketones) and in their carbon-chain length (from six to nine carbons). The results obtained by presentation of a total of 16 x 16 odour pairs show that (i) all odorants presented could be learned, although acquisition was lower for short-chain ketones; (ii) generalisation varied depending both on the functional group and the carbon-chain length of odours trained; higher generalisation was found between long-chain than between short-chain molecules and between groups such as primary and secondary alcohols; (iii) for some odour pairs, cross-generalisation between odorants was asymmetric; (iv) a putative olfactory space could be defined for the honeybee with functional group and carbon-chain length as inner dimensions; (v) perceptual distances in such a space correlate well with physiological distances determined from optophysiological recordings of antennal lobe activity. We conclude that functional group and carbon-chain length are inner dimensions of the honeybee olfactory space and that neural activity in the antennal lobe reflects the perceptual quality of odours.

Computational modeling suggests that response properties rather than spatial position determine connectivity between olfactory glomeruli

Olfactory responses require the representation of high-dimensional olfactory stimuli within the constraints of two-dimensional neural networks. We used a computational model of the honeybee antennal lobe to test how inhibitory interactions in the antennal lobe should be organized to best reproduce the experimentally measured input-output function in this structure. Our simulations show that a functionally organized inhibitory network, as opposed to an anatomically or all-to-all organized inhibitory network, best reproduces the input-output function of the antennal lobe observed with calcium imaging. In this network, inhibition between each pair of glomeruli was proportional to the similarity of their odor-response profiles. We conclude that contrast enhancement between odorants in the honeybee antennal lobe is best achieved when interglomerular inhibition is organized based on glomerular odor response profiles rather than on anatomical neighborhood relations.

A Redefinition of Odor Mixture Quality

Odor mixtures are perceived as different from (configural) or the same as (elemental) their components. Recent studies (L. M. Kay, C. A. Lowry, & H. A. Jacobs, 2003; C. Wiltrout, S. Dogra, & C. Linster, 2003) propose that component structural or perceptual similarities predict configural properties of binary mixtures. The authors evaluated this in rats using 4 binary mixtures with varying structural similarity (eucalyptol-benzaldehyde, eugenol-benzaldehyde, octanol-octanal, and [+/-]-limonene). The range of tested ratios for each mixture was determined by the components' vapor pressures. Three results are presented: (a) No mixture maintains purely elemental or configural properties for all concentration ratios, (b) structural similarity or dissimilarity does not predict configural or elemental perception, and (c) overshadowing is significant in responses to all odor sets. The authors offer more precise definitions of elemental and configural properties and overshadowing as they relate to odor mixture perception.

Learning modulates the ensemble representations for odors in primary olfactory networks

Recent evidence suggests that odor-driven responses in the insect antennal lobe (AL) can be modified by associative and nonassociative processes, as has been shown in the vertebrate olfactory bulb. However, the specific network changes that occur in response to olfactory learning remain unknown. To characterize changes in AL network activity during learning, we developed an in vivo protocol in Manduca sexta that allows continuous monitoring of neural ensembles and feeding behavior over the course of olfactory conditioning. Here, we show that Pavlovian conditioning produced a net recruitment of responsive neural units across the AL that persisted after conditioning. Recruitment only occurred when odor reliably predicted food. Conversely, when odor did not predict food, a net loss of responsive units occurred. Simultaneous measures of feeding responses indicated that the treatment-specific patterns of neural recruitment were positively correlated with changes in the insect's behavioral response to odor. In addition to recruitment, conditioning also produced consistent and profound shifts in the temporal responses of 16% of recorded units. These results show that odor representations in the AL are dynamic and related to olfactory memory consolidation. We furthermore provide evidence that the basis of the learning-dependent changes in the AL is not simply an increase in activity in the neural network representing an odorant. Rather, learning produces a restructuring of spatial and temporal components of network responses to odor in the AL.

Variation in complex olfactory stimuli and its influence on odour recognition

Natural olfactory stimuli are often complex and highly variable. The olfactory systems of animals are likely to have evolved to use specific features of olfactory stimuli for identification and discrimination. Here, we train honeybees to learn chemically defined odorant mixtures that systematically vary from trial to trial and then examine how they generalize to each odorant present in the mixture. An odorant that was present at a constant concentration in a mixture becomes more representative of the mixture than other variable odorants. We also show that both variation and intensity of a complex olfactory stimulus affect the rate of generalization by honeybees to subsequent olfactory stimuli. These results have implications for the way that all animals perceive and attend to features of olfactory stimuli.

Associative olfactory learning of honeybees to differential rewards in multiple contexts--effect of odor component and mixture similarity

Discrimination among differentially rewarding flowers allows honeybees to maximize their foraging efficiency. We studied how honeybees are able to relate to differential positive rewards when the odor representations are either structurally dissimilar, structurally similar (or form a substrate-product duo in planta), or form a binary mixture sharing a common constituent. Bees were tested both in conditioning of the proboscis-extension response (PER) and in a free-flying context. Our results point to honeybees using olfactory associative learning to differentiate between two positively rewarded odors. In PER, subjects discriminated best between dissimilar odors; they initially generalized between similar odors, but eventually learned to discriminate between them. The discrimination between mixtures sharing a common constituent remained poor. Likewise, the difference in visits to low- and high-rewarding flowers of free-flying bees was greater for dissimilar odors than for binary mixtures sharing a common constituent. Consequences of the operant conditioning nature of the free-flying context are discussed.

Side-specific olfactory conditioning leads to more specific odor representation between sides but not within sides in the honeybee antennal lobes

Honeybees can be trained to associate odorants to sucrose reward by conditioning the proboscis extension response. Using this paradigm, we have recently shown that bees can solve a side-specific task: they learn simultaneously to discriminate a reinforced odor A from a non-reinforced odor B at one antenna (A+B-) and the reversed problem at the other antenna (A-B+). Side-specific (A+B-/B+A-) conditioning is an interesting tool to measure neurophysiological changes due to olfactory learning because the same odorant is excitatory (CS+) on one brain side and inhibitory (CS-) on the opposite side. In the bee brain, the antennal lobe (AL) is the first olfactory relay where the olfactory memory is established. Using calcium imaging, we compared odor-evoked activity in the functional units, the glomeruli, of the two ALs, both in naive and conditioned individuals. Each odor evoked a different pattern of glomerular activity, which was symmetrical between sides and highly conserved among naive animals. In conditioned bees, response patterns were overall symmetrical but showed more active glomeruli and topical differences between sides. By representing odor vectors in a virtual olfactory space whose dimensions are the responses of 23 identified glomeruli, we found that distances between odor representations on each brain side were significantly higher in conditioned than in naive bees, but only for CS+ and CS-. However, the distance between CS+ and CS- representations was equal to that of naive individuals. Our work suggests that side-specific conditioning decorrelates odor representations between AL sides but not between CS+ and CS- within one AL.

Modulation of early olfactory processing by an octopaminergic reinforcement pathway in the honeybee

Processing of olfactory information in the antennal lobes of insects and olfactory bulbs of vertebrates is modulated by centrifugal inputs that represent reinforcing events. Octopamine release by one such pathway in the honeybee antennal lobe modulates olfactory processing in relation to nectar (sucrose) reinforcement. To test more specifically what role octopamine plays in the antennal lobe, we used two treatments to disrupt an octopamine receptor from Apis mellifera brain (AmOAR) function: (1) an OAR antagonist, mianserin, was used to block receptor function, and (2) AmOAR double-stranded RNA was used to silence receptor expression. Both treatments inhibited olfactory acquisition and recall, but they did not disrupt odor discrimination. These results suggest that octopamine mediates consolidation of a component of olfactory memory at this early processing stage in the antennal lobe. Furthermore, after consolidation, octopamine release becomes essential for recall, which suggests that the modulatory circuits become incorporated as essential components of neural representations that activate odor memory.

How synchronization properties among second-order sensory neurons can mediate stimulus salience

Spatial patterns of glomerular activity in the vertebrate olfactory bulb and arthropod antennal lobe reflect an important component of first-order olfactory representation and contribute to odorant identification. Higher concentration odor stimuli evoke broader glomerular activation patterns, resulting in greater spatial overlap among different odor representations. However, behavioral studies demonstrate results contrary to what these data might suggest: Honeybees are more, not less, able to discriminate among odorants applied at higher concentrations. Using a computational model of the honeybee antennal lobe, the authors show that changes in synchronization patterns among antennal lobe projection neurons, as observed electrophysiologically, could parsimoniously underlie these observations. The results suggest that stimulus salience, as defined behaviorally, is directly correlated with the degree of synchronization among second-order olfactory neurons.

How spike synchronization among olfactory neurons can contribute to sensory discrimination

Recent studies in honeybees have demonstrated that, when odor-evoked action potentials in antennal lobe neurons are pharmacologically desynchronized, the bees are impaired in their ability to discriminate chemically similar odor stimuli. Using a reduced computational model of the honeybee antennal lobe, we show how changes in spike-synchronization properties alone, independent of changes in overall spike-discharge rate or differences in activity levels among responsive neurons, can produce changes in associative learning similar to those observed experimentally.

Symmetry, stereotypy, and topography of odorant representations in mouse olfactory bulbs

The molecular basis of vertebrate odorant representations has been derived extensively from mice. The functional correlates of these molecular features were visualized using optical imaging of intrinsic signals in mouse olfactory bulbs. Single odorants activated clusters of glomeruli in consistent, restricted portions of the bulb. Patterns of activated glomeruli were clearly bilaterally symmetric and consistent in different individual mice, but the precise number, position, and intensity of activated glomeruli in the two bulbs of the same individual and between individuals varied considerably. Representations of aliphatic aldehydes of different carbon chain length shifted systematically along a rostral-caudal strip of the dorsal bulb, indicating a functional topography of odorant representations. Binary mixtures of individual aldehydes elicited patterns of glomerular activation that were topographic combinations of the maps for each individual odor. Thus the principles derived from the molecular organization of a small subset of murine olfactory receptor neuron projection patterns-bilateral symmetry, local clustering, and local variability-are reliable guides to the initial functional representation of odorant molecules.

Olfactory coding in a simple system: adaptation in Drosophila larvae

Drosophila melanogaster larvae were pre-stimulated with high concentrations of six homologous alcohols (C4-C9) and then tested for adaptation and cross-adaptation using these same alcohols, four aliphatic n-acetates and three acids. Pre-stimulation with hexanol effectively reduced to zero (abolished) test responses to all six alcohols, whereas test responses to hexanol were only affected by pre-stimulation with hexanol. This substance appears to play a fundamental role in the organization of the larval olfactory system. Test responses to butanol and pentanol, and the effect of pre-stimulation with butanol and pentanol, were not significantly different, indicating that they are sensory equivalents. Heptanol, octanol and nonanol induce a complex set of responses among one another. Cross-adaptation between functional groups was observed, in particular following pre-stimulation with hexanol, but there was also evidence that functional groups are coded separately. A model of olfactory processing in the fruitfly maggot is presented that explains the data and provides predictions for future anatomical, genetic and electrophysiological studies.

Blocking and the detection of odor components in blends

Recent studies of olfactory blocking have revealed that binary odorant mixtures are not always processed as though they give rise to mixture-unique configural properties. When animals are conditioned to one odorant (A) and then conditioned to a mixture of that odorant with a second (X), the ability to learn or express the association of X with reinforcement appears to be reduced relative to animals that were not preconditioned to A. A recent model of odor-based response patterns in the insect antennal lobe predicts that the strength of the blocking effect will be related to the perceptual similarity between the two odorants, i.e. greater similarity should increase the blocking effect. Here, we test that model in the honeybee Apis mellifera by first establishing a generalization matrix for three odorants and then testing for blocking between all possible combinations of them. We confirm earlier findings demonstrating the occurrence of the blocking effect in olfactory learning of compound stimuli. We show that the occurrence and the strength of the blocking effect depend on the odorants used in the experiment. In addition, we find very good agreement between our results and the model, and less agreement between our results and an alternative model recently proposed to explain the effect.

Odour perception in honeybees: coding information in glomerular patterns

Major advances have been made during the past two years in understanding how honeybees process olfactory input at the level of their first brain structure dealing with odours, the antennal lobe (the insect analogue of the mammalian olfactory bulb). It is now possible to map physiological responses to morphologically identified olfactory glomeruli, allowing for the creation of a functional atlas of the antennal lobe. Furthermore, the measurement of odour-evoked activity patterns has now been combined with studies of appetitive odour learning. The results show that both genetically determined components and learning-related plasticity shape olfactory processing in the antennal lobe.

Impairment of olfactory discrimination by blockade of GABA and nitric oxide activity in the honey bee antennal lobes

Honey bees readily associate an odor with sucrose reinforcement, and the response generalizes to other odors as a function of structural similarity to the conditioned odor. Recent studies have shown that a portion of odor memory is consolidated in the antennal lobes (AL), where first-order synaptic processing of sensory information takes place. The AL and/or the sensory afferents that project into them show staining patterns for the enzyme nitric oxide synthase, which catalyzes the release of the gaseous transmitter nitric oxide (NO). The results show that pharmacological blockade of NO release impairs olfactory discrimination only when release is blocked before conditioning. Blockade of GABAergic transmission disrupts discrimination of similar but not dissimilar odorants, and does so when the block occurs before condition or before testing. These results show that GABA and NO regulate the specificity of associative olfactory memory in the AL.

Odor specificity of habituation in the rat anterior piriform cortex

Exposure to odorants results in a rapid (<10 s) reduction in odor-evoked activity in the rat piriform cortex despite relatively maintained afferent input from olfactory bulb mitral cells. To further understand this form of cortical plasticity, a detailed analysis of its odor specificity was performed. Habituation of odor responses in anterior piriform cortex single units was examined in anesthetized, freely breathing rats. The magnitude of single-unit responses of layer II/III neurons to 2-s odor pulses were examined before and after a 50-s habituating stimulus of either the same or different odor. The results demonstrated that odor habituation was odor specific, with no significant cross-habituation between either markedly different single odors or between odors within a series of straight chain alkanes. Furthermore, habituation to binary 1:1 mixtures produced minimal cross-habituation to the components of that mixture. These latter results may suggest synthetic odor processing in the olfactory system, with novel odor mixtures processed as unique stimuli. Potential mechanisms of odor habituation in the piriform cortex must be able to account for the high degree of specificity of this effect.

A systems perspective on early olfactory coding

This review critically examines neuronal coding strategies and how they might apply to olfactory processing. Basic notions such as identity, spatial, temporal, and correlation codes are defined and different perspectives are brought to the study of neural codes. Odors as physical stimuli and their processing by the early olfactory system, one or two synapses away from the receptors, are discussed. Finally, the concept of lateral inhibition, as usually understood and applied to odor coding by mitral (or equivalent) cells, is challenged and extended to a broader context, possibly more appropriate for olfactory processing.

Generalization between binary odor mixtures and their components in the rat

We have adopted a conditioning paradigm to investigate generalization between odor mixtures and components. Rats were conditioned to find a reward buried in odor-scented cups. The conditioned odor was either a mixture (O1 + O2) or a pure component (O1). Once they learned the task to criterion, they were tested in random sequence for response to that O1, O1 + O2 and to an unrelated odor (O3). Generalization was consistently the strongest from O1 to O1 + O2 or from O1 + O2 to O1. Furthermore. the degree of generalization depended on the odorants used as O1, O2, and O3. This latter finding in a particular indicates that this assay can be used to assess properties of mixtures, which could arise at either peripheral or more central locations.

Analysis of interaction in binary odorant mixtures

An understanding of the olfactory system of any animal must account for how odor mixtures are perceived and processed. The present experiments apply associationist models to the study of how elements are processed in binary odorant mixtures. Using experimental designs for Proboscis Extension Conditioning of honey bees, I show that learning about a pure odorant element is frequently affected by its occurrence in a mixture with a second odorant. Presence of a background odor when an odorant is associated with sucrose reinforcement decreases the rate and/or asymptotic level of associative strength that accumulates to that odorant. This interaction is in part due to synthetic qualities that arise in sensory transduction and initial processing. In addition, it involves an attention-like processing system like that involved in overshadowing. Therefore, a model that includes representations of the component and configural qualities of odorants in mixtures is needed to provide a more complete account of learning about odor mixtures.

Computational models of neuromodulation

Computational modeling of neural substrates provides an excellent theoretical framework for the understanding of the computational roles of neuromodulation. In this review, we illustrate, with a large number of modeling studies, the specific computations performed by neuromodulation in the context of various neural models of invertebrate and vertebrate preparations. We base our characterization of neuromodulations on their computational and functional roles rather than on anatomical or chemical criteria. We review the main framework in which neuromodulation has been studied theoretically (central pattern generation and oscillations, sensory processing, memory and information integration). Finally, we present a detailed mathematical overview of how neuromodulation has been implemented at the single cell and network levels in modeling studies. Overall, neuromodulation is found to increase and control computational complexity.