Keeping their distance? Odor response patterns along the concentration range

Antenna movements as a function of odorants' biological value in honeybees (Apis mellifera L.)

In honeybees, the antennae are highly mobile sensory organs that express scanning movements in various behavioral contexts and toward many stimuli, especially odorants. The rules underlying these movements are still unclear. Using a motion-capture system, we analyzed bees' antennal responses to a panel of pheromonal and other biologically relevant odorants. We observed clear differences in bees' antennal responses, with opposite movements to stimuli related to opposite contexts: slow backward movements were expressed in response to alarm pheromones, while fast forward movements were elicited by food related cues as well as brood and queen related pheromones. These responses are reproducible, as a similar pattern of odor-specific responses was observed in bees from different colonies, on different years. We then tested whether odorants' attractiveness for bees, measured using an original olfactory orientation setup, may predict antenna movements. This simple measure of odorants' valence did however not correlate with either antennal position or velocity measures, showing that more complex rules than simple hedonics underlie bees' antennal responses to odorants. Lastly, we show that newly-emerged bees express only limited antennal responses compared to older bees, suggesting that a significant part of the observed responses are acquired during bees' behavioral development.

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

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

Olfactory coding in honeybees

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

Odorant mixtures elicit less variable and faster responses than pure odorants

In natural environments, odors are typically mixtures of several different chemical compounds. However, the implications of mixtures for odor processing have not been fully investigated. We have extended a standard olfactory receptor model to mixtures and found through its mathematical analysis that odorant-evoked activity patterns are more stable across concentrations and first-spike latencies of receptor neurons are shorter for mixtures than for pure odorants. Shorter first-spike latencies arise from the nonlinear dependence of binding rate on odorant concentration, commonly described by the Hill coefficient, while the more stable activity patterns result from the competition between different ligands for receptor sites. These results are consistent with observations from numerical simulations and physiological recordings in the olfactory system of insects. Our results suggest that mixtures allow faster and more reliable olfactory coding, which could be one of the reasons why animals often use mixtures in chemical signaling.

Differential Processing by Two Olfactory Subsystems in the Honeybee Brain

Among insects, Hymenoptera present a striking olfactory system with a clear neural dichotomy from the periphery to higher order centers, based on two main tracts of second-order (projection) neurons: the medial and lateral antennal lobe tracts (m-ALT and l-ALT). Despite substantial work on this dual pathway, its exact function is yet unclear. Here, we ask how attributes of odor quality and odor quantity are represented in the projection neurons (PNs) of the two pathways. Using in vivo calcium imaging, we compared the responses of m-ALT and l-ALT PNs of the honey bee Apis mellifera to a panel of 16 aliphatic odorants, and to three chosen odorants at eight concentrations. The results show that each pathway conveys differential information about odorants' chemical features or concentration to higher order centers. While the l-ALT primarily conveys information about odorants' chain length, the m-ALT informs about odorants' functional group. Furthermore, each tract can only predict chemical distances or bees' behavioral responses for odorants that differ according to its main feature, chain length or functional group. Generally l-ALT neurons displayed more graded dose-response relationships than m-ALT neurons, with a correspondingly smoother progression of inter-odor distances with increasing concentration. Comparison of these results with previous data recorded at AL input reveals differential processing by local networks within the two pathways. These results support the existence of parallel processing of odorant features in the insect brain.

Take time: odor coding capacity across sensory neurons increases over time in Drosophila

Due to the highly efficient olfactory code, olfactory sensory systems are able to reliably encode enormous numbers of olfactory stimuli. The olfactory code consists of combinatorial activation patterns across sensory neurons, thus its capacity exceeds the number of involved classes of sensory neurons by a manifold. Activation patterns are not static but vary over time, caused by the temporally complex response dynamics of the individual sensory neuron responses. We systematically analyzed the temporal dynamics of olfactory sensory neuron responses to a diverse set of odorants. We find that response dynamics depend on the combination of sensory neuron and odorant and that information about odorant identity can be extracted from the time course of the response. We also show that new response dynamics can arise when mixing two odorants. Our data show that temporal dynamics of odorant responses are able to significantly enhance the coding capacity of olfactory sensory systems.

Glomerular and Mitral-Granule Cell Microcircuits Coordinate Temporal and Spatial Information Processing in the Olfactory Bulb

The olfactory bulb processes inputs from olfactory receptor neurons (ORNs) through two levels: the glomerular layer at the site of input, and the granule cell level at the site of output to the olfactory cortex. The sequence of action of these two levels has not yet been examined. We analyze this issue using a novel computational framework that is scaled up, in three-dimensions (3D), with realistic representations of the interactions between layers, activated by simulated natural odors, and constrained by experimental and theoretical analyses. We suggest that the postulated functions of glomerular circuits have as their primary role transforming a complex and disorganized input into a contrast-enhanced and normalized representation, but cannot provide for synchronization of the distributed glomerular outputs. By contrast, at the granule cell layer, the dendrodendritic interactions mediate temporal decorrelation, which we show is dependent on the preceding contrast enhancement by the glomerular layer. The results provide the first insights into the successive operations in the olfactory bulb, and demonstrate the significance of the modular organization around glomeruli. This layered organization is especially important for natural odor inputs, because they activate many overlapping glomeruli.

Space Takes Time: Concentration Dependent Output Codes from Primary Olfactory Networks Rapidly Provide Additional Information at Defined Discrimination Thresholds

As odor concentration increases, primary olfactory network representations expand in spatial distribution, temporal complexity and duration. However, the direct relationship between concentration dependent odor representations and the psychophysical thresholds of detection and discrimination is poorly understood. This relationship is absolutely critical as thresholds signify transition points whereby representations become meaningful to the organism. Here, we matched stimulus protocols for psychophysical assays and intracellular recordings of antennal lobe (AL) projection neurons (PNs) in the moth Manduca sexta to directly compare psychophysical thresholds and the output representations they elicit. We first behaviorally identified odor detection and discrimination thresholds across an odor dilution series for a panel of structurally similar odors. We then characterized spatiotemporal spiking patterns across a population of individually filled and identified AL PNs in response to those odors at concentrations below, at, and above identified thresholds. Using spatial and spatiotemporal based analyses we observed that each stimulus produced unique representations, even at sub-threshold concentrations. Mean response latency did not decrease and the percent glomerular activation did not increase with concentration until undiluted odor. Furthermore, correlations between spatial patterns for odor decreased, but only significantly with undiluted odor. Using time-integrated Euclidean distance (ED) measures, we determined that added spatiotemporal information was present at the discrimination but not detection threshold. This added information was evidenced by an increase in integrated distance between the sub-detection and discrimination threshold concentrations (of the same odor) that was not present in comparison of the sub-detection and detection threshold. After consideration of delays for information to reach the AL we find that it takes ~120-140 ms for the AL to output identity information. Overall, these results demonstrate that as odor concentration increases, added information about odor identity is embedded in the spatiotemporal representation at the discrimination threshold.

Olfactory coding in the honeybee lateral horn

Olfactory systems dynamically encode odor information in the nervous system. Insects constitute a well-established model for the study of the neural processes underlying olfactory perception. In insects, odors are detected by sensory neurons located in the antennae, whose axons project to a primary processing center, the antennal lobe. There, the olfactory message is reshaped and further conveyed to higher-order centers, the mushroom bodies and the lateral horn. Previous work has intensively analyzed the principles of olfactory processing in the antennal lobe and in the mushroom bodies. However, how the lateral horn participates in olfactory coding remains comparatively more enigmatic. We studied odor representation at the input to the lateral horn of the honeybee, a social insect that relies on both floral odors for foraging and pheromones for social communication. Using in vivo calcium imaging, we show consistent neural activity in the honeybee lateral horn upon stimulation with both floral volatiles and social pheromones. Recordings reveal odor-specific maps in this brain region as stimulations with the same odorant elicit more similar spatial activity patterns than stimulations with different odorants. Odor-similarity relationships are mostly conserved between antennal lobe and lateral horn, so that odor maps recorded in the lateral horn allow predicting bees' behavioral responses to floral odorants. In addition, a clear segregation of odorants based on pheromone type is found in both structures. The lateral horn thus contains an odor-specific map with distinct representations for the different bee pheromones, a prerequisite for eliciting specific behaviors.

Data-driven honeybee antennal lobe model suggests how stimulus-onset asynchrony can aid odour segregation

Insects have a remarkable ability to identify and track odour sources in multi-odour backgrounds. Recent behavioural experiments show that this ability relies on detecting millisecond stimulus asynchronies between odourants that originate from different sources. Honeybees, Apis mellifera, are able to distinguish mixtures where both odourants arrive at the same time (synchronous mixtures) from those where odourant onsets are staggered (asynchronous mixtures) down to an onset delay of only 6ms. In this paper we explore this surprising ability in a model of the insects' primary olfactory brain area, the antennal lobe. We hypothesize that a winner-take-all inhibitory network of local neurons in the antennal lobe has a symmetry-breaking effect, such that the response pattern in projection neurons to an asynchronous mixture is different from the response pattern to the corresponding synchronous mixture for an extended period of time beyond the initial odourant onset where the two mixture conditions actually differ. The prolonged difference between response patterns to synchronous and asynchronous mixtures could facilitate odoursegregation in downstream circuits of the olfactory pathway. We present a detailed data-driven model of the bee antennal lobe that reproduces a large data set of experimentally observed physiological odour responses, successfully implements the hypothesised symmetry-breaking mechanism and so demonstrates that this mechanism is consistent with our current knowledge of the olfactory circuits in the bee brain. This article is part of a Special Issue entitled Neural Coding 2012.