Fast odor learning improves reliability of odor responses in the locust antennal lobe

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 varying ratios in complex mixtures. Changes in nectar production throughout the day and over the animal's lifetime add to the complexity. The honeybee olfactory system, containing fewer 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 in the AL circuits, but its role in odor learning remains poorly understood. Using a biophysical computational model, tuned by in vivo electrophysiological data, and live imaging of the honeybee's AL, we explored the neural mechanisms of plasticity in the AL. Our findings revealed that when trained with a set of rewarded and unrewarded odors, the AL inhibitory network suppresses responses to 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 neural network performing an odor categorization task revealed a similar mechanism for contrast enhancement. Our study provides insights into how inhibitory plasticity in the early olfactory network reshapes the coding for efficient learning of complex odors.

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 varying 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 fewer than 1,000 principal neurons in the early olfactory relay, the antennal lobe (AL), must learn to associate diverse volatile blends with rewards. Previous studies identified plasticity in the AL circuits, but its role in odor learning remains poorly understood. Using a biophysical computational network model, tuned by in vivo electrophysiological data, and live imaging of the honeybee's AL, we explored 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 neural network performing an odor categorization task revealed a similar mechanism for contrast enhancement. Our study provides insights into how inhibitory plasticity in the early olfactory network reshapes the coding for efficient learning of complex odors.

Stimulus-repetition effects on macaque V1 and V4 microcircuits explain gamma-synchronization increase

Under natural conditions, animals repeatedly encounter the same visual scenes, objects or patterns repeatedly. These repetitions constitute statistical regularities, which the brain captures in an internal model through learning. A signature of such learning in primate visual areas V1 and V4 is the gradual strengthening of gamma synchronization. We used a V1-V4 Dynamic Causal Model (DCM) to explain visually induced responses in early and late epochs from a sequence of several hundred grating presentations. The DCM reproduced the empirical increase in local and inter-areal gamma synchronization, revealing specific intrinsic connectivity effects that could explain the phenomenon. In a sensitivity analysis, the isolated modulation of several connection strengths induced increased gamma. Comparison of alternative models showed that empirical gamma increases are better explained by (1) repetition effects in both V1 and V4 intrinsic connectivity (alone or together with extrinsic) than in extrinsic connectivity alone, and (2) repetition effects on V1 and V4 population input rather than output gain. The best input gain model included effects in V1 granular and superficial excitatory populations and in V4 granular and deep excitatory populations. Our findings are consistent with gamma reflecting bottom-up signal precision, which increases with repetition and, therefore, with predictability and learning.

Chronic exposure to odors at naturally occurring concentrations triggers limited plasticity in early stages of Drosophila olfactory processing

In insects and mammals, olfactory experience in early life alters olfactory behavior and function in later life. In the vinegar fly Drosophila, flies chronically exposed to a high concentration of a monomolecular odor exhibit reduced behavioral aversion to the familiar odor when it is reencountered. This change in olfactory behavior has been attributed to selective decreases in the sensitivity of second-order olfactory projection neurons (PNs) in the antennal lobe that respond to the overrepresented odor. However, since odorant compounds do not occur at similarly high concentrations in natural sources, the role of odor experience-dependent plasticity in natural environments is unclear. Here, we investigated olfactory plasticity in the antennal lobe of flies chronically exposed to odors at concentrations that are typically encountered in natural odor sources. These stimuli were chosen to each strongly and selectively excite a single class of primary olfactory receptor neuron (ORN), thus facilitating a rigorous assessment of the selectivity of olfactory plasticity for PNs directly excited by overrepresented stimuli. Unexpectedly, we found that chronic exposure to three such odors did not result in decreased PN sensitivity but rather mildly increased responses to weak stimuli in most PN types. Odor-evoked PN activity in response to stronger stimuli was mostly unaffected by odor experience. When present, plasticity was observed broadly in multiple PN types and thus was not selective for PNs receiving direct input from the chronically active ORNs. We further investigated the DL5 olfactory coding channel and found that chronic odor-mediated excitation of its input ORNs did not affect PN intrinsic properties, local inhibitory innervation, ORN responses or ORN-PN synaptic strength; however, broad-acting lateral excitation evoked by some odors was increased. These results show that PN odor coding is only mildly affected by strong persistent activation of a single olfactory input, highlighting the stability of early stages of insect olfactory processing to significant perturbations in the sensory environment.

Harnessing insect olfactory neural circuits for detecting and discriminating human cancers

There is overwhelming evidence that presence of cancer alters cellular metabolic processes, and these changes are manifested in emitted volatile organic compound (VOC) compositions of cancer cells. Here, we take a novel forward engineering approach by developing an insect olfactory neural circuit-based VOC sensor for cancer detection. We obtained oral cancer cell culture VOC-evoked extracellular neural responses from in vivo insect (locust) antennal lobe neurons. We employed biological neural computations of the antennal lobe circuitry for generating spatiotemporal neuronal response templates corresponding to each cell culture VOC mixture, and employed these neuronal templates to distinguish oral cancer cell lines (SAS, Ca9-22, and HSC-3) vs. a non-cancer cell line (HaCaT). Our results demonstrate that three different human oral cancers can be robustly distinguished from each other and from a non-cancer oral cell line. By using high-dimensional population neuronal response analysis and leave-one-trial-out methodology, our approach yielded high classification success for each cell line tested. Our analyses achieved 76-100% success in identifying cell lines by using the population neural response (n = 194) collected for the entire duration of the cell culture study. We also demonstrate this cancer detection technique can distinguish between different types of oral cancers and non-cancer at different time-matched points of growth. This brain-based cancer detection approach is fast as it can differentiate between VOC mixtures within 250 ms of stimulus onset. Our brain-based cancer detection system comprises a novel VOC sensing methodology that incorporates entire biological chemosensory arrays, biological signal transduction, and neuronal computations in a form of a forward-engineered technology for cancer VOC detection.

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

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

Experience-dependent plasticity modulates ongoing activity in the antennal lobe and enhances odor representations

Ongoing neural activity has been observed across several brain regions and is thought to reflect the internal state of the brain. Yet, it is important to understand how ongoing neural activity interacts with sensory experience and shapes sensory representations. Here, we show that the projection neurons of the fruit fly antennal lobe exhibit spatiotemporally organized ongoing activity. After repeated exposure to odors, we observe a gradual and cumulative decrease in the amplitude and number of calcium events occurring in the absence of odor stimulation, as well as a reorganization of correlations between olfactory glomeruli. Accompanying these plastic changes, we find that repeated odor experience decreases trial-to-trial variability and enhances the specificity of odor representations. Our results reveal an odor-experience-dependent modulation of ongoing and sensory-evoked activity at peripheral levels of the fruit fly olfactory system.

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The fruit fly antennal lobe exhibits spatiotemporally organized ongoing activity

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Repeated odor experience decreases the amplitude and number of ongoing calcium events

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Odor experience enhances the robustness and the specificity of odor representations

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Representations of different odors become more dissimilar upon repeated exposure

Stimulus-specific plasticity in human visual gamma-band activity and functional connectivity

Under natural conditions, the visual system often sees a given input repeatedly. This provides an opportunity to optimize processing of the repeated stimuli. Stimulus repetition has been shown to strongly modulate neuronal-gamma band synchronization, yet crucial questions remained open. Here we used magnetoencephalography in 30 human subjects and find that gamma decreases across ≈10 repetitions and then increases across further repetitions, revealing plastic changes of the activated neuronal circuits. Crucially, increases induced by one stimulus did not affect responses to other stimuli, demonstrating stimulus specificity. Changes partially persisted when the inducing stimulus was repeated after 25 minutes of intervening stimuli. They were strongest in early visual cortex and increased interareal feedforward influences. Our results suggest that early visual cortex gamma synchronization enables adaptive neuronal processing of recurring stimuli. These and previously reported changes might be due to an interaction of oscillatory dynamics with established synaptic plasticity mechanisms.

Self-Organized Structuring of Recurrent Neuronal Networks for Reliable Information Transmission

Simple Summary

Information processing in the brain takes places at multiple stages, each of which is a local network of neurons. The long-range connections between these network stages are sparse and do not change over time. Thus, within each stage information arrives at a sparse subset of input neurons and must be routed to a sparse subset of output neurons. In this theoretical work, we investigate how networks achieve this routing in a self-organized manner without losing information. We show that biologically inspired self-organization entails that input information is distributed to all neurons in the network by strengthening many synapses in the local networks. Thus, after successful self-organization, input information can be read out and decoded from a small number of outputs. We also show that this way of self-organization can still be more energy efficient than creating more long-range in- and output connections.

Abstract

Our brains process information using a layered hierarchical network architecture, with abundant connections within each layer and sparse long-range connections between layers. As these long-range connections are mostly unchanged after development, each layer has to locally self-organize in response to new inputs to enable information routing between the sparse in- and output connections. Here we demonstrate that this can be achieved by a well-established model of cortical self-organization based on a well-orchestrated interplay between several plasticity processes. After this self-organization, stimuli conveyed by sparse inputs can be rapidly read out from a layer using only very few long-range connections. To achieve this information routing, the neurons that are stimulated form feed-forward projections into the unstimulated parts of the same layer and get more neurons to represent the stimulus. Hereby, the plasticity processes ensure that each neuron only receives projections from and responds to only one stimulus such that the network is partitioned into parts with different preferred stimuli. Along this line, we show that the relation between the network activity and connectivity self-organizes into a biologically plausible regime. Finally, we argue how the emerging connectivity may minimize the metabolic cost for maintaining a network structure that rapidly transmits stimulus information despite sparse input and output connectivity.

Spatial, but not temporal, aspects of orientation are controlled by the fine-scale distribution of chemical cues in turbulent odor plumes

Orientation within turbulent odor plumes occurs across a vast range of spatial and temporal scales. From salmon homing across featureless oceans to microbes forming reproductive spores, the extraction of spatial and temporal information from chemical cues is a common sensory phenomenon. Yet, given the difficulty of quantifying chemical cues at the spatial and temporal scales used by organisms, discovering what aspects of chemical cues control orientation behavior has remained elusive. In this study, we placed electrochemical sensors on the carapace of orienting crayfish and measured, with fast temporal rates and small spatial scales, the concentration fluctuations arriving at the olfactory appendages during orientation. Our results show that the spatial aspects of orientation (turning and heading angles) are controlled by the temporal aspects of odor cues.

Adaptive temporal processing of odor stimuli

The olfactory system translates chemical signals into neuronal signals that inform behavioral decisions of the animal. Odors are cues for source identity, but if monitored long enough, they can also be used to localize the source. Odor representations should therefore be robust to changing conditions and flexible in order to drive an appropriate behavior. In this review, we aim at discussing the main computations that allow robust and flexible encoding of odor information in the olfactory neural pathway.

Odor tracking in aquatic organisms: the importance of temporal and spatial intermittency of the turbulent plume

In aquatic and terrestrial environments, odorants are dispersed by currents that create concentration distributions that are spatially and temporally complex. Animals navigating in a plume must therefore rely upon intermittent, and time-varying information to find the source. Navigation has typically been studied as a spatial information problem, with the aim of movement towards higher mean concentrations. However, this spatial information alone, without information of the temporal dynamics of the plume, is insufficient to explain the accuracy and speed of many animals tracking odors. Recent studies have identified a subpopulation of olfactory receptor neurons (ORNs) that consist of intrinsically rhythmically active 'bursting' ORNs (bORNs) in the lobster, Panulirus argus. As a population, bORNs provide a neural mechanism dedicated to encoding the time between odor encounters. Using a numerical simulation of a large-scale plume, the lobster is used as a framework to construct a computer model to examine the utility of intermittency for orienting within a plume. Results show that plume intermittency is reliably detectable when sampling simulated odorants on the order of seconds, and provides the most information when animals search along the plume edge. Both the temporal and spatial variation in intermittency is predictably structured on scales relevant for a searching animal that encodes olfactory information utilizing bORNs, and therefore is suitable and useful as a navigational cue.

Neural Circuit Dynamics for Sensory Detection

We consider the question of how sensory networks enable the detection of sensory stimuli in a combinatorial coding space. We are specifically interested in the olfactory system, wherein recent experimental studies have reported the existence of rich, enigmatic response patterns associated with stimulus onset and offset. This study aims to identify the functional relevance of such response patterns (i.e., what benefits does such neural activity provide in the context of detecting stimuli in a natural environment). We study this problem through the lens of normative, optimization-based modeling. Here, we define the notion of a low-dimensional latent representation of stimulus identity, which is generated through action of the sensory network. The objective of our optimization framework is to ensure high-fidelity tracking of a nominal representation in this latent space in an energy-efficient manner. It turns out that the optimal motifs emerging from this framework possess morphologic similarity with prototypical onset and offset responses observed in vivo in locusts (Schistocerca americana) of either sex. Furthermore, this objective can be exactly achieved by a network with reciprocal excitatory-inhibitory competitive dynamics, similar to interactions between projection neurons and local neurons in the early olfactory system of insects. The derived model also makes several predictions regarding maintenance of robust latent representations in the presence of confounding background information and trade-offs between the energy of sensory activity and resultant behavioral measures such as speed and accuracy of stimulus detection.SIGNIFICANCE STATEMENT A key area of study in olfactory coding involves understanding the transformation from high-dimensional sensory stimulus to low-dimensional decoded representation. Here, we examine not only the dimensionality reduction of this mapping but also its temporal dynamics, with specific focus on stimuli that are temporally continuous. Through optimization-based synthesis, we examine how sensory networks can track representations without prior assumption of discrete trial structure. We show that such tracking can be achieved by canonical network architectures and dynamics, and that the resulting responses resemble observations from neurons in the insect olfactory system. Thus, our results provide hypotheses regarding the functional role of olfactory circuit activity at both single neuronal and population scales.

Neuroimaging results suggest the role of prediction in cross-domain priming

The repetition of a stimulus leads to shorter reaction times as well as to the reduction of neural activity. Previous encounters with closely related stimuli (primes) also lead to faster and often to more accurate processing of subsequent stimuli (targets). For instance, if the prime is a name, and the target is a face, the recognition of a persons’ face is facilitated by prior presentation of his/her name. A possible explanation for this phenomenon is that the prime allows predicting the occurrence of the target. To the best of our knowledge, so far, no study tested the neural correlates of such cross-domain priming with fMRI. To fill this gap, here we used names of famous persons as primes, and congruent or incongruent faces as targets. We found that congruent primes not only reduced RT, but also lowered the BOLD signal in bilateral fusiform (FFA) and occipital (OFA) face areas. This suggests that semantic information affects not only behavioral performance, but also neural responses in relatively early processing stages of the occipito-temporal cortex. We interpret our results in the framework of predictive coding theories.

Using Biophysical Models to Understand the Effect of tDCS on Neurorehabilitation: Searching for Optimal Covariates to Enhance Poststroke Recovery

Stroke is a leading cause of worldwide disability, and up to 75% of survivors suffer from some degree of arm paresis. Recently, rehabilitation of stroke patients has focused on recovering motor skills by taking advantage of use-dependent neuroplasticity, where high-repetition of goal-oriented movement is at times combined with non-invasive brain stimulation, such as transcranial direct current stimulation (tDCS). Merging the two approaches is thought to provide outlasting clinical gains, by enhancing synaptic plasticity and motor relearning in the motor cortex primary area. However, this general approach has shown mixed results across the stroke population. In particular, stroke location has been found to correlate with the likelihood of success, which suggests that different patients might require different protocols. Understanding how motor rehabilitation and stimulation interact with ongoing neural dynamics is crucial to optimize rehabilitation strategies, but it requires theoretical and computational models to consider the multiple levels at which this complex phenomenon operate. In this work, we argue that biophysical models of cortical dynamics are uniquely suited to address this problem. Specifically, biophysical models can predict treatment efficacy by introducing explicit variables and dynamics for damaged connections, changes in neural excitability, neurotransmitters, neuromodulators, plasticity mechanisms, and repetitive movement, which together can represent brain state, effect of incoming stimulus, and movement-induced activity. In this work, we hypothesize that effects of tDCS depend on ongoing neural activity and that tDCS effects on plasticity may be also related to enhancing inhibitory processes. We propose a model design for each step of this complex system, and highlight strengths and limitations of the different modeling choices within our approach. Our theoretical framework proposes a change in paradigm, where biophysical models can contribute to the future design of novel protocols, in which combined tDCS and motor rehabilitation strategies are tailored to the ongoing dynamics that they interact with, by considering the known biophysical factors recruited by such protocols and their interaction.

Rhythm Generation and Rhythm Perception in Insects: The Evolution of Synchronous Choruses

Insect sounds dominate the acoustic environment in many natural habitats such as rainforests or meadows on a warm summer day. Among acoustic insects, usually males are the calling sex; they generate signals that transmit information about the species-identity, sex, location, or even sender quality to conspecific receivers. Males of some insect species generate signals at distinct time intervals, and other males adjust their own rhythm relative to that of their conspecific neighbors, which leads to fascinating acoustic group displays. Although signal timing in a chorus can have important consequences for the calling energetics, reproductive success and predation risk of individuals, still little is known about the selective forces that favor the evolution of insect choruses. Here, we review recent advances in our understanding of the neuronal network responsible for acoustic pattern generation of a signaler, and pattern recognition in receivers. We also describe different proximate mechanisms that facilitate the synchronous generation of signals in a chorus and provide examples of suggested hypotheses to explain the evolution of chorus synchrony in insects. Some hypotheses are related to sexual selection and inter-male cooperation or competition, whereas others refer to the selection pressure exerted by natural predators. In this article, we summarize the results of studies that address chorus synchrony in the tropical katydid Mecopoda elongata, where some males persistently signal as followers although this reduces their mating success.

Neural Encoding of Odors during Active Sampling and in Turbulent Plumes

Sensory inputs are often fluctuating and intermittent, yet animals reliably utilize them to direct behavior. Here we ask how natural stimulus fluctuations influence the dynamic neural encoding of odors. Using the locust olfactory system, we isolated two main causes of odor intermittency: chaotic odor plumes and active sampling behaviors. Despite their irregularity, chaotic odor plumes still drove dynamic neural response features including the synchronization, temporal patterning, and short-term plasticity of spiking in projection neurons, enabling classifier-based stimulus identification and activating downstream decoders (Kenyon cells). Locusts can also impose odor intermittency through active sampling movements with their unrestrained antennae. Odors triggered immediate, spatially targeted antennal scanning that, paradoxically, weakened individual neural responses. However, these frequent but weaker responses were highly informative about stimulus location. Thus, not only are odor-elicited dynamic neural responses compatible with natural stimulus fluctuations and important for stimulus identification, but locusts actively increase intermittency, possibly to improve stimulus localization.

Trade-off between information format and capacity in the olfactory system

As information about the sensory environment passes between layers within the nervous system, the format of the information often changes. To examine how information format affects the capacity of neurons to represent stimuli, we measured the rate of information transmission in olfactory neurons in intact, awake locusts (Schistocerca americana) while pharmacologically manipulating patterns of correlated neuronal activity. Blocking the periodic inhibition underlying odor-elicited neural oscillatory synchronization increased information transmission rates. This suggests oscillatory synchrony, which serves other information processing roles, comes at a cost to the speed with which neurons can transmit information. Our results provide an example of a trade-off between benefits and costs in neural information processing.

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.

Moving sensory adaptation beyond suppressive effects in single neurons

How an object is perceived depends on the temporal context in which it is encountered. Sensory signals in the brain also depend on temporal context, a phenomenon often referred to as adaptation. Traditional descriptions of adaptation effects emphasize various forms of response fatigue in single neurons, which grow in strength with exposure to a stimulus. Recent work on vision, and other sensory modalities, has shown that this description has substantial shortcomings. Here we review our emerging understanding of how adaptation alters the balance between excitatory and suppressive signals, how effects depend on adaptation duration, and how adaptation influences representations that are distributed within and across multiple brain structures. This work points to a sophisticated set of mechanisms for adjusting to recent sensory experience, and suggests new avenues for understanding their function.

Heterosynaptic plasticity prevents runaway synaptic dynamics

Spike timing-dependent plasticity (STDP) and other conventional Hebbian-type plasticity rules are prone to produce runaway dynamics of synaptic weights. Once potentiated, a synapse would have higher probability to lead to spikes and thus to be further potentiated, but once depressed, a synapse would tend to be further depressed. The runaway synaptic dynamics can be prevented by precisely balancing STDP rules for potentiation and depression; however, experimental evidence shows a great variety of potentiation and depression windows and magnitudes. Here we show that modifications of synapses to layer 2/3 pyramidal neurons from rat visual and auditory cortices in slices can be induced by intracellular tetanization: bursts of postsynaptic spikes without presynaptic stimulation. Induction of these heterosynaptic changes depended on the rise of intracellular calcium, and their direction and magnitude correlated with initial state of release mechanisms. We suggest that this type of plasticity serves as a mechanism that stabilizes the distribution of synaptic weights and prevents their runaway dynamics. To test this hypothesis, we develop a cortical neuron model implementing both homosynaptic (STDP) and heterosynaptic plasticity with properties matching the experimental data. We find that heterosynaptic plasticity effectively prevented runaway dynamics for the tested range of STDP and input parameters. Synaptic weights, although shifted from the original, remained normally distributed and nonsaturated. Our study presents a biophysically constrained model of how the interaction of different forms of plasticity--Hebbian and heterosynaptic--may prevent runaway synaptic dynamics and keep synaptic weights unsaturated and thus capable of further plastic changes and formation of new memories.

Self body-size perception in an insect

Animals negotiating complex environments encounter a wide range of obstacles of different shapes and sizes. It is greatly beneficial for the animal to react to such obstacles in a precise, context-specific manner, in order to avoid harm or even simply to minimize energy expenditure. An essential key challenge is, therefore, an estimation of the animal's own physical characteristics, such as body size. A further important aspect of self body-size perception (or SBSP) is the need to update it in accordance with changes in the animal's size and proportions. Despite the major role of SBSP in functional behavior, little is known about if and how it is mediated. Here, we demonstrate that insects are also capable of self perception of body size and that this is a vital factor in allowing them to adjust their behavior following the sudden and dramatic growth associated with periodic molting. We reveal that locusts' SBSP is strongly correlated with their body size. However, we show that the dramatic change in size accompanying adult emergence is not sufficient to create a new and updated SBSP. Rather, this is created and then consolidated only following the individuals' experience and interaction with the physical environment. Behavioral or pharmacological manipulations can both result in maintenance of the old larval SBSP. Our results emphasize the importance of learning and memory-related processes in the development and update of SBSP, and highlight the advantage of insects as good models for a detailed study on the neurobiological and molecular aspects of SBSP.

Plasticity of recurrent inhibition in the Drosophila antennal lobe

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

Repetition Priming and Repetition Suppression: A Case for Enhanced Efficiency Through Neural Synchronization

Stimulus repetition in identification tasks leads to improved behavioral performance ("repetition priming") but attenuated neural responses ("repetition suppression") throughout task-engaged cortical regions. While it's clear that this pervasive brain-behavior relationship reflects some form of improved processing efficiency, the exact form that it takes remains elusive. In this Discussion Paper, we review four different theoretical proposals that have the potential to link repetition suppression and priming, with a particular focus on a proposal that stimulus repetition affects improved efficiency through enhanced neural synchronization. We argue that despite exciting recent work on the role of neural synchronization in cognitive processes such as attention and perception, similar studies in the domain of learning and memory - and priming, in particular - have been lacking. We emphasize the need for new studies with adequate spatiotemporal resolution, formulate several novel predictions, and discuss our ongoing efforts to disentangle the current proposals.

Repetition priming and repetition suppression: Multiple mechanisms in need of testing

In our Discussion Paper, we reviewed four theoretical proposals that have the potential to link the neural and behavioral phenomena of Repetition Suppression and Repetition Priming. We argued that among these proposals, the Synchrony and Bayesian Explaining Away models appear to be the most promising in addressing existing data, and we articulated a series of predictions to distinguish between them. The commentaries have helped to clarify some of these predictions, have highlighted additional evidence supporting the Facilitation and Sharpening models, and have emphasized dissociations by repetition lag and brain location. Our reply addresses these issues in turn, and we argue that progress will require the testing of Repetition Suppression, changes in neural tuning, and changes in synchronization throughout the brain and over a variety of lags and task contexts.

Insect olfactory coding and memory at multiple timescales

Insects can learn, allowing them great flexibility for locating seasonal food sources and avoiding wily predators. Because insects are relatively simple and accessible to manipulation, they provide good experimental preparations for exploring mechanisms underlying sensory coding and memory. Here we review how the intertwining of memory with computation enables the coding, decoding, and storage of sensory experience at various stages of the insect olfactory system. Individual parts of this system are capable of multiplexing memories at different timescales, and conversely, memory on a given timescale can be distributed across different parts of the circuit. Our sampling of the olfactory system emphasizes the diversity of memories, and the importance of understanding these memories in the context of computations performed by different parts of a sensory system.

Using the structure of inhibitory networks to unravel mechanisms of spatiotemporal patterning

Neuronal networks exhibit a rich dynamical repertoire, a consequence of both the intrinsic properties of neurons and the structure of the network. It has been hypothesized that inhibitory interneurons corral principal neurons into transiently synchronous ensembles that encode sensory information and subserve behavior. How does the structure of the inhibitory network facilitate such spatiotemporal patterning? We established a relationship between an important structural property of a network, its colorings, and the dynamics it constrains. Using a model of the insect antennal lobe, we show that our description allows the explicit identification of the groups of inhibitory interneurons that switch, during odor stimulation, between activity and quiescence in a coordinated manner determined by features of the network structure. This description optimally matches the perspective of the downstream neurons looking for synchrony in ensembles of presynaptic cells and allows a low-dimensional description of seemingly complex high-dimensional network activity.

Behavioral and neurophysiological responses of an insect to changing ratios of constituents in host plant-derived volatile mixtures

Ratios of compounds in host plant odors fluctuate with the phenological stage of the plant. In the present study, we investigated the effect of changing ratios of host plant volatile constituents on herbivore insect attraction and olfactory information processing. We tested a synthetic mixture of bioactive peach shoot volatiles with different concentrations of one of the mixture constituents, benzonitrile, on oriental fruit moth Cydia (=Grapholita) molesta females. Y-tube olfactometer bioassays showed that female attraction to the mixture was maintained while increasing the benzonitrile level up to 100 times. Further increases led to behaviorally ineffective mixtures. Then, we recorded odor-evoked neural activity patterns in the antennal lobes, the main olfactory center of the brain, using calcium imaging. Benzonitrile-containing mixtures elicited strong activation in two glomeruli, which were found to process mixture-related information in specific ways. Activation in one glomerulus directly paralleled behavioral effects of the different ratios tested whereas a deviating pattern was noted in the other glomerulus. Our results indicate that the ratio of constituents in a volatile mixture can be varied to a certain degree without reducing female attraction. Thus, volatile blends in nature might vary quantitatively within a certain range without affecting odor-guided host location. Neurophysiological results showed that the processing of mixture-related information inside the antennal lobes is not uniform across glomeruli. Thus, final processing of this information probably takes place in higher-order brain centers.

Sensory representation and learning-related plasticity in mushroom body extrinsic feedback neurons of the protocerebral tract

Gamma-aminobutyric acid immunoreactive feedback neurons of the protocerebral tract are a major component of the honeybee mushroom body. They have been shown to be subject to learning-related plasticity and provide putative inhibitory input to Kenyon cells and the pedunculus extrinsic neuron, PE1. We hypothesize, that learning-related modulation in these neurons is mediated by varying the amount of inhibition provided by feedback neurons. We performed Ca(2+) imaging recordings of populations of neurons of the protocerebral-calycal tract (PCT) while the bees were conditioned in an appetitive olfactory paradigm and their behavioral responses were quantified using electromyographic recordings from M17, the muscle which controls the proboscis extension response. The results corroborate findings from electrophysiological studies showing that PCT neurons respond to sucrose and odor stimuli. The odor responses are concentration dependent. Odor and sucrose responses are modulated by repeated stimulus presentations. Furthermore, animals that learned to associate an odor with sucrose reward responded to the repeated presentations of the rewarded odor with less depression than they did to an unrewarded and a control odor.

Mechanisms explaining transitions between tonic and phasic firing in neuronal populations as predicted by a low dimensional firing rate model

Several firing patterns experimentally observed in neural populations have been successfully correlated to animal behavior. Population bursting, hereby regarded as a period of high firing rate followed by a period of quiescence, is typically observed in groups of neurons during behavior. Biophysical membrane-potential models of single cell bursting involve at least three equations. Extending such models to study the collective behavior of neural populations involves thousands of equations and can be very expensive computationally. For this reason, low dimensional population models that capture biophysical aspects of networks are needed. The present paper uses a firing-rate model to study mechanisms that trigger and stop transitions between tonic and phasic population firing. These mechanisms are captured through a two-dimensional system, which can potentially be extended to include interactions between different areas of the nervous system with a small number of equations. The typical behavior of midbrain dopaminergic neurons in the rodent is used as an example to illustrate and interpret our results. The model presented here can be used as a building block to study interactions between networks of neurons. This theoretical approach may help contextualize and understand the factors involved in regulating burst firing in populations and how it may modulate distinct aspects of behavior.

Object repetition leads to local increases in the temporal coordination of neural responses

Experience with visual objects leads to later improvements in identification speed and accuracy ("repetition priming"), but generally leads to reductions in neural activity in single-cell recording studies in animals and fMRI studies in humans. Here we use event-related, source-localized MEG (ER-SAM) to evaluate the possibility that neural activity changes related to priming in occipital, temporal, and prefrontal cortex correspond to more temporally coordinated and synchronized activity, reflected in local increases in the amplitude of low-frequency activity fluctuations (i.e. evoked power) that are time-locked to stimulus onset. Subjects (N = 17) identified pictures of objects that were either novel or repeated during the session. Tests in two separate low-frequency bands (theta/alpha: 5-15 Hz; beta: 15-35 Hz) revealed increases in evoked power (5-15 Hz) for repeated stimuli in the right fusiform gyrus, with the earliest significant increases observed 100-200 ms after stimulus onset. Increases with stimulus repetition were also observed in striate/extrastriate cortex (15-35 Hz) by 200-300 ms post-stimulus, along with a trend for a similar pattern in right lateral prefrontal cortex (5-15 Hz). Our results suggest that experience-dependent reductions in neural activity may affect improved behavioral identification through more coordinated, synchronized activity at low frequencies, constituting a mechanism for more efficient neural processing with experience.

Early olfactory experience modifies neural activity in the antennal lobe of a social insect at the adult stage

In the antennal lobe (AL), the first olfactory centre of the insect brain, odorants are represented as spatiotemporal patterns of glomerular activity. Whether and how such patterns are modified in the long term after precocious olfactory experiences (i.e. in the first days of adulthood) remains unknown. To address this question, we used in vivo optical imaging of calcium activity in the antennal lobe of 17-day-old honeybees which either experienced an odorant associated with sucrose solution 5-8 days after emergence or were left untreated. In both cases, we imaged neural responses to the learned odor and to three novel odors varying in functional group and carbon-chain length. Two different odor concentrations were used. We also measured behavioral responses of 17-day-old honeybees, treated and untreated, to these stimuli. We show that precocious olfactory experience increased general odor-induced activity and the number of activated glomeruli in the adult AL, but also affected qualitative odor representations, which appeared shifted in the neural space of treated animals relative to control animals. Such effects were not limited to the experienced odor, but were generalized to other perceptually similar odors. A similar trend was found in behavioral experiments, in which increased responses to the learned odor extended to perceptually similar odors in treated bees. Our results show that early olfactory experiences have long-lasting effects, reflected in behavioral responses to odorants and concomitant neural activity in the adult olfactory system.

Reliable and precise neuronal firing during sensory plasticity in superficial layers of primary somatosensory cortex

Neocortical neurons show astonishing variation in the presence and timing of action potentials across stimulus trials, a phenomenon whose function and significance has been the subject of great interest. Here we present data showing that this response variability can be significantly reduced by altered sensory experience. Removal of all but one whisker from the side of the mouse face results in the rapid (within 24 h) potentiation of mean firing rates within the cortical representation of the spared whisker in young postnatal animals (postnatal days 13-16). Analysis of single-unit responses from whisker-spared animals shows that this potentiation can be attributed to an enhancement of trial-to-trial reliability (i.e., reduced response failures), as well as an increase in the mean number of spikes evoked within a successful trial. Changes were confined to superficial layers 2/3 and were not observed in the input layer of the cortex, layer 4. In addition to these changes in firing rates, we also observed profound changes in the precise timing of sensory-evoked responses. Trial-to-trial temporal precision was enhanced and the absolute latency of responses was reduced after single-whisker experience. Enhanced spike-timing precision and trial-to-trial reliability could also be triggered in adolescent animals with longer periods (7 d) of single-whisker experience. These experiments provide a quantitative analysis of how sensory experience can enhance both reliability and temporal precision in neocortical neurons and provide a framework for testing specific hypotheses about the role of response variability in cortical function and the molecular mechanisms underlying this phenomenon.

Chemosensor-driven artificial antennal lobe transient dynamics enable fast recognition and working memory

The speed and accuracy of odor recognition in insects can hardly be resolved by the raw descriptors provided by olfactory receptors alone due to their slow time constant and high variability. The animal overcomes these barriers by means of the antennal lobe (AL) dynamics, which consolidates the classificatory information in receptor signal with a spatiotemporal code that is enriched in odor sensitivity, particularly in its transient. Inspired by this fact, we propose an easily implementable AL-like network and show that it significantly expedites and enhances the identification of odors from slow and noisy artificial polymer sensor responses. The device owes its efficiency to two intrinsic mechanisms: inhibition (which triggers a competition) and integration (due to the dynamical nature of the network). The former functions as a sharpening filter extracting the features of receptor signal that favor odor separation, whereas the latter implements a working memory by accumulating the extracted features in trajectories. This cooperation boosts the odor specificity during the receptor transient, which is essential for fast odor recognition.

Calcium current diversity in physiologically different local interneuron types of the antennal lobe

Behavioral and physiological studies show that neuronal interactions among the glomeruli in the insect antennal lobe (AL) take place during the processing of odor information. These interactions are mediated by a complex network of inhibitory and excitatory local interneurons (LNs) that restructure the olfactory representation in the AL, thereby regulating the tuning profile of projection neurons. In Periplaneta americana, we characterized two LN types with distinctive physiological properties: (1) type I LNs that generated Na(+)-driven action potentials on odor stimulation and exhibited GABA-like immunoreactivity (GLIR) and (2) type II LNs, in which odor stimulation evoked depolarizations, but no Na(+)-driven action potentials (APs). Type II LNs did not express voltage-dependent transient Na(+) currents and accordingly would not trigger transmitter release by Na(+)-driven APs. Ninety percent of type II LNs did not exhibit GLIR. The distinct intrinsic firing properties were reflected in functional parameters of their voltage-activated Ca(2+) currents (I(Ca)). Consistent with graded synaptic release, we found a shift in the voltage for half-maximal activation of I(Ca) to more hyperpolarized membrane potentials in the type II LNs. These marked physiological differences between the two LN types imply consequences for their computational capacity, synaptic output kinetics, and thus their function in the olfactory circuit.

Gamma-aminobutyric acid (GABA)-mediated neural connections in the Drosophila antennal lobe

Inhibitory synaptic connections mediated by gamma-aminobutyric acid (GABA) play important roles in the neural computation of the brain. To obtain a detailed overview of the neural connections mediated by GABA signals, we analyzed the distribution of the cells that produce and receive GABA in the Drosophila adult brain. Relatively small numbers of the cells, which form clusters in several areas of the brain, express the GABA synthesis enzyme Gad1. On the other hand, many cells scattered across the brain express ionotropic GABA(A) receptor subunits (Lcch3 and Rdl) and metabotropic GABA(B) receptor subtypes (GABA-B-R1, -2, and -3). To analyze the expression of these genes in distinct identified cell types, we focused on the antennal lobe, where GABAergic neurons play important roles in odor coding. By combining fluorescent in situ hybridization and immunolabeling against GFP expressed with cell-type-specific GAL4 driver strains, we quantified the percentage of the cells that produce or receive GABA for each cell type. GABA was synthesized in the middle antennocerebral tract (mACT) projection neurons and two types of local neurons. Among them, mACT neurons had few presynaptic sites in the antennal lobe, making the local neurons essentially the sole provider of GABA signals there. On the other hand, not only these local neurons but also all types of projection neurons expressed both ionotropic and metabotropic GABA receptors. Thus, even though inhibitory signals are released from only a few, specific types of local neurons, the signals are read by most of the neurons in the antennal lobe neural circuitry.

A model of stimulus-specific neural assemblies in the insect antennal lobe

It has been proposed that synchronized neural assemblies in the antennal lobe of insects encode the identity of olfactory stimuli. In response to an odor, some projection neurons exhibit synchronous firing, phase-locked to the oscillations of the field potential, whereas others do not. Experimental data indicate that neural synchronization and field oscillations are induced by fast GABA(A)-type inhibition, but it remains unclear how desynchronization occurs. We hypothesize that slow inhibition plays a key role in desynchronizing projection neurons. Because synaptic noise is believed to be the dominant factor that limits neuronal reliability, we consider a computational model of the antennal lobe in which a population of oscillatory neurons interact through unreliable GABA(A) and GABA(B) inhibitory synapses. From theoretical analysis and extensive computer simulations, we show that transmission failures at slow GABA(B) synapses make the neural response unpredictable. Depending on the balance between GABA(A) and GABA(B) inputs, particular neurons may either synchronize or desynchronize. These findings suggest a wiring scheme that triggers stimulus-specific synchronized assemblies. Inhibitory connections are set by Hebbian learning and selectively activated by stimulus patterns to form a spiking associative memory whose storage capacity is comparable to that of classical binary-coded models. We conclude that fast inhibition acts in concert with slow inhibition to reformat the glomerular input into odor-specific synchronized neural assemblies.

Behavioral states, network states, and sensory response variability

We review data demonstrating that single-neuron sensory responses change with the states of the neural networks (indexed in terms of spectral properties of local field potentials) in which those neurons are embedded. We start with broad network changes--different levels of anesthesia and sleep--and then move to studies demonstrating that the sensory response plasticity associated with attention and experience can also be conceptualized as functions of network state changes. This leads naturally to the recent data that can be interpreted to suggest that even brief experience can change sensory responses via changes in network states and that trial-to-trial variability in sensory responses is a nonrandom function of network fluctuations, as well. We suggest that the CNS may have evolved specifically to deal with stimulus variability and that the coupling with network states may be central to sensory processing.

Synaptic learning rules and sparse coding in a model sensory system

Neural circuits exploit numerous strategies for encoding information. Although the functional significance of individual coding mechanisms has been investigated, ways in which multiple mechanisms interact and integrate are not well understood. The locust olfactory system, in which dense, transiently synchronized spike trains across ensembles of antenna lobe (AL) neurons are transformed into a sparse representation in the mushroom body (MB; a region associated with memory), provides a well-studied preparation for investigating the interaction of multiple coding mechanisms. Recordings made in vivo from the insect MB demonstrated highly specific responses to odors in Kenyon cells (KCs). Typically, only a few KCs from the recorded population of neurons responded reliably when a specific odor was presented. Different odors induced responses in different KCs. Here, we explored with a biologically plausible model the possibility that a form of plasticity may control and tune synaptic weights of inputs to the mushroom body to ensure the specificity of KCs' responses to familiar or meaningful odors. We found that plasticity at the synapses between the AL and the MB efficiently regulated the delicate tuning necessary to selectively filter the intense AL oscillatory output and condense it to a sparse representation in the MB. Activity-dependent plasticity drove the observed specificity, reliability, and expected persistence of odor representations, suggesting a role for plasticity in information processing and making a testable prediction about synaptic plasticity at AL-MB synapses.

The way in which the brain encodes, processes, transforms, and stores sensory information is a fundamental question in systems neuroscience. One challenge is to understand how neural oscillations, synchrony, population coding, and sparseness interact in the process of transforming and transferring information. Another question is how synaptic plasticity, the ability of synapses to change their strength, interacts efficiently with these different coding strategies to support learning and information storage. We approached these questions, rarely accessible to direct experimental investigation, in the olfactory system of the locust, a well-studied example. Here, the neurons in the antennal lobe carry neural representations of odor identity using dense, spatially distributed, oscillatory synchronized patterns of neural activity. Odor information cannot be interpreted by considering their activity independently. On the contrary, in the mushroom body—the next processing region, involved in the storage and retrieval of olfactory memories and analogous to the olfactory cortex—odor representations are sparse and carried by more selective neurons. Sparse information coding by ensembles of neurons provides several important advantages including high memory capacity, low overlap between stored objects, and easy information retrieval. How is this sparseness achieved? Here, with a rigorous computational model of the olfactory system, we demonstrate that plasticity at the input afferents to the mushroom body can efficiently mediate the delicate tuning necessary to selectively filter intense sensory input, condensing it to the sparse responses observed in the mushroom body. Our results suggest a general mechanism for plasticity-enabled sparse representations in other sensory systems, such as the visual system. Overall, we illustrate a potential central role for plasticity in the transfer of information across different coding strategies within neural systems.

Dynamic ensemble odor coding in the mammalian olfactory bulb: sensory information at different timescales

Neural firing discharges are often temporally patterned, but it is often ambiguous as to whether the temporal features of these patterns constitute a useful code. Here we show in the mouse olfactory bulb that ensembles of projection neurons respond with complex odor- and concentration-specific dynamic activity sequences developing below and above sniffing frequency. Based on this activity, almost optimal discrimination of presented odors was possible during single sniffs, consistent with reported behavioral data. Within a sniff cycle, slower features of the dynamics alone (>100 ms resolution, including mean firing rate) were sufficient for maximal discrimination. A smaller amount of information was also observed in faster features down to 20-40 ms resolution. Therefore, mitral cell ensemble activity contains information at different timescales that could be separately or complementarily exploited by downstream brain centers to make odor discriminations. Our results also support suggestive analogies in the dynamics of odor representations between insects and mammals.

Sensory processing in the Drosophila antennal lobe increases reliability and separability of ensemble odor representations

Here we describe several fundamental principles of olfactory processing in the Drosophila melanogaster antennal lobe (the analog of the vertebrate olfactory bulb), through the systematic analysis of input and output spike trains of seven identified glomeruli. Repeated presentations of the same odor elicit more reproducible responses in second-order projection neurons (PNs) than in their presynaptic olfactory receptor neurons (ORNs). PN responses rise and accommodate rapidly, emphasizing odor onset. Furthermore, weak ORN inputs are amplified in the PN layer but strong inputs are not. This nonlinear transformation broadens PN tuning and produces more uniform distances between odor representations in PN coding space. In addition, portions of the odor response profile of a PN are not systematically related to their direct ORN inputs, which probably indicates the presence of lateral connections between glomeruli. Finally, we show that a linear discriminator classifies odors more accurately using PN spike trains than using an equivalent number of ORN spike trains.

Adaptive regulation of sparseness by feedforward inhibition

In the mushroom body of insects, odors are represented by very few spikes in a small number of neurons, a highly efficient strategy known as sparse coding. Physiological studies of these neurons have shown that sparseness is maintained across thousand-fold changes in odor concentration. Using a realistic computational model, we propose that sparseness in the olfactory system is regulated by adaptive feedforward inhibition. When odor concentration changes, feedforward inhibition modulates the duration of the temporal window over which the mushroom body neurons may integrate excitatory presynaptic input. This simple adaptive mechanism could maintain the sparseness of sensory representations across wide ranges of stimulus conditions.

Oscillation and coding in a formal neural network considered as a guide for plausible simulations of the insect olfactory system

For the analysis of coding mechanisms in the insect olfactory system, a fully connected network of synchronously updated McCulloch and Pitts neurons (MC-P type) was developed [Quenet, B., Horn, D., 2003. The dynamic neural filter: a binary model of spatio-temporal coding. Neural Comput. 15 (2), 309-329]. Considering the update time as an intrinsic clock, this "Dynamic Neural Filter" (DNF), which maps regions of input space into spatio-temporal sequences of neuronal activity, is able to produce exact binary codes extracted from the synchronized activities recorded at the level of projection neurons (PN) in the locust antennal lobe (AL) in response to different odors [Wehr, M., Laurent, G., 1996. Odor encoding by temporal sequences of firing in oscillating neural assemblies. Nature 384, 162-166]. Here, in a first step, we separate the populations of PN and local inhibitory neurons (LN) and use the DNF as a guide for simulations based on biological plausible neurons (Hodgkin-Huxley: H-H type). We show that a parsimonious network of 10 H-H neurons generates action potentials whose timing represents the required codes. In a second step, we construct a new type of DNF in order to study the population dynamics when different delays are taken into account. We find synaptic matrices which lead to both the emergence of robust oscillations and spatio-temporal patterns, using a formal criterion, based on a Normalized Euclidian Distance (NED), in order to measure the use of the temporal dimension as a coding dimension by the DNF. Similarly to biological PN, the activity of excitatory neurons in the model can be both phase-locked to different cycles of oscillations which remind local field potential (LFP), and nevertheless exhibit dynamic behavior complex enough to be the basis of spatio-temporal codes.

Nitric oxide synthase in crayfish walking leg ganglia: Segmental differences in chemo-tactile centers argue against a generic role in sensory integration

Nitric oxide (NO) is a diffusible signaling molecule with evolutionarily conserved roles in neural plasticity. Prominent expression of NO synthase (NOS) in the primary olfactory centers of mammals and insects lead to the notion of a special role for NO in olfaction. In insects, however, NOS is also strongly expressed in non-olfactory chemo-tactile centers of the thoracic nerve cord. The functional significance of this apparent association with various sensory centers is unclear, as is the extent to which it occurs in other arthropods. We therefore investigated the expression of NOS in the pereopod ganglia of crayfish (Pacifastacus lenisculus and Procambarus clarkii). Conventional NADPH diaphorase (NADPHd) staining after formaldehyde fixation gave poor anatomic detail, whereas fixation in methanol/formalin (MF-NADPHd) resulted in Golgi-like staining, which was supported by immunohistochemistry using NOS antibodies that recognize a 135-kDa protein in crayfish. MF-NADPHd revealed an exceedingly dense innervation of the chemo-tactile centers. As in insects, this innervation was provided by a system of prominent intersegmental neurons. Superimposed on a putatively conserved architecture, however, were pronounced segmental differences. Strong expression occurred only in the anterior three pereopod ganglia, correlating with the presence of claws on pereopods one to three. These clawed pereopods, in addition to their role in locomotion, are crucially involved in feeding, where they serve both sensory and motor functions. Our findings indicate that strong expression of NOS is not a universal feature of primary sensory centers but instead may subserve a specific requirement for sensory plasticity that arises only in particular behavioral contexts.

Information processing in the olfactory systems of insects and vertebrates

Insects and vertebrates separately evolved remarkably similar mechanisms to process olfactory information. Odors are sampled by huge numbers of receptor neurons, which converge type-wise upon a much smaller number of principal neurons within glomeruli. There, odor information is transformed by inhibitory interneuron-mediated, cross-glomerular circuit interactions that impose slow temporal structures and fast oscillations onto the firing patterns of principal neurons. The transformations appear to improve signal-to-noise characteristics, define odor categories, achieve precise odor identification, extract invariant features, and begin the process of sparsening the neural representations of odors for efficient discrimination, memorization, and recognition.

Insect olfactory memory in time and space

Recent studies using functional optical imaging have revealed that cellular memory traces form in different areas of the insect brain after olfactory classical conditioning. These traces are revealed as increased calcium signals or synaptic release from defined neurons, and include a short-lived trace that forms immediately after conditioning in antennal lobe projection neurons, an early trace in dopaminergic neurons, and a medium-term trace in dorsal paired medial neurons. New molecular genetic tools have revealed that for normal behavioral memory performance, synaptic transmission from the mushroom body neurons is required only during retrieval, whereas synaptic transmission from dopaminergic neurons is required at the time of acquisition and synaptic transmission from dorsal paired medial neurons is required during the consolidation period. Such experimental results are helping to identify the types of neurons that participate in olfactory learning and when their participation is required. Olfactory learning often occurs alongside crossmodal interactions of sensory information from other modalities. Recent studies have revealed complex interactions between the olfactory and the visual senses that can occur during olfactory learning, including the facilitation of learning about subthreshold olfactory stimuli due to training with concurrent visual stimuli.