Sparse odor representation and olfactory learning

A temporal channel for information in sparse sensory coding

BACKGROUND

Sparse codes are found in nearly every sensory system, but the role of spike timing in sparse sensory coding is unclear. Here, we use the olfactory system of awake locusts to test whether the timing of spikes in Kenyon cells, a population of neurons that responds sparsely to odors, carries sensory information to and influences the responses of follower neurons.

RESULTS

We characterized two major classes of direct followers of Kenyon cells. With paired intracellular and field potential recordings made during odor presentations, we found that these followers contain information about odor identity in the temporal patterns of their spikes rather than in the spike rate, the spike phase, or the identities of the responsive neurons. Subtly manipulating the relative timing of Kenyon cell spikes with temporally and spatially structured microstimulation reliably altered the response patterns of the followers.

CONCLUSIONS

Our results show that even remarkably sparse spiking responses can provide information through stimulus-specific variations in timing on the order of tens to hundreds of milliseconds and that these variations can determine the responses of downstream neurons. These results establish the importance of spike timing in a sparse sensory code.

Associative learning of classical conditioning as an emergent property of spatially extended spiking neural circuits with synaptic plasticity

Associative learning of temporally disparate events is of fundamental importance for perceptual and cognitive functions. Previous studies of the neural mechanisms of such association have been mainly focused on individual neurons or synapses, often with an assumption that there is persistent neural firing activity that decays slowly. However, experimental evidence supporting such firing activity for associative learning is still inconclusive. Here we present a novel, alternative account of associative learning in the context of classical conditioning, demonstrating that it is an emergent property of a spatially extended, spiking neural circuit with spike-timing dependent plasticity and short term synaptic depression. We show that both the conditioned and unconditioned stimuli can be represented by spike sequences which are produced by wave patterns propagating through the network, and that the interactions of these sequences are timing-dependent. After training, the occurrence of the sequence encoding the conditioned stimulus (CS) naturally regenerates that encoding the unconditioned stimulus (US), therefore resulting in association between them. Such associative learning based on interactions of spike sequences can happen even when the timescale of their separation is significantly larger than that of individual neurons. In particular, our network model is able to account for the temporal contiguity property of classical conditioning, as observed in behavioral studies. We further show that this emergent associative learning in our network model is quite robust to noise perturbations. Our results therefore demonstrate that associative learning of temporally disparate events can happen in a distributed way at the level of neural circuits.

Induction of aversive learning through thermogenetic activation of Kenyon cell ensembles in Drosophila

Drosophila represents a model organism to analyze neuronal mechanisms underlying learning and memory. Kenyon cells of the Drosophila mushroom body are required for associative odor learning and memory retrieval. But is the mushroom body sufficient to acquire and retrieve an associative memory? To answer this question we have conceived an experimental approach to bypass olfactory sensory input and to thermogenetically activate sparse and random ensembles of Kenyon cells directly. We found that if the artifical activation of Kenyon cell ensembles coincides with a salient, aversive stimulus learning was induced. The animals adjusted their behavior in a subsequent test situation and actively avoided reactivation of these Kenyon cells. Our results show that Kenyon cell activity in coincidence with a salient aversive stimulus can suffice to form an associative memory. Memory retrieval is characterized by a closed feedback loop between a behavioral action and the reactivation of sparse ensembles of Kenyon cells.

Peak shift in honey bee olfactory learning

If animals are trained with two similar stimuli such that one is rewarding (S+) and one punishing (S-), then following training animals show a greatest preference not for the S+, but for a novel stimulus that is slightly more different from the S- than the S+ is. This peak shift phenomenon has been widely reported for vertebrates and has recently been demonstrated for bumblebees and honey bees. To explore the nature of peak shift in invertebrates further, here we examined the properties of peak shift in honey bees trained in a free-flight olfactory learning assay. Hexanal and heptanol were mixed in different ratios to create a continuum of odour stimuli. Bees were trained to artificial flowers such that one odour mixture was rewarded with 2 molar sucrose (S+), and one punished with distasteful quinine (S-). After training, bees were given a non-rewarded preference test with five different mixtures of hexanal and heptanol. Following training bees' maximal preference was for an odour mixture slightly more distinct from the S- than the trained S+. This effect was not seen if bees were initially trained with two distinct odours, replicating the classic features of peak shift reported for vertebrates. We propose a conceptual model of how peak shift might occur in honey bees. We argue that peak shift does not require any higher level of processing than the known olfactory learning circuitry of the bee brain and suggest that peak shift is a very general feature of discrimination learning.

Pain-relief learning in flies, rats, and man: basic research and applied perspectives

Memories relating to a painful, negative event are adaptive and can be stored for a lifetime to support preemptive avoidance, escape, or attack behavior. However, under unfavorable circumstances such memories can become overwhelmingly powerful. They may trigger excessively negative psychological states and uncontrollable avoidance of locations, objects, or social interactions. It is therefore obvious that any process to counteract such effects will be of value. In this context, we stress from a basic-research perspective that painful, negative events are "Janus-faced" in the sense that there are actually two aspects about them that are worth remembering: What made them happen and what made them cease. We review published findings from fruit flies, rats, and man showing that both aspects, respectively related to the onset and the offset of the negative event, induce distinct and oppositely valenced memories: Stimuli experienced before an electric shock acquire negative valence as they signal upcoming punishment, whereas stimuli experienced after an electric shock acquire positive valence because of their association with the relieving cessation of pain. We discuss how memories for such punishment- and relief-learning are organized, how this organization fits into the threat-imminence model of defensive behavior, and what perspectives these considerations offer for applied psychology in the context of trauma, panic, and nonsuicidal self-injury.

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

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

Natural image sequences constrain dynamic receptive fields and imply a sparse code

In their natural environment, animals experience a complex and dynamic visual scenery. Under such natural stimulus conditions, neurons in the visual cortex employ a spatially and temporally sparse code. For the input scenario of natural still images, previous work demonstrated that unsupervised feature learning combined with the constraint of sparse coding can predict physiologically measured receptive fields of simple cells in the primary visual cortex. This convincingly indicated that the mammalian visual system is adapted to the natural spatial input statistics. Here, we extend this approach to the time domain in order to predict dynamic receptive fields that can account for both spatial and temporal sparse activation in biological neurons. We rely on temporal restricted Boltzmann machines and suggest a novel temporal autoencoding training procedure. When tested on a dynamic multi-variate benchmark dataset this method outperformed existing models of this class. Learning features on a large dataset of natural movies allowed us to model spatio-temporal receptive fields for single neurons. They resemble temporally smooth transformations of previously obtained static receptive fields and are thus consistent with existing theories. A neuronal spike response model demonstrates how the dynamic receptive field facilitates temporal and population sparseness. We discuss the potential mechanisms and benefits of a spatially and temporally sparse representation of natural visual input.

A spatiotemporal coding mechanism for background-invariant odor recognition

Sensory stimuli evoke neural activity that evolves over time. What features of these spatiotemporal responses allow the robust encoding of stimulus identity in a multistimulus environment? Here we examined this issue in the locust (Schistocerca americana) olfactory system. We found that sensory responses evoked by an odorant (foreground) varied when presented atop or after an ongoing stimulus (background). These inconsistent sensory inputs triggered dynamic reorganization of ensemble activity in the downstream antennal lobe. As a result, partial pattern matches between neural representations encoding the same foreground stimulus across conditions were achieved. The degree and segments of response overlaps varied; however, any overlap observed was sufficient to drive background-independent responses in the downstream neural population. Notably, recognition performance of locusts in behavioral assays correlated well with our physiological findings. Hence, our results reveal how background-independent recognition of odors can be achieved using spatiotemporal patterns of neural activity.

Cellular adaptation facilitates sparse and reliable coding in sensory pathways

Most neurons in peripheral sensory pathways initially respond vigorously when a preferred stimulus is presented, but adapt as stimulation continues. It is unclear how this phenomenon affects stimulus coding in the later stages of sensory processing. Here, we show that a temporally sparse and reliable stimulus representation develops naturally in sequential stages of a sensory network with adapting neurons. As a modeling framework we employ a mean-field approach together with an adaptive population density treatment, accompanied by numerical simulations of spiking neural networks. We find that cellular adaptation plays a critical role in the dynamic reduction of the trial-by-trial variability of cortical spike responses by transiently suppressing self-generated fast fluctuations in the cortical balanced network. This provides an explanation for a widespread cortical phenomenon by a simple mechanism. We further show that in the insect olfactory system cellular adaptation is sufficient to explain the emergence of the temporally sparse and reliable stimulus representation in the mushroom body. Our results reveal a generic, biophysically plausible mechanism that can explain the emergence of a temporally sparse and reliable stimulus representation within a sequential processing architecture.

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

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

Trace conditioning in insects-keep the trace!

Trace conditioning is a form of associative learning that can be induced by presenting a conditioned stimulus (CS) and an unconditioned stimulus (US) following each other, but separated by a temporal gap. This gap distinguishes trace conditioning from classical delay conditioning, where the CS and US overlap. To bridge the temporal gap between both stimuli and to form an association between CS and US in trace conditioning, the brain must keep a neural representation of the CS after its termination-a stimulus trace. Behavioral and physiological studies on trace and delay conditioning revealed similarities between the two forms of learning, like similar memory decay and similar odor identity perception in invertebrates. On the other hand differences were reported also, like the requirement of distinct brain structures in vertebrates or disparities in molecular mechanisms in both vertebrates and invertebrates. For example, in commonly used vertebrate conditioning paradigms the hippocampus is necessary for trace but not for delay conditioning, and Drosophila delay conditioning requires the Rutabaga adenylyl cyclase (Rut-AC), which is dispensable in trace conditioning. It is still unknown how the brain encodes CS traces and how they are associated with a US in trace conditioning. Insects serve as powerful models to address the mechanisms underlying trace conditioning, due to their simple brain anatomy, behavioral accessibility and established methods of genetic interference. In this review we summarize the recent progress in insect trace conditioning on the behavioral and physiological level and emphasize similarities and differences compared to delay conditioning. Moreover, we examine proposed molecular and computational models and reassess different experimental approaches used for trace conditioning.

Invertebrate learning and cognition: relating phenomena to neural substrate

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

The role of the coreceptor Orco in insect olfactory transduction

Insects sense odorants with specialized odorant receptors (ORs). Each antennal olfactory receptor neuron expresses one OR with an odorant binding site together with a conserved coreceptor called Orco which does not bind odorants. Orco is necessary for localization of ORs to dendritic membranes and, thus, is essential for odorant detection. It forms a spontaneously opening cation channel, activated via phosphorylation by protein kinase C. Thereafter, Orco is also activated via cyclic adenosine monophosphate (cAMP). Orco forms homo-as well as heteromers with ORs with unknown stoichiometry. Contradictory publications suggest different mechanisms of olfactory transduction. On the one hand, evidence accumulates for the employment of more than one G protein-coupled olfactory transduction cascade in different insects. On the other hand, results from other studies suggest that the OR-Orco complex functions as an odorant-gated cation channel mediating ionotropic signal transduction. This review analyzes conflicting hypotheses concerning the role of Orco in insect olfactory transduction. In conclusion, in situ studies in hawkmoths falsify the hypothesis that Orco underlies odorant-induced ionotropic signal transduction in all insect species. Instead, Orco forms a metabotropically gated, slow cation channel which controls odorant response threshold and kinetics of the sensory neuron.

Parallel processing via a dual olfactory pathway in the honeybee

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

Reinforcement signalling in Drosophila; dopamine does it all after all

Reinforcement systems are believed to drive synaptic plasticity within neural circuits that store memories. Recent evidence from the fruit fly suggests that anatomically distinct dopaminergic neurons ultimately provide the key instructive signals for both appetitive and aversive learning. This dual role for dopamine overturns the previous model that octopamine signalled reward and dopamine punishment. More importantly, this anatomically segregated double role for dopamine in reward and aversion mirrors that emerging in mammals. Therefore, an antagonistic organization of distinct reinforcing dopaminegic neurons is a conserved feature of brains. It now seems crucial to understand how the dopaminergic neurons are controlled and what the released dopamine does to the underlying circuits to convey opposite valence.

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

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

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

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

Olfactory learning and spike timing dependent plasticity

Hebbian spike-timing-dependent plasticity (STDP) is widely observed in organisms ranging from insects to humans and may provide a cellular mechanism for associative learning. STDP requires a millisecond-scale temporal correlation of spiking activity in pre- and postsynaptic neurons. However, animals can learn to associate a sensory cue and a reward that are presented seconds apart. Thus, for STDP to mediate associative learning, the brain must retain information about the sensory cue as spiking activity until the reinforcement signal arrives. In our recent study, we tested this requirement in the moth Manduca sexta. We characterized the odor responses of Kenyon cells, a key neuronal population for insect olfactory learning, and conditioned moths to associate an odor with a sugar water reward. By varying the amount of temporal overlap between odor-evoked spikes and the reward presentation, we found that the most learning occurred when spiking activity had no overlap with the reward presentation; further, increasing the overlap actually decreased the learning efficacy. Thus, STDP alone cannot mediate the olfactory learning in Kenyon cells. Here, we discuss possible cellular mechanisms that could bridge the temporal gap between physiological and behavioral time scales.

Functional analysis of a higher olfactory center, the lateral horn

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

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

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

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

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

Excitatory local interneurons enhance tuning of sensory information

Neurons in the insect antennal lobe represent odors as spatiotemporal patterns of activity that unfold over multiple time scales. As these patterns unspool they decrease the overlap between odor representations and thereby increase the ability of the olfactory system to discriminate odors. Using a realistic model of the insect antennal lobe we examined two competing components of this process -lateral excitation from local excitatory interneurons, and slow inhibition from local inhibitory interneurons. We found that lateral excitation amplified differences between representations of similar odors by recruiting projection neurons that did not receive direct input from olfactory receptors. However, this increased sensitivity also amplified noisy variations in input and compromised the ability of the system to respond reliably to multiple presentations of the same odor. Slow inhibition curtailed the spread of projection neuron activity and increased response reliability. These competing influences must be finely balanced in order to decorrelate odor representations.

Spontaneous olfactory receptor neuron activity determines follower cell response properties

Noisy or spontaneous activity is common in neural systems and poses a challenge to detecting and discriminating signals. Here we use the locust to answer fundamental questions about noise in the olfactory system: Where does spontaneous activity originate? How is this activity propagated or reduced throughout multiple stages of neural processing? What mechanisms favor the detection of signals despite the presence of spontaneous activity? We found that spontaneous activity long observed in the secondary projection neurons (PNs) originates almost entirely from the primary olfactory receptor neurons (ORNs) rather than from spontaneous circuit interactions in the antennal lobe, and that spontaneous activity in ORNs tonically depolarizes the resting membrane potentials of their target PNs and local neurons (LNs) and indirectly tonically depolarizes tertiary Kenyon cells (KCs). However, because these neurons have different response thresholds, in the absence of odor stimulation, ORNs and PNs display a high spontaneous firing rate but KCs are nearly silent. Finally, we used a simulation of the olfactory network to show that discrimination of signal and noise in the KCs is best when threshold levels are set so that baseline activity in PNs persists. Our results show how the olfactory system benefits from making a signal detection decision after a point of maximal information convergence, e.g., after KCs pool inputs from many PNs.

Olfactory ecology and the processing of complex mixtures

Natural olfactory stimuli typically are mixtures of which the identities, concentrations, and ratios of chemical constituents are important for many odor-mediated behaviors. Despite abundant behavioral examples, links between odor-evoked behavior and the processing and discrimination of complex olfactory stimuli remains an area of active study. Coupling electrophysiological and behavioral experiments, recent studies in a variety of different insect models have provided new insights into the perceptual and neural mechanisms about how natural olfactory stimuli are processed, and how plasticity and internal state of the insect may influence the odor representation. These studies show that complex stimuli are represented in unique percepts that are different from their individual constituents, and that the representation may be modulated by experience and influenced by other sensory modalities.

Peripheral and central olfactory tuning in a moth

Animals can be innately attracted to certain odorants. Because these attractants are particularly salient, they might be expected to induce relatively strong responses throughout the olfactory pathway, helping animals detect the most relevant odors but limiting flexibility to respond to other odors. Alternatively, specific neural wiring might link innately preferred odors to appropriate behaviors without a need for intensity biases. How nonpheromonal attractants are processed by the general olfactory system remains largely unknown. In the moth Manduca sexta, we studied this with a set of innately preferred host plant odors and other, neutral odors. Electroantennogram recordings showed that, as a population, olfactory receptor neurons (ORNs) did not respond with greater intensity to host plant odors, and further local field potential recordings showed that no specific amplification of signals induced by host plant odors occurred between the first olfactory center and the second. Moreover, when odorants were mutually diluted to elicit equally intense output from the ORNs, moths were able to learn to associate all tested odorants equally well with food reward. Together, these results suggest that, although nonpheromonal host plant odors activate broadly distributed responses, they may be linked to attractive behaviors mainly through specific wiring in the brain.

Conditional modulation of spike-timing-dependent plasticity for olfactory learning

Mushroom bodies are a well-known site for associative learning in insects. Yet the precise mechanisms that underlie plasticity there and ensure their specificity remain elusive. In locusts, the synapses between the intrinsic mushroom body neurons and their postsynaptic targets obey a Hebbian spike-timing-dependent plasticity (STDP) rule. Although this property homeostatically regulates the timing of mushroom body output, its potential role in associative learning is unknown. Here we show in vivo that pre-post pairing causing STDP can, when followed by the local delivery of a reinforcement-mediating neuromodulator, specify the synapses that will undergo an associative change. At these synapses, and there only, the change is a transformation of the STDP rule itself. These results illustrate the multiple actions of STDP, including a role in associative learning, despite potential temporal dissociation between the pairings that specify synaptic modification and the delivery of reinforcement-mediating neuromodulator signals.

The vestibular system: multimodal integration and encoding of self-motion for motor control

Understanding how sensory pathways transmit information under natural conditions remains a major goal in neuroscience. The vestibular system plays a vital role in everyday life, contributing to a wide range of functions from reflexes to the highest levels of voluntary behavior. Recent experiments establishing that vestibular (self-motion) processing is inherently multimodal also provide insight into a set of interrelated questions. What neural code is used to represent sensory information in vestibular pathways? How do the interactions between the organism and the environment shape encoding? How is self-motion information processing adjusted to meet the needs of specific tasks? This review highlights progress that has recently been made towards understanding how the brain encodes and processes self-motion to ensure accurate motor control.

Associative memory: without a trace

Some transient sensory stimuli can cause prolonged activity in the brain. Trace conditioning experiments can reveal the time over which these lasting representations can be utilized and where they reside.

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.

The neurobiology of insect olfaction: sensory processing in a comparative context

The simplicity and accessibility of the olfactory systems of insects underlie a body of research essential to understanding not only olfactory function but also general principles of sensory processing. As insect olfactory neurobiology takes advantage of a variety of species separated by millions of years of evolution, the field naturally has yielded some conflicting results. Far from impeding progress, the varieties of insect olfactory systems reflect the various natural histories, adaptations to specific environments, and the roles olfaction plays in the life of the species studied. We review current findings in insect olfactory neurobiology, with special attention to differences among species. We begin by describing the olfactory environments and olfactory-based behaviors of insects, as these form the context in which neurobiological findings are interpreted. Next, we review recent work describing changes in olfactory systems as adaptations to new environments or behaviors promoting speciation. We proceed to discuss variations on the basic anatomy of the antennal (olfactory) lobe of the brain and higher-order olfactory centers. Finally, we describe features of olfactory information processing including gain control, transformation between input and output by operations such as broadening and sharpening of tuning curves, the role of spiking synchrony in the antennal lobe, and the encoding of temporal features of encounters with an odor plume. In each section, we draw connections between particular features of the olfactory neurobiology of a species and the animal's life history. We propose that this perspective is beneficial for insect olfactory neurobiology in particular and sensory neurobiology in general.

Olfactory trace conditioning in Drosophila

The neural representation of a sensory stimulus evolves with time, and animals keep that representation even after stimulus cessation (i.e., a stimulus "trace"). To contrast the memories of an odor and an odor trace, we here establish a rigorous trace conditioning paradigm in the fruit fly, Drosophila melanogaster. We modify the olfactory associative learning paradigm, in which the odor and electric shock are presented with a temporal overlap (delay conditioning). Given a few-second temporal gap between the presentations of the odor and the shock in trace conditioning, the odor trace must be kept until the arrival of electric shock to form associative memory. We found that memories after trace and delay conditioning have striking similarities: both reached the same asymptotic learning level, although at different rates, and both kinds of memory have similar decay kinetics and highly correlated generalization profiles across odors. In search of the physiological correlate of the odor trace, we used in vivo calcium imaging to characterize the odor-evoked activity of the olfactory receptor neurons in the antennal lobe. After the offset of odor presentation, the receptor neurons showed persistent, odor-specific response patterns that lasted for a few seconds and were fundamentally different from the response patterns during the stimulation. Weak correlation between the behavioral odor generalization profile in trace conditioning and the physiological odor similarity profiles in the antennal lobe suggest that the odor trace used for associative learning may be encoded downstream of the olfactory receptor neurons.

Are mushroom bodies cerebellum-like structures?

The mushroom bodies are distinctive neuropils in the protocerebral brain segments of many protostomes. A defining feature of mushroom bodies is their intrinsic neurons, masses of cytoplasm-poor globuli cells that form a system of lobes with their densely-packed, parallel-projecting axon-like processes. In insects, the role of the mushroom bodies in olfactory processing and associative learning and memory has been studied in depth, but several lines of evidence suggest that the function of these higher brain centers cannot be restricted to these roles. The present account considers whether insight into an underlying function of mushroom bodies may be provided by cerebellum-like structures in vertebrates, which are similarly defined by the presence of masses of tiny granule cells that emit thin parallel fibers forming a dense molecular layer. In vertebrates, the shared neuroarchitecture of cerebellum-like structures has been suggested to underlie a common functional role as adaptive filters for the removal of predictable sensory elements, such as those arising from reafference, from the total sensory input. Cerebellum-like structures include the vertebrate cerebellum, the electrosensory lateral line lobe, dorsal and medial octavolateral nuclei of fish, and the dorsal cochlear nucleus of mammals. The many architectural and physiological features that the insect mushroom bodies share with cerebellum-like structures suggest that it might be fruitful to consider mushroom body function in light of a possible role as adaptive sensory filters. The present account thus presents a detailed comparison of the insect mushroom bodies with vertebrate cerebellum-like structures.

Mushroom body output neurons encode odor-reward associations

Neural correlates of learning and memory formation have been reported at different stages of the olfactory pathway in both vertebrates and invertebrates. However, the contribution of different neurons to the formation of a memory trace is little understood. Mushroom bodies (MBs) in the insect brain are higher-order structures involved in integration of olfactory, visual, and mechanosensory information and in memory formation. Here we focus on the ensemble spiking activity of single MB output neurons (ENs) when honeybees learned to associate an odor with reward. A large group of ENs (∼50%) changed their odor response spectra by losing or gaining sensitivity for specific odors. This response switching was dominated by the rewarded stimulus (CS+), which evoked exclusively recruitment. The remaining ENs did not change their qualitative odor spectrum but modulated their tuning strength, again dominated by increased responses to the CS+. While the bees showed a conditioned response (proboscis extension) after a few acquisition trials, no short-term effects were observed in the neuronal activity. In both EN types, associative plastic changes occurred only during retention 3 h after conditioning. Thus, long-term but not short-term memory was reflected by increased EN activity to the CS+. During retention, the EN ensemble separated the CS+ most differently from the CS- and control odors ∼140 ms after stimulus onset. The learned behavioral response appeared ∼330 ms later. It is concluded that after memory consolidation, the ensemble activity of the MB output neurons predicts the meaning of the stimulus (reward) and may provide the prerequisite for the expression of the learned behavior.

Appetitive and aversive learning in Spodoptera littoralis larvae

Adult Lepidoptera are capable of associative learning. This helps them to forage flowers or to find suitable oviposition sites. Larval learning has never been seriously considered because they have limited foraging capabilities and usually depend on adults as concerns their food choices. We tested if Spodoptera littoralis larvae can learn to associate an odor with a tastant using a new classical conditioning paradigm. Groups of larvae were exposed to an unconditioned stimulus (US: fructose or quinine mixed with agar) paired with a conditioned stimulus (CS: hexanol, geraniol or pentyl acetate) in a petri dish. Their reaction to CS was subsequently tested in a petri dish at different time intervals after conditioning. Trained larvae showed a significant preference or avoidance to CS when paired with US depending on the reinforcer used. The training was more efficient when larvae were given a choice between an area where CS-US was paired and an area with no CS (or another odor). In these conditions, the memory formed could be recalled at least 24 h after pairing with an aversive stimulus and only 5 min after pairing with an appetitive stimulus. This learning was specific to CS because trained larvae were able to discriminate CS from another odor that was present during the training but unrewarded. These results suggest that Lepidoptera larvae exhibit more behavioral plasticity than previously appreciated.

Mind the gap: olfactory trace conditioning in honeybees

Trace conditioning is a form of classical conditioning, where a neutral stimulus (conditioned stimulus, CS) is associated with a following appetitive or aversive stimulus (unconditioned stimulus, US). Unlike classical delay conditioning, in trace conditioning there is a stimulus-free gap between CS and US, and thus a poststimulus neural representation (trace) of the CS is required to bridge the gap until its association with the US. The properties of such stimulus traces are not well understood, nor are their underlying physiological mechanisms. Using behavioral and physiological approaches, we studied appetitive olfactory trace conditioning in honeybees. We found that single-odor presentation created a trace containing information about odor identity. This trace conveyed odor information about the initial stimulus and was robust against interference by other odors. Memory acquisition decreased with increasing CS-US gap length. The maximum learnable CS-US gap length could be extended by previous trace-conditioning experience. Furthermore, acquisition improved when an additional odor was presented during the CS-US gap. Using calcium imaging, we tested whether projection neurons in the primary olfactory brain area, the antennal lobe, contain a CS trace. We found odor-specific persistent responses after stimulus offset. These post-odor responses, however, did not encode the CS trace, and perceived odor quality could be predicted by the initial but not by the post-odor response. Our data suggest that olfactory trace conditioning is a less reflexive form of learning than classical delay conditioning, indicating that odor traces might involve higher-level cognitive processes.

Brain organization and the roots of anticipation in Drosophila olfactory conditioning

Defining learning at the molecular and physiological level has been one of the greatest challenges in biology. Recent research suggests that by studying fruit fly (Drosophila melanogaster) brain organization we can now begin to unravel some of these mysteries. The fruit fly brain is organized into executive centers that regulate anatomically separate behavioral systems. The mushroom body is an example of an executive center which is modified by olfactory conditioning. During this simple form of learning, an odor is paired with either food or shock. Either experience alters distinguishable specific circuitry within the mushroom body. Results suggest that after conditioning an odor to food, the mushroom body will activate a feeding system via a subset of its circuitry. After conditioning an odor to shock, the mushroom body will instead activate an avoidance system with other subsets of mushroom body neurons. The results of these experiments demonstrate a mechanism for flies to display anticipation of their environment after olfactory conditioning has occurred. However, these results fail to provide evidence for reinforcement, a consequence of action, as part of this mechanism. Instead, specific subsets of dopaminergic and octopaminergic neurons provide a simple pairing signal, in contrast to a reinforcement signal, which allows for prediction of the environment after experience. This view has implications for models of conditioning.

Offset response of the olfactory projection neurons in the moth antennal lobe

We investigated a population activity of central olfactory neurons after the termination of odor input. Olfactory response of projection neurons in the moth primary olfactory center was characterized using in vivo intracellular recording and staining techniques. The population activity changed rapidly to the different states after the stimulus offset. The response after stimulus offset represents information regarding odor identity. We analyzed the spatial distribution of offset-activated glomeruli in a virtual neuronal population that was reconstructed using accumulated individual recordings obtained from different specimens. The offset-activated glomeruli tended to be widely distributed, whereas the onset-activated glomeruli were relatively clustered. These results suggest the importance of lateral interaction in shaping the offset olfactory response.

Dopamine reveals neural circuit mechanisms of fly memory

A goal of memory research is to understand how changing the weight of specific synapses in neural circuits in the brain leads to an appropriate learned behavioral response. Finding the relevant synapses should allow investigators to probe the underlying physiological and molecular operations that encode memories and permit their retrieval. In this review I discuss recent work in Drosophila that implicates specific subsets of dopaminergic (DA) neurons in aversive reinforcement and appetitive motivation. The zonal architecture of these DA neurons is likely to reveal the functional organization of aversive and appetitive memory in the mushroom bodies. Combinations of fly DA neurons might code negative and positive value, consistent with a motivational systems role as proposed in mammals.

Frequency transitions in odor-evoked neural oscillations

In many species, sensory stimuli elicit the oscillatory synchronization of groups of neurons. What determines the properties of these oscillations? In the olfactory system of the moth, we found that odors elicited oscillatory synchronization through a neural mechanism like that described in locust and Drosophila. During responses to long odor pulses, oscillations suddenly slowed as net olfactory receptor neuron (ORN) output decreased; thus, stimulus intensity appeared to determine oscillation frequency. However, changing the concentration of the odor had little effect upon oscillatory frequency. Our recordings in vivo and computational models based on these results suggested that the main effect of increasing odor concentration was to recruit additional, less well-tuned ORNs whose firing rates were tightly constrained by adaptation and saturation. Thus, in the periphery, concentration is encoded mainly by the size of the responsive ORN population, and oscillation frequency is set by the adaptation and saturation of this response.

Intrinsic Membrane Properties and Inhibitory Synaptic Input of Kenyon Cells as Mechanisms for Sparse Coding?

The insect mushroom bodies (MBs) are multimodal signal processing centers and are essential for olfactory learning. Electrophysiological recordings from the MBs' principal component neurons, the Kenyon cells (KCs), showed a sparse representation of olfactory signals. It has been proposed that the intrinsic and synaptic properties of the KC circuitry combine to reduce the firing of action potentials and to generate relatively brief windows for synaptic integration in the KCs, thus causing them to operate as coincidence detectors. To better understand the ionic mechanisms that mediate the KC intrinsic firing properties, we used whole cell patch-clamp recordings from KCs in the adult, intact brain of Periplaneta americana to analyze voltage- and/or Ca2+-dependent inward ( ICa, INa) and outward currents [ IA, IK(V), IK,ST, IO(Ca)]. In general the currents had properties similar to those of currents in other insect neurons. Certain functional parameters of ICaand IO(Ca), however, had unusually high values, allowing them to assist sparse coding. ICahad a low-activation threshold and a very high current density compared with those of ICain other insect neurons. Together these parameters make ICasuitable for boosting and sharpening the excitatory postsynaptic potentials as reported in previous studies. IO(Ca)also had a large current density and a very depolarized activation threshold. In combination, the large ICaand IO(Ca)are likely to mediate the strong spike frequency adaptation. These intrinsic properties of the KCs are likely to be supported by their tonic, inhibitory synaptic input, which was revealed by specific GABA antagonists and which contributes significantly to the hyperpolarized membrane potential at rest.

How the olfactory bulb got its glomeruli: a just so story?

The nearly 2,000 glomeruli that cover the surface of the olfactory bulb are so distinctive that they were noted specifically in the earliest of Cajal's catalogues. They have variously been considered a functional unit, an organizational unit and a crucial component of the olfactory coding circuit. Despite their central position in olfactory processing, the development of the glomeruli has only recently begun to be investigated with new and powerful genetic tools. Some unexpected findings have been made that may lead to a new understanding of the processes involved in wiring sensory regions of the brain. It may no longer be sufficient to simply invoke genes, spikes and their interplay in the construction of brain circuits. The story of 'how the olfactory bulb got its glomeruli' may be more complex, and more revealing, than has been supposed.