Neuronal computations in the olfactory system of zebrafish

Mixing things up! - how odor blends are processed in Drosophila

Insects have to navigate a complex and rich olfactory environment consisting of mixtures of odors at varying ratios. However, we understand little of how the olfactory system represents these complex blends. This review aims to highlight some of the recent results of studying this mixture code, in the Drosophila melanogaster olfactory system, as well as gives a short background to one of the most challenging questions in olfaction - how are mixtures encoded in the brain?

Normative and mechanistic model of an adaptive circuit for efficient encoding and feature extraction

One major question in neuroscience is how to relate connectomes to neural activity, circuit function, and learning. We offer an answer in the peripheral olfactory circuit of the Drosophila larva, composed of olfactory receptor neurons (ORNs) connected through feedback loops with interconnected inhibitory local neurons (LNs). We combine structural and activity data and, using a holistic normative framework based on similarity-matching, we formulate biologically plausible mechanistic models of the circuit. In particular, we consider a linear circuit model, for which we derive an exact theoretical solution, and a nonnegative circuit model, which we examine through simulations. The latter largely predicts the ORN [Formula: see text] LN synaptic weights found in the connectome and demonstrates that they reflect correlations in ORN activity patterns. Furthermore, this model accounts for the relationship between ORN [Formula: see text] LN and LN-LN synaptic counts and the emergence of different LN types. Functionally, we propose that LNs encode soft cluster memberships of ORN activity, and partially whiten and normalize the stimulus representations in ORNs through inhibitory feedback. Such a synaptic organization could, in principle, autonomously arise through Hebbian plasticity and would allow the circuit to adapt to different environments in an unsupervised manner. We thus uncover a general and potent circuit motif that can learn and extract significant input features and render stimulus representations more efficient. Finally, our study provides a unified framework for relating structure, activity, function, and learning in neural circuits and supports the conjecture that similarity-matching shapes the transformation of neural representations.

Escape steering by cholecystokinin peptidergic signaling

Escape is an evolutionarily conserved and essential avoidance response. Considered to be innate, most studies on escape responses focused on hard-wired circuits. We report here that a neuropeptide NLP-18 and its cholecystokinin receptor CKR-1 enable the escape circuit to execute a full omega (Ω) turn. We demonstrate in vivo NLP-18 is mainly secreted by the gustatory sensory neuron (ASI) to activate CKR-1 in the head motor neuron (SMD) and the turn-initiating interneuron (AIB). Removal of NLP-18 or CKR-1 or specific knockdown of CKR-1 in SMD or AIB neurons leads to shallower turns, hence less robust escape steering. Consistently, elevation of head motor neuron (SMD)'s Ca²⁺ transients during escape steering is attenuated upon the removal of NLP-18 or CKR-1. In vitro, synthetic NLP-18 directly evokes CKR-1-dependent currents in oocytes and CKR-1-dependent Ca²⁺ transients in SMD. Thus, cholecystokinin peptidergic signaling modulates an escape circuit to generate robust escape steering.

Finding the Brain in the Nose

Olfaction is fundamentally distinct from other sensory modalities. Natural odor stimuli are complex mixtures of volatile chemicals that interact in the nose with a receptor array that, in rodents, is built from more than 1,000 unique receptors. These interactions dictate a peripheral olfactory code, which in the brain is transformed and reformatted as it is broadcast across a set of highly interconnected olfactory regions. Here we discuss the problems of characterizing peripheral population codes for olfactory stimuli, of inferring the specific functions of different higher olfactory areas given their extensive recurrence, and of ultimately understanding how odor representations are linked to perception and action. We argue that, despite the differences between olfaction and other sensory modalities, addressing these specific questions will reveal general principles underlying brain function.

The glomerular network of the zebrafish olfactory bulb

Each zebrafish olfactory bulb contains ~ 140 glomeruli that are distinguishable based on size, location, neurochemistry and function. Here we examine the mitral cell innervation of differently sized glomeruli in adult zebrafish. Type 1 glomeruli had diameters of 80.9 ± 8.1 μm and were innervated by 5.9 ± 0.9 mitral cells. The Type 1 mediodorsal glomeruli (mdG) were innervated by both uniglomerular (innervating only single glomeruli) and multiglomerular mitral cells (innervating two or more glomeruli). In contrast, the Type 1 ventroposterior (vpG) and lateral glomeruli (lG) were only innervated by uniglomerular mitral cells. Type 2 ventral glomeruli were 46 ± 5.1 μm in diameter and were innervated by 3.3 ± 0.2 mitral cells. Type 2 ventromedial glomeruli (vmG) were innervated exclusively by uniglomerular mitral cells. Type 3 glomeruli had diameters of 17 ± 2.5 μm and were innervated by 1.1 ± 0.6 multiglomerular mitral cells each. Finally, Type 4 glomeruli were small, with average diameters of 4.8 ± 3.9 μm and were restricted to the lateral plexus. These glomeruli were innervated mainly by multiglomerular mitral cells with extensively branching dendrites. This study provides the first specific associations between uni- and multiglomerular mitral cells with known zebrafish glomeruli. Our results suggest that glomeruli are distinguishable based on their postsynaptic compartment and that distinct input-output computations occur in different types of zebrafish glomeruli.

PiVR: An affordable and versatile closed-loop platform to study unrestrained sensorimotor behavior

Tools enabling closed-loop experiments are crucial to delineate causal relationships between the activity of genetically labeled neurons and specific behaviors. We developed the Raspberry Pi Virtual Reality (PiVR) system to conduct closed-loop optogenetic stimulation of neural functions in unrestrained animals. PiVR is an experimental platform that operates at high temporal resolution (70 Hz) with low latencies (<30 milliseconds), while being affordable ( Collapse

Key Words Collapse

MESH Headings

• Animals
• Behavior, Animal/physiology
• Chemotaxis
• Drosophila melanogaster/physiology
• Larva/physiology
• Light
• Locomotion
• Male
• Neurons/physiology
• Odorants
• Optogenetics
• Sensation/physiology
• Sensorimotor Cortex/physiology
• Software
• Taste/physiology
• Virtual Reality
• Zebrafish

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Grants

• R01 NS113048 NINDS NIH HHS
• R25 GM067110 NIGMS NIH HHS
• National Science Foundation
• National Institute of Health
• Gordon and Betty Moore Foundation

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Affiliation(s)

David Tadres Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, California, United States of America Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, California, United States of America Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland

Matthieu Louis Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, California, United States of America Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, California, United States of America Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America

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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.

Behavioural and neuronal basis of olfactory imprinting and kin recognition in larval fish

Imprinting is a specific form of long-term memory of a cue acquired during a sensitive phase of development. To ensure that organisms memorize the right cue, the learning process must happen during a specific short time period, mostly soon after hatching, which should end before irrelevant or misleading signals are encountered. A well-known case of olfactory imprinting in the aquatic environment is that of the anadromous Atlantic and Pacific salmon, which prefer the olfactory cues of natal rivers to which they return after migrating several years in the open ocean. Recent research has shown that olfactory imprinting and olfactory guided navigation in the marine realm are far more common than previously assumed. Here, we present evidence for the involvement of olfactory imprinting in the navigation behaviour of coral reef fish, which prefer their home reef odour over that of other reefs. Two main olfactory imprinting processes can be differentiated: (1) imprinting on environmental cues and (2) imprinting on chemical compounds released by kin, which is based on genetic relatedness among conspecifics. While the first process allows for plasticity, so that organisms can imprint on a variety of chemical signals, the latter seems to be restricted to specific genetically determined kin signals. We focus on the second, elucidating the behavioural and neuronal basis of the imprinting process on kin cues using larval zebrafish (Danio rerio) as a model. Our data suggest that the process of imprinting is not confined to the central nervous system but also triggers some changes in the olfactory epithelium.

Neurotoxicological effects induced by up-regulation of miR-137 following triclosan exposure to zebrafish (Danio rerio)

Triclosan (TCS) is a prevalent anthropogenic contaminant in aquatic environments and its chronic exposure can lead to a series of neurotoxic effects in zebrafish. Both qRT-PCR and W-ISH identified that TCS exposure resulted in significant up-regulation of miR-137, but downregulation of its regulatory genes (bcl11aa, MAPK6 and Runx1). These target genes are mainly associated with neurodevelopment and the MAPK signaling pathway, and showed especially high expression in the brain. After overexpression or knockdown treatments by manual intervention of miR-137, a series of abnormalities were induced, such as ventricular abnormality, bent spine, yolk cyst, closure of swim sac and venous sinus hemorrhage. The most sensitive larval toxicological endpoint from intervened miR-137 expression was impairment of the central nervous system (CNS), ventricular abnormalities and notochord curvature. Microinjection of microRNA mimics or inhibitors of miR-137 both caused zebrafish malformations. The posterior lateral line neuromasts became obscured and decreased in number in intervened miR-137 groups and TCS-exposure groups. Up-regulation of miR-137 led to more severe neurotoxic effects than its down-regulation. Behavioral observations demonstrated that both TCS exposure and miR-137 over-expression led to inhibited hearing or vision sensitivity. HE staining indicated that hearing and vision abnormalities induced by long-term TCS exposure originated from CNS injury, such as reduced glial cells and loose and hollow fiber structures. The findings of this study enhance our mechanistic understanding of neurotoxicity in aquatic animals in response to TCS exposure. These observations provide theoretical guidance for development of early intervention treatments for nervous system diseases.

Rapid olfactory discrimination learning in adult zebrafish

The zebrafish is a model organism to study olfactory information processing, but efficient behavioral procedures to analyze olfactory discrimination and memory are lacking. We devised an automated odor discrimination task for adult zebrafish based on olfactory conditioning of feeding behavior. Presentation of a conditioned odor (CS+), but not a neutral odor (CS−) was followed by food delivery at a specific location. Fish developed differential behavioral responses to CS+ and CS− within a few trials. The behavioral response to the CS+ was complex and included components reminiscent of food search such as increased swimming speed and water surface sampling. Appetitive behavior was therefore quantified by a composite score that combined measurements of multiple behavioral parameters. Robust discrimination behavior was observed in different strains, even when odors were chemically similar, and learned preferences could overcome innate odor preferences. These results confirm that zebrafish can rapidly learn to make fine odor discriminations. The procedure is efficient and provides novel opportunities to dissect the neural mechanisms underlying olfactory discrimination and memory.

Circuit variability interacts with excitatory-inhibitory diversity of interneurons to regulate network encoding capacity

Local interneurons (LNs) in the Drosophila olfactory system exhibit neuronal diversity and variability, yet it is still unknown how these features impact information encoding capacity and reliability in a complex LN network. We employed two strategies to construct a diverse excitatory-inhibitory neural network beginning with a ring network structure and then introduced distinct types of inhibitory interneurons and circuit variability to the simulated network. The continuity of activity within the node ensemble (oscillation pattern) was used as a readout to describe the temporal dynamics of network activity. We found that inhibitory interneurons enhance the encoding capacity by protecting the network from extremely short activation periods when the network wiring complexity is very high. In addition, distinct types of interneurons have differential effects on encoding capacity and reliability. Circuit variability may enhance the encoding reliability, with or without compromising encoding capacity. Therefore, we have described how circuit variability of interneurons may interact with excitatory-inhibitory diversity to enhance the encoding capacity and distinguishability of neural networks. In this work, we evaluate the effects of different types and degrees of connection diversity on a ring model, which may simulate interneuron networks in the Drosophila olfactory system or other biological systems.

Temporal Response Properties of Accessory Olfactory Bulb Neurons: Limitations and Opportunities for Decoding

The vomeronasal system (VNS) is a major vertebrate chemosensory system that functions in parallel to the main olfactory system (MOS). Despite many similarities, the two systems dramatically differ in the temporal domain. While MOS responses are governed by breathing and follow a subsecond temporal scale, VNS responses are uncoupled from breathing and evolve over seconds. This suggests that the contribution of response dynamics to stimulus information will differ between these systems. While temporal dynamics in the MOS are widely investigated, similar analyses in the accessory olfactory bulb (AOB) are lacking. Here, we have addressed this issue using controlled stimulus delivery to the vomeronasal organ of male and female mice. We first analyzed the temporal properties of AOB projection neurons and demonstrated that neurons display prolonged, variable, and neuron-specific characteristics. We then analyzed various decoding schemes using AOB population responses. We showed that compared with the simplest scheme (i.e., integration of spike counts over the entire response period), the division of this period into smaller temporal bins actually yields poorer decoding accuracy. However, optimal classification accuracy can be achieved well before the end of the response period by integrating spike counts within temporally defined windows. Since VNS stimulus uptake is variable, we analyzed decoding using limited information about stimulus uptake time, and showed that with enough neurons, such time-invariant decoding is feasible. Finally, we conducted simulations that demonstrated that, unlike the main olfactory bulb, the temporal features of AOB neurons disfavor decoding with high temporal accuracy, and, rather, support decoding without precise knowledge of stimulus uptake time.SIGNIFICANCE STATEMENT A key goal in sensory system research is to identify which metrics of neuronal activity are relevant for decoding stimulus features. Here, we describe the first systematic analysis of temporal coding in the vomeronasal system (VNS), a chemosensory system devoted to socially relevant cues. Compared with the main olfactory system, timescales of VNS function are inherently slower and variable. Using various analyses of real and simulated data, we show that the consideration of response times relative to stimulus uptake can aid the decoding of stimulus information from neuronal activity. However, response properties of accessory olfactory bulb neurons favor decoding schemes that do not rely on the precise timing of stimulus uptake. Such schemes are consistent with the variable nature of VNS stimulus uptake.

Mechanosensory-Based Phase Coding of Odor Identity in the Olfactory Bulb

Mitral and tufted (M/T) cells in the olfactory bulb produce rich temporal patterns of activity in response to different odors. However, it remains unknown how these temporal patterns are generated and how they are utilized in olfaction. Here we show that temporal patterning effectively discriminates between the two sensory modalities detected by olfactory sensory neurons (OSNs): odor and airflow-driven mechanical signals. Sniff-induced mechanosensation generates glomerulus-specific oscillatory activity in M/T cells, whose phase was invariant across airflow speed. In contrast, odor stimulation caused phase shifts (phase coding). We also found that odor-evoked phase shifts are concentration invariant and stable across multiple sniff cycles, contrary to the labile nature of rate coding. The loss of oscillatory mechanosensation impaired the precision and stability of phase coding, demonstrating its role in olfaction. We propose that phase, not rate, coding is a robust encoding strategy of odor identity and is ensured by airflow-induced mechanosensation in OSNs.

Sparse synaptic connectivity is required for decorrelation and pattern separation in feedforward networks

Pattern separation is a fundamental function of the brain. The divergent feedforward networks thought to underlie this computation are widespread, yet exhibit remarkably similar sparse synaptic connectivity. Marr-Albus theory postulates that such networks separate overlapping activity patterns by mapping them onto larger numbers of sparsely active neurons. But spatial correlations in synaptic input and those introduced by network connectivity are likely to compromise performance. To investigate the structural and functional determinants of pattern separation we built models of the cerebellar input layer with spatially correlated input patterns, and systematically varied their synaptic connectivity. Performance was quantified by the learning speed of a classifier trained on either the input or output patterns. Our results show that sparse synaptic connectivity is essential for separating spatially correlated input patterns over a wide range of network activity, and that expansion and correlations, rather than sparse activity, are the major determinants of pattern separation.

Input decorrelation, expansion recoding and sparse activity have been proposed to separate overlapping activity patterns in feedforward networks. Here the authors use reduced and detailed spiking models to elucidate how synaptic connectivity affects the contribution of these mechanisms to pattern separation in cerebellar cortex.

3-dimensional electron microscopic imaging of the zebrafish olfactory bulb and dense reconstruction of neurons

Large-scale reconstructions of neuronal populations are critical for structural analyses of neuronal cell types and circuits. Dense reconstructions of neurons from image data require ultrastructural resolution throughout large volumes, which can be achieved by automated volumetric electron microscopy (EM) techniques. We used serial block face scanning EM (SBEM) and conductive sample embedding to acquire an image stack from an olfactory bulb (OB) of a zebrafish larva at a voxel resolution of 9.25×9.25×25 nm3. Skeletons of 1,022 neurons, 98% of all neurons in the OB, were reconstructed by manual tracing and efficient error correction procedures. An ergonomic software package, PyKNOSSOS, was created in Python for data browsing, neuron tracing, synapse annotation, and visualization. The reconstructions allow for detailed analyses of morphology, projections and subcellular features of different neuron types. The high density of reconstructions enables geometrical and topological analyses of the OB circuitry. Image data can be accessed and viewed through the neurodata web services (http://www.neurodata.io). Raw data and reconstructions can be visualized in PyKNOSSOS.

Building the Ferretome

Databases of structural connections of the mammalian brain, such as CoCoMac (cocomac.g-node.org) or BAMS (https://bams1.org), are valuable resources for the analysis of brain connectivity and the modeling of brain dynamics in species such as the non-human primate or the rodent, and have also contributed to the computational modeling of the human brain. Another animal model that is widely used in electrophysiological or developmental studies is the ferret; however, no systematic compilation of brain connectivity is currently available for this species. Thus, we have started developing a database of anatomical connections and architectonic features of the ferret brain, the Ferret(connect)ome, www.Ferretome.org. The Ferretome database has adapted essential features of the CoCoMac methodology and legacy, such as the CoCoMac data model. This data model was simplified and extended in order to accommodate new data modalities that were not represented previously, such as the cytoarchitecture of brain areas. The Ferretome uses a semantic parcellation of brain regions as well as a logical brain map transformation algorithm (objective relational transformation, ORT). The ORT algorithm was also adopted for the transformation of architecture data. The database is being developed in MySQL and has been populated with literature reports on tract-tracing observations in the ferret brain using a custom-designed web interface that allows efficient and validated simultaneous input and proofreading by multiple curators. The database is equipped with a non-specialist web interface. This interface can be extended to produce connectivity matrices in several formats, including a graphical representation superimposed on established ferret brain maps. An important feature of the Ferretome database is the possibility to trace back entries in connectivity matrices to the original studies archived in the system. Currently, the Ferretome contains 50 reports on connections comprising 20 injection reports with more than 150 labeled source and target areas, the majority reflecting connectivity of subcortical nuclei and 15 descriptions of regional brain architecture. We hope that the Ferretome database will become a useful resource for neuroinformatics and neural modeling, and will support studies of the ferret brain as well as facilitate advances in comparative studies of mesoscopic brain connectivity.

Remote z-scanning with a macroscopic voice coil motor for fast 3D multiphoton laser scanning microscopy

There is a high demand for 3D multiphoton imaging in neuroscience and other fields but scanning in axial direction presents technical challenges. We developed a focusing technique based on a remote movable mirror that is conjugate to the specimen plane and translated by a voice coil motor. We constructed cost-effective z-scanning modules from off-the-shelf components that can be mounted onto standard multiphoton laser scanning microscopes to extend scan patterns from 2D to 3D. Systems were designed for large objectives and provide high resolution, high speed and a large z-scan range (>300 μm). We used these systems for 3D multiphoton calcium imaging in the adult zebrafish brain and measured odor-evoked activity patterns across >1500 neurons with single-neuron resolution and high signal-to-noise ratio.

Correlations and Neuronal Population Information

Brain function involves the activity of neuronal populations. Much recent effort has been devoted to measuring the activity of neuronal populations in different parts of the brain under various experimental conditions. Population activity patterns contain rich structure, yet many studies have focused on measuring pairwise relationships between members of a larger population-termed noise correlations. Here we review recent progress in understanding how these correlations affect population information, how information should be quantified, and what mechanisms may give rise to correlations. As population coding theory has improved, it has made clear that some forms of correlation are more important for information than others. We argue that this is a critical lesson for those interested in neuronal population responses more generally: Descriptions of population responses should be motivated by and linked to well-specified function. Within this context, we offer suggestions of where current theoretical frameworks fall short.

Dense EM-based reconstruction of the interglomerular projectome in the zebrafish olfactory bulb

The dense reconstruction of neuronal circuits from volumetric electron microscopy (EM) data has the potential to uncover fundamental structure-function relationships in the brain. To address bottlenecks in the workflow of this emerging methodology, we developed a procedure for conductive sample embedding and a pipeline for neuron reconstruction. We reconstructed ∼98% of all neurons (>1,000) in the olfactory bulb of a zebrafish larva with high accuracy and annotated all synapses on subsets of neurons representing different types. The organization of the larval olfactory bulb showed marked differences from that of the adult but similarities to that of the insect antennal lobe. Interneurons comprised multiple types but granule cells were rare. Interglomerular projections of interneurons were complex and bidirectional. Projections were not random but biased toward glomerular groups receiving input from common types of sensory neurons. Hence, the interneuron network in the olfactory bulb exhibits a specific topological organization that is governed by glomerular identity.

Functional organization of the mammalian auditory midbrain

The inferior colliculus (IC) is a critical nexus between the auditory brainstem and the forebrain. Parallel auditory pathways that emerge from the brainstem are integrated in the IC. In this integration, de-novo auditory information processed as local and ascending inputs converge via the complex neural circuit of the IC. However, it is still unclear how information is processed within the neural circuit. The purpose of this review is to give an anatomical and physiological overview of the IC neural circuit. We address the functional organization of the IC where the excitatory and inhibitory synaptic inputs interact to shape the responses of IC neurons to sound.

Neuronal pattern separation in the olfactory bulb improves odor discrimination learning

Neuronal pattern separation is thought to enable the brain to disambiguate sensory stimuli with overlapping features, thereby extracting valuable information. In the olfactory system, it remains unknown whether pattern separation acts as a driving force for sensory discrimination and the learning thereof. We found that overlapping odor-evoked input patterns to the mouse olfactory bulb (OB) were dynamically reformatted in the network on the timescale of a single breath, giving rise to separated patterns of activity in an ensemble of output neurons, mitral/tufted (M/T) cells. Notably, the extent of pattern separation in M/T assemblies predicted behavioral discrimination performance during the learning phase. Furthermore, exciting or inhibiting GABAergic OB interneurons, using optogenetics or pharmacogenetics, altered pattern separation and thereby odor discrimination learning in a bidirectional way. In conclusion, we propose that the OB network can act as a pattern separator facilitating olfactory stimulus distinction, a process that is sculpted by synaptic inhibition.

It takes two-coincidence coding within the dual olfactory pathway of the honeybee

To rapidly process biologically relevant stimuli, sensory systems have developed a broad variety of coding mechanisms like parallel processing and coincidence detection. Parallel processing (e.g., in the visual system), increases both computational capacity and processing speed by simultaneously coding different aspects of the same stimulus. Coincidence detection is an efficient way to integrate information from different sources. Coincidence has been shown to promote associative learning and memory or stimulus feature detection (e.g., in auditory delay lines). Within the dual olfactory pathway of the honeybee both of these mechanisms might be implemented by uniglomerular projection neurons (PNs) that transfer information from the primary olfactory centers, the antennal lobe (AL), to a multimodal integration center, the mushroom body (MB). PNs from anatomically distinct tracts respond to the same stimulus space, but have different physiological properties, characteristics that are prerequisites for parallel processing of different stimulus aspects. However, the PN pathways also display mirror-imaged like anatomical trajectories that resemble neuronal coincidence detectors as known from auditory delay lines. To investigate temporal processing of olfactory information, we recorded PN odor responses simultaneously from both tracts and measured coincident activity of PNs within and between tracts. Our results show that coincidence levels are different within each of the two tracts. Coincidence also occurs between tracts, but to a minor extent compared to coincidence within tracts. Taken together our findings support the relevance of spike timing in coding of olfactory information (temporal code).

Simultaneous encoding of odors by channels with diverse sensitivity to inhibition

Odorant receptors in the periphery map precisely onto olfactory glomeruli ("coding channels") in the brain. However, the odor tuning of a glomerulus is not strongly correlated with its spatial position. This raises the question of whether lateral inhibition between glomeruli is specific or nonspecific. Here we show that, in the Drosophila brain, focal activation of even a single glomerulus recruits GABAergic interneurons in all glomeruli. Moreover, the relative level of interneuron activity in different glomeruli is largely odor invariant. Although interneurons are recruited nonspecifically, glomeruli differ dramatically in their sensitivity to interneuron activity, and this is explained by their varying sensitivity to GABA. Interestingly, a stimulus is typically encoded in parallel by channels having high and low sensitivity to inhibition. Because lateral inhibition confers both costs and benefits, the brain might rely preferentially on "high" and "low" channels in different behavioral contexts.

Functional transformations of odor inputs in the mouse olfactory bulb

Sensory inputs from the nasal epithelium to the olfactory bulb (OB) are organized as a discrete map in the glomerular layer (GL). This map is then modulated by distinct types of local neurons and transmitted to higher brain areas via mitral and tufted cells. Little is known about the functional organization of the circuits downstream of glomeruli. We used in vivo two-photon calcium imaging for large scale functional mapping of distinct neuronal populations in the mouse OB, at single cell resolution. Specifically, we imaged odor responses of mitral cells (MCs), tufted cells (TCs) and glomerular interneurons (GL-INs). Mitral cells population activity was heterogeneous and only mildly correlated with the olfactory receptor neuron (ORN) inputs, supporting the view that discrete input maps undergo significant transformations at the output level of the OB. In contrast, population activity profiles of TCs were dense, and highly correlated with the odor inputs in both space and time. Glomerular interneurons were also highly correlated with the ORN inputs, but showed higher activation thresholds suggesting that these neurons are driven by strongly activated glomeruli. Temporally, upon persistent odor exposure, TCs quickly adapted. In contrast, both MCs and GL-INs showed diverse temporal response patterns, suggesting that GL-INs could contribute to the transformations MCs undergo at slow time scales. Our data suggest that sensory odor maps are transformed by TCs and MCs in different ways forming two distinct and parallel information streams.

Construction of functional neuronal circuitry in the olfactory bulb

Recent studies using molecular genetics, electrophysiology, in vivo imaging, and behavioral analyses have elucidated detailed connectivity and function of the mammalian olfactory circuits. The olfactory bulb is the first relay station of olfactory perception in the brain, but it is more than a simple relay: olfactory information is dynamically tuned by local olfactory bulb circuits and converted to spatiotemporal neural code for higher-order information processing. Because the olfactory bulb processes ∼1000 discrete input channels from different odorant receptors, it serves as a good model to study neuronal wiring specificity, from both functional and developmental aspects. This review summarizes our current understanding of the olfactory bulb circuitry from functional standpoint and discusses important future studies with particular focus on its development and plasticity.

Neuronal circuits and computations: pattern decorrelation in the olfactory bulb

Neuronal circuits in the olfactory bulb transform odor-evoked activity patterns across the input channels, the olfactory glomeruli, into distributed activity patterns across the output neurons, the mitral cells. One computation associated with this transformation is a decorrelation of activity patterns representing similar odors. Such a decorrelation has various benefits for the classification and storage of information by associative networks in higher brain areas. Experimental results from adult zebrafish show that pattern decorrelation involves a redistribution of activity across the population of mitral cells. These observations imply that pattern decorrelation cannot be explained by a global scaling mechanism but that it depends on interactions between distinct subsets of neurons in the network. This article reviews insights into the network mechanism underlying pattern decorrelation and discusses recent results that link pattern decorrelation in the olfactory bulb to odor discrimination behavior.

Coding and transformations in the olfactory system

How is sensory information represented in the brain? A long-standing debate in neural coding is whether and how timing of spikes conveys information to downstream neurons. Although we know that neurons in the olfactory bulb (OB) exhibit rich temporal dynamics, the functional relevance of temporal coding remains hotly debated. Recent recording experiments in awake behaving animals have elucidated highly organized temporal structures of activity in the OB. In addition, the analysis of neural circuits in the piriform cortex (PC) demonstrated the importance of not only OB afferent inputs but also intrinsic PC neural circuits in shaping odor responses. Furthermore, new experiments involving stimulation of the OB with specific temporal patterns allowed for testing the relevance of temporal codes. Together, these studies suggest that the relative timing of neuronal activity in the OB conveys odor information and that neural circuits in the PC possess various mechanisms to decode temporal patterns of OB input.

ORA1, a zebrafish olfactory receptor ancestral to all mammalian V1R genes, recognizes 4-hydroxyphenylacetic acid, a putative reproductive pheromone

The teleost v1r-related ora genes are a small, highly conserved olfactory receptor gene family of only six genes, whose direct orthologues can be identified in lineages as far as that of cartilaginous fish. However, no ligands for fish olfactory receptor class A related genes (ORA) had been uncovered so far. Here we have deorphanized the ORA1 receptor using heterologous expression and calcium imaging. We report that zebrafish ORA1 recognizes with high specificity and sensitivity 4-hydroxyphenylacetic acid. The carboxyl group of this compound is required in a particular distance from the aromatic ring, whereas the hydroxyl group in the para-position is not essential, but strongly enhances the binding efficacy. Low concentrations of 4-hydroxyphenylacetic acid elicit increases in oviposition frequency in zebrafish mating pairs. This effect is abolished by naris closure. We hypothesize that 4-hydroxyphenylacetic acid might function as a pheromone for reproductive behavior in zebrafish. ORA1 is ancestral to mammalian V1Rs, and its putative function as pheromone receptor is reminiscent of the role of several mammalian V1Rs as pheromone receptors.

Changes in the social environment induce neurogenic plasticity predominantly in niches residing in sensory structures of the zebrafish brain independently of cortisol levels

The social environment is known to modulate adult neurogenesis. Studies in mammals and birds have shown a strong correlation between social isolation and decreases in neurogenesis, whereas time spent in an enriched environment has been shown to restore these deficits and enhance neurogenesis. These data suggest that there exists a common adaptive response among neurogenic niches to each extreme of the social environment. We sought to further test this hypothesis in zebrafish, a social species with distinct neurogenic niches within primary sensory structures and telencephalic nuclei of the brain. By examining stages of adult neurogenesis, including the proliferating stem/progenitor population, their surviving cohort, and the resulting newly differentiated neuronal population, we show that niches residing in sensory structures are most sensitive to changes in the social context, and that social isolation or novelty are both capable of decreasing the number of proliferating cells while increasing the number of newborn neurons within a single niche. Contrary to observations in rodents, we demonstrate that social novelty, a form of enrichment, does not consistently rescue deficits in cell proliferation following social isolation, and that cortisol levels do not negatively regulate changes in adult neurogenesis, but are correlated with the social context. We propose that enhancement or suppression of adult neurogenesis in the zebrafish brain under different social contexts depends largely on the type of niche (sensory or telencephalic), experience from the preceding social environment, and occurs independently of changes in cortisol levels.

Equalization of odor representations by a network of electrically coupled inhibitory interneurons

Robustness of neuronal activity patterns against variations in input intensity is critical for neuronal computations. We found that odor representations in the olfactory bulb were stabilized by interneurons that were densely coupled to the output neurons by electrical and GABAergic synapses. This interneuron network modulated responses of output neurons as a function of stimulus intensity in two ways: it globally boosted responses to weak odors, but attenuated responses to strong odors, and it increased the sensitivity of some output neurons, but decreased the sensitivity of others. These effects are closely related to strategies used in engineering to increase dynamic range. Together, they maintained not only the mean, but also the distribution, of activity across the population of output neurons within narrow limits, which is important for pattern classification. Neuronal circuits in the olfactory bulb therefore stabilize combinatorial sensory representations against variations in stimulus intensity by generic mechanisms.