Early transformations in odor representation

Serotonergic input from the dorsal raphe nucleus shapes learning-associated odor responses in the olfactory bulb

AIM

Neural activity in the olfactory bulb (OB) can represent odor information during different brain and behavioral states. For example, the odor responses of mitral/tufted (M/T) cells in the OB change during learning of odor-discrimination tasks and, at the network level, beta power increases and the high gamma (HG) power decreases during odor presentation in such tasks. However, the neural mechanisms underlying these observations remain poorly understood. Here, we investigate whether serotonergic modulation from the dorsal raphe nucleus (DRN) to the OB is involved in shaping activity during the learning process in a go/no-go task in mice.

METHODS

Fiber photometry was used to record the population activity of DRN serotonergic neurons during a go/no-go task. In vivo electrophysiology was used to record neural activity (single units and local field potentials) in the OB during the go/no-go task. Real-time place preference (RTPP) and intracranial light administration in a specific subarea (iClass) tests were used to assess the ability of mice to encoding reward information.

RESULTS

Odor-evoked population activity in serotonergic neurons in the DRN was shaped during the learning process in a go/no-go task. In the OB, neural activity from oscillations to single cells showed complex, learning-associated changes and ability to encode information during an odor discrimination task. However, these properties were not observed after ablation of DRN serotonergic neurons.

CONCLUSION

The activity of neural networks and single cells in the OB, and their ability to encode information about odor value, are shaped by serotonergic projections from the DRN.

Imaging different cell populations in the mouse olfactory bulb using the genetically encoded voltage indicator ArcLight

Genetically encoded voltage indicators (GEVIs) are protein-based optical sensors that allow for measurements from genetically defined populations of neurons. Although in vivo imaging in the mammalian brain with early generation GEVIs was difficult due to poor membrane expression and low signal-to-noise ratio, newer and more sensitive GEVIs have begun to make them useful for answering fundamental questions in neuroscience. We discuss principles of imaging using GEVIs and genetically encoded calcium indicators, both useful tools for in vivo imaging of neuronal activity, and review some of the recent mechanistic advances that have led to GEVI improvements. We provide an overview of the mouse olfactory bulb (OB) and discuss recent studies using the GEVI ArcLight to study different cell types within the bulb using both widefield and two-photon microscopy. Specific emphasis is placed on using GEVIs to begin to study the principles of concentration coding in the OB, how to interpret the optical signals from population measurements in the in vivo brain, and future developments that will push the field forward.

Reciprocal processes of sensory perception and social bonding: an integrated social-sensory framework of social behavior

Organisms filter the complexity of natural stimuli through their individual sensory and perceptual systems. Such perceptual filtering is particularly important for social stimuli. A shared "social umwelt" allows individuals to respond appropriately to the expected diversity of cues and signals during social interactions. In this way, the behavioral and neurobiological mechanisms of sociality and social bonding cannot be disentangled from perceptual mechanisms and sensory processing. While a degree of embeddedness between social and sensory processes is clear, our dominant theoretical frameworks favor treating the social and sensory processes as distinct. An integrated social-sensory framework has the potential to greatly expand our understanding of the mechanisms underlying individual variation in social bonding and sociality more broadly. Here we leverage what is known about sensory processing and pair bonding in two common study systems with significant species differences in their umwelt (rodent chemosensation and avian acoustic communication). We primarily highlight that (1) communication is essential for pair bond formation and maintenance, (2) the neural circuits underlying perception, communication and social bonding are integrated, and (3) candidate neuromodulatory mechanisms that regulate pair bonding also impact communication and perception. Finally, we propose approaches and frameworks that more fully integrate sensory processing, communication, and social bonding across levels of analysis: behavioral, neurobiological, and genomic. This perspective raises two key questions: (1) how is social bonding shaped by differences in sensory processing?, and (2) to what extent is sensory processing and the saliency of signals shaped by social interactions and emerging relationships?

How the insect central complex could coordinate multimodal navigation

The central complex of the insect midbrain is thought to coordinate insect guidance strategies. Computational models can account for specific behaviours, but their applicability across sensory and task domains remains untested. Here, we assess the capacity of our previous model (Sun et al. 2020) of visual navigation to generalise to olfactory navigation and its coordination with other guidance in flies and ants. We show that fundamental to this capacity is the use of a biologically plausible neural copy-and-shift mechanism that ensures sensory information is presented in a format compatible with the insect steering circuit regardless of its source. Moreover, the same mechanism is shown to allow the transfer cues from unstable/egocentric to stable/geocentric frames of reference, providing a first account of the mechanism by which foraging insects robustly recover from environmental disturbances. We propose that these circuits can be flexibly repurposed by different insect navigators to address their unique ecological needs.

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

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

Principles of odor coding in vertebrates and artificial chemosensory systems

The biological olfactory system is the sensory system responsible for the detection of the chemical composition of the environment. Several attempts to mimic biological olfactory systems have led to various artificial olfactory systems using different technical approaches. Here we provide a parallel description of biological olfactory systems and their technical counterparts. We start with a presentation of the input to the systems, the stimuli, and treat the interface between the external world and the environment where receptor neurons or artificial chemosensors reside. We then delineate the functions of receptor neurons and chemosensors as well as their overall I-O relationships. Up to this point, our account of the systems goes along similar lines. The next processing steps differ considerably: while in biology the processing step following the receptor neurons is the "integration" and "processing" of receptor neuron outputs in the olfactory bulb, this step has various realizations in electronic noses. For a long period of time, the signal processing stages beyond the olfactory bulb, i.e., the higher olfactory centers were little studied. Only recently there has been a marked growth of studies tackling the information processing in these centers. In electronic noses, a third stage of processing has virtually never been considered. In this review, we provide an up-to-date overview of the current knowledge of both fields and, for the first time, attempt to tie them together. We hope it will be a breeding ground for better information, communication, and data exchange between very related but so far little connected fields.

Cannabinoids Regulate Sensory Processing in Early Olfactory and Visual Neural Circuits

Our sensory systems such as the olfactory and visual systems are the target of neuromodulatory regulation. This neuromodulation starts at the level of sensory receptors and extends into cortical processing. A relatively new group of neuromodulators includes cannabinoids. These form a group of chemical substances that are found in the cannabis plant. Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) are the main cannabinoids. THC acts in the brain and nervous system like the chemical substances that our body produces, the endogenous cannabinoids or endocannabinoids, also nicknamed the brain's own cannabis. While the function of the endocannabinoid system is understood fairly well in limbic structures such as the hippocampus and the amygdala, this signaling system is less well understood in the olfactory pathway and the visual system. Here, we describe and compare endocannabinoids as signaling molecules in the early processing centers of the olfactory and visual system, the olfactory bulb, and the retina, and the relevance of the endocannabinoid system for synaptic plasticity.

A physicochemical model of odor sampling

We present a general physicochemical sampling model for olfaction, based on established pharmacological laws, in which arbitrary combinations of odorant ligands and receptors can be generated and their individual and collective effects on odor representations and olfactory performance measured. Individual odor ligands exhibit receptor-specific affinities and efficacies; that is, they may bind strongly or weakly to a given receptor, and can act as strong agonists, weak agonists, partial agonists, or antagonists. Ligands interacting with common receptors compete with one another for dwell time; these competitive interactions appropriately simulate the degeneracy that fundamentally defines the capacities and limitations of odorant sampling. The outcome of these competing ligand-receptor interactions yields a pattern of receptor activation levels, thereafter mapped to glomerular presynaptic activation levels based on the convergence of sensory neuron axons. The metric of greatest interest is the mean discrimination sensitivity, a measure of how effectively the olfactory system at this level is able to recognize a small change in the physicochemical quality of a stimulus. This model presents several significant outcomes, both expected and surprising. First, adding additional receptors reliably improves the system's discrimination sensitivity. Second, in contrast, adding additional ligands to an odorscene initially can improve discrimination sensitivity, but eventually will reduce it as the number of ligands increases. Third, the presence of antagonistic ligand-receptor interactions produced clear benefits for sensory system performance, generating higher absolute discrimination sensitivities and increasing the numbers of competing ligands that could be present before discrimination sensitivity began to be impaired. Finally, the model correctly reflects and explains the modest reduction in odor discrimination sensitivity exhibited by transgenic mice in which the specificity of glomerular targeting by primary olfactory neurons is partially disrupted.

Extrinsic neuromodulation in the rodent olfactory bulb

Evolutionarily, olfaction is one of the oldest senses and pivotal for an individual's health and survival. The olfactory bulb (OB), as the first olfactory relay station in the brain, is known to heavily process sensory information. To adapt to an animal's needs, OB activity can be influenced by many factors either from within (intrinsic neuromodulation) or outside (extrinsic neuromodulation) the OB which include neurotransmitters, neuromodulators, hormones, and neuropeptides. Extrinsic sources seem to be of special importance as the OB receives massive efferent input from numerous brain centers even outweighing the sensory input from the nose. Here, we review neuromodulatory processes in the rodent OB from such extrinsic sources. We will discuss extrinsic neuromodulation according to points of origin, receptors involved, affected circuits, and changes in behavior. In the end, we give a brief outlook on potential future directions in research on neuromodulation in the OB.

A Systematic Framework for Olfactory Bulb Signal Transformations

We describe an integrated theory of olfactory systems operation that incorporates experimental findings across scales, stages, and methods of analysis into a common framework. In particular, we consider the multiple stages of olfactory signal processing as a collective system, in which each stage samples selectively from its antecedents. We propose that, following the signal conditioning operations of the nasal epithelium and glomerular-layer circuitry, the plastic external plexiform layer of the olfactory bulb effects a process of category learning-the basis for extracting meaningful, quasi-discrete odor representations from the metric space of undifferentiated olfactory quality. Moreover, this early categorization process also resolves the foundational problem of how odors of interest can be recognized in the presence of strong competitive interference from simultaneously encountered background odorants. This problem is fundamentally constraining on early-stage olfactory encoding strategies and must be resolved if these strategies and their underlying mechanisms are to be understood. Multiscale general theories of olfactory systems operation are essential in order to leverage the analytical advantages of engineered approaches together with our expanding capacity to interrogate biological systems.

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

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

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

Author summary

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

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

Mosaic representations of odors in the input and output layers of the mouse olfactory bulb

The elementary stimulus features encoded by the olfactory system remain poorly understood. We examined the relationship between 1,666 physical-chemical descriptors of odors and the activity of olfactory bulb inputs and outputs in awake mice. Glomerular and mitral and tufted cell responses were sparse and locally heterogeneous, with only a weak dependence of their positions on physical-chemical properties. Odor features represented by ensembles of mitral and tufted cells were overlapping but distinct from those represented in glomeruli, which is consistent with an extensive interplay between feedforward and feedback inputs to the bulb. This reformatting was well described as a rotation in odor space. The physical-chemical descriptors accounted for a small fraction in response variance, and the similarity of odors in the physical-chemical space was a poor predictor of similarity in neuronal representations. Our results suggest that commonly used physical-chemical properties are not systematically represented in bulbar activity and encourage further searches for better descriptors of odor space.

Primacy coding facilitates effective odor discrimination when receptor sensitivities are tuned

The olfactory system faces the difficult task of identifying an enormous variety of odors independent of their intensity. Primacy coding, where the odor identity is encoded by the receptor types that respond earliest, might provide a compact and informative representation that can be interpreted efficiently by the brain. In this paper, we analyze the information transmitted by a simple model of primacy coding using numerical simulations and statistical descriptions. We show that the encoded information depends strongly on the number of receptor types included in the primacy representation, but only weakly on the size of the receptor repertoire. The representation is independent of the odor intensity and the transmitted information is useful to perform typical olfactory tasks with close to experimentally measured performance. Interestingly, we find situations in which a smaller receptor repertoire is advantageous for discriminating odors. The model also suggests that overly sensitive receptor types could dominate the entire response and make the whole array useless, which allows us to predict how receptor arrays need to adapt to stay useful during environmental changes. Taken together, we show that primacy coding is more useful than simple binary and normalized coding, essentially because the sparsity of the odor representations is independent of the odor statistics, in contrast to the alternatives. Primacy coding thus provides an efficient odor representation that is independent of the odor intensity and might thus help to identify odors in the olfactory cortex.

Humans can identify odors independent of their intensity. Experimental data suggest that this is accomplished by representing the odor identity by the earliest responding receptor types. Using theoretical modeling, we here show that such a primacy code outperforms alternative encodings and allows discriminating odors with close to experimentally measured performance. This performance depends strongly on the number of receptors considered in the primacy code, but the receptor repertoire size is less important. The model also suggests a strong evolutionary pressure on the receptor sensitivities, which could explain observed receptor copy number adaptations. By predicting psycho-physical experiments, the model will thus contribute to our understanding of the olfactory system.

Connectivity of neuronal populations within and between areas of primate somatosensory cortex

Functions of the cerebral cortex emerge via interactions of horizontally distributed neuronal populations within and across areas. However, the connectional underpinning of these interactions is not well understood. The present study explores the circuitry of column-size cortical domains within the hierarchically organized somatosensory cortical areas 3b and 1 using tract tracing and optical intrinsic signal imaging (OIS). The anatomical findings reveal that feedforward connections exhibit high topographic specificity, while intrinsic and feedback connections have a more widespread distribution. Both intrinsic and inter-areal connections are topographically oriented across the finger representations. Compared to area 3b, the low clustering of connections and small cortical magnification factor supports that the circuitry of area 1 scaffolds a sparse functional representation that integrates peripheral information from a large area that is fed back to area 3b. Fast information exchange between areas is ensured by thick axons forming a topographically organized, reciprocal pathway. Moreover, the highest density of projecting neurons and groups of axon arborization patches corresponds well with the size and locations of the functional population response reported by OIS. The findings establish connectional motifs at the mesoscopic level that underpin the functional organization of the cerebral cortex.

Noradrenergic effects on olfactory perception and learning

We here review modulation of olfactory guided behavioral tasks by noradrenaline. In this review we focus on modulation of the main olfactory system in adult rodents. We detail behavioral paradigms commonly used and discuss how sensory perception and learning can be measured using these paradigms. We then describe neuromodulatory effects on several aspects of olfactory processing, including detection and encoding. We describe how memory duration, specificity and duration are affected by noradrenergic modulation.

Computing Odor Images

This perspective examines psychophysical methods that may reveal the algorithms that encode odor images by integrating current data from sensory measurement into a computational model of odor perception. There is evidence that algorithms used by the nervous system to process odor sensations require input from only a few odorants, between three and eight. Furthermore, the number of recognizable odors in foods that contribute anything to the aroma of all foods is approximately 250. This may imply that it is the ratio of a small number of key odorants (KOs) that create a multitude of food odors. Studies with large mixtures of odorants (formulated to be of equal potency) show that a subject's ability to detect individual odorants in these mixtures was vanishingly small. These large mixtures had weak and nondescript but similar odor character. If only a few stimulants are used to represent complex images, it is direct evidence of the simplicity and therefore the tractability of the computational process.

History-Dependent Odor Processing in the Mouse Olfactory Bulb

In nature, animals normally perceive sensory information on top of backgrounds. Thus, the neural substrate to perceive under background conditions is inherent in all sensory systems. Where and how sensory systems process backgrounds is not fully understood. In olfaction, just a few studies have addressed the issue of odor coding on top of continuous odorous backgrounds. Here, we tested how background odors are encoded by mitral cells (MCs) in the olfactory bulb (OB) of male mice. Using in vivo two-photon calcium imaging, we studied how MCs responded to odors in isolation versus their responses to the same odors on top of continuous backgrounds. We show that MCs adapt to continuous odor presentation and that mixture responses are different when preceded by background. In a subset of odor combinations, this history-dependent processing was useful in helping to identify target odors over background. Other odorous backgrounds were highly dominant such that target odors were completely masked by their presence. Our data are consistent in both low and high odor concentrations and in anesthetized and awake mice. Thus, odor processing in the OB is strongly influenced by the recent history of activity, which could have a powerful impact on how odors are perceived.

SIGNIFICANCE STATEMENT We examined a basic feature of sensory processing in the olfactory bulb. Specifically, we measured how mitral cells adapt to continuous background odors and how target odors are encoded on top of such background. Our results show clear differences in odor coding based on the immediate history of the stimulus. Our results support the argument that odor coding in the olfactory bulb depends on the recent history of the sensory environment.

Stimulation of the Locus Ceruleus Modulates Signal-to-Noise Ratio in the Olfactory Bulb

Norepinephrine (NE) has been shown to influence sensory, and specifically olfactory processing at the behavioral and physiological levels, potentially by regulating signal-to-noise ratio (S/N). The present study is the first to look at NE modulation of olfactory bulb (OB) in regards to S/N in vivo We show, in male rats, that locus ceruleus stimulation and pharmacological infusions of NE into the OB modulate both spontaneous and odor-evoked neural responses. NE in the OB generated a non-monotonic dose-response relationship, suppressing mitral cell activity at high and low, but not intermediate, NE levels. We propose that NE enhances odor responses not through direct potentiation of the afferent signal per se, but rather by reducing the intrinsic noise of the system. This has important implications for the ways in which an animal interacts with its olfactory environment, particularly as the animal shifts from a relaxed to an alert behavioral state.SIGNIFICANCE STATEMENT Sensory perception can be modulated by behavioral states such as hunger, fear, stress, or a change in environmental context. Behavioral state often affects neural processing via the release of circulating neurochemicals such as hormones or neuromodulators. We here show that the neuromodulator norepinephrine modulates olfactory bulb spontaneous activity and odor responses so as to generate an increased signal-to-noise ratio at the output of the olfactory bulb. Our results help interpret and improve existing ideas for neural network mechanisms underlying behaviorally observed improvements in near-threshold odor detection and discrimination.

Inhibitory circuits of the mammalian main olfactory bulb

Synaptic inhibition critically influences sensory processing throughout the mammalian brain, including the main olfactory bulb (MOB), the first station of sensory processing in the olfactory system. Decades of research across numerous laboratories have established a central role for granule cells (GCs), the most abundant GABAergic interneuron type in the MOB, in the precise regulation of principal mitral and tufted cell (M/TC) firing rates and synchrony through lateral and recurrent inhibitory mechanisms. In addition to GCs, however, the MOB contains a vast diversity of other GABAergic interneuron types, and recent findings suggest that, while fewer in number, these oft-ignored interneurons are just as important as GCs in shaping odor-evoked M/TC activity. Here I challenge the prevailing centrality of GCs. In this review, I first outline the specific properties of each GABAergic interneuron type in the rodent MOB, with particular emphasis placed on direct interneuron recordings and cell type-selective manipulations. On the basis of these properties, I then critically reevaluate the contribution of GCs vs. other interneuron types to the regulation of odor-evoked M/TC firing rates and synchrony via lateral, recurrent, and other inhibitory mechanisms. This analysis yields a novel model in which multiple interneuron types with distinct abundances, connectivity patterns, and physiologies complement one another to regulate M/TC activity and sensory processing.

Population Coding in an Innately Relevant Olfactory Area

Different olfactory cortical regions are thought to harbor distinct sensory representations, enabling each area to play a unique role in odor perception and behavior. In the piriform cortex (PCx), spatially dispersed sensory inputs evoke activity in distributed ensembles of neurons that act as substrates for odor learning. In contrast, the posterolateral cortical amygdala (plCoA) receives hardwired inputs that may link specific odor cues to innate olfactory behaviors. Here we show that despite stark differences in the patterning of plCoA and PCx inputs, odor-evoked neural ensembles in both areas are equally capable of discriminating odors, and exhibit similar odor tuning, reliability, and correlation structure. These results demonstrate that brain regions mediating odor-driven innate behaviors can, like brain areas involved in odor learning, represent odor objects using distributive population codes; these findings suggest both alternative mechanisms for the generation of innate odor-driven behaviors and additional roles for the plCoA in odor perception.

Presynaptic gain control by endogenous cotransmission of dopamine and GABA in the olfactory bulb

In the olfactory bulb, lateral inhibition mediated by local juxtaglomerular interneurons has been proposed as a gain control mechanism, important for decorrelating odorant responses. Among juxtaglomerular interneurons, short axon cells are unique as dual-transmitter neurons that release dopamine and GABA. To examine their intraglomerular function, we expressed channelrhodopsin under control of the DAT-cre promoter and activated olfactory afferents within individual glomeruli. Optical stimulation of labeled cells triggered endogenous dopamine release as measured by cyclic voltammetry and GABA release as measured by whole cell GABA_A receptor currents. Activation of short axon cells reduced the afferent presynaptic release probability via D₂ and GABA_B receptor activation, resulting in reduced spiking in both mitral and external tufted cells. Our results suggest that short axon cells influence glomerular activity not only by direct inhibition of external tufted cells but also by inhibition of afferent inputs to external tufted and mitral cells.NEW & NOTEWORTHY Sensory systems, including the olfactory system, encode information across a large dynamic range, making synaptic mechanisms of gain control critical to proper function. Here we demonstrate that a dual-transmitter interneuron in the olfactory bulb controls the gain of intraglomerular afferent input via two distinct mechanisms, presynaptic inhibition as well as inhibition of a principal neuron subtype, and thereby potently controls the synaptic gain of afferent inputs.

Differences in Glomerular-Layer-Mediated Feedforward Inhibition onto Mitral and Tufted Cells Lead to Distinct Modes of Intensity Coding

Understanding how each of the many interneuron subtypes affects brain network activity is critical. In the mouse olfactory system, mitral cells (MCs) and tufted cells (TCs) comprise parallel pathways of olfactory bulb output that are thought to play distinct functional roles in odor coding. Here, in acute mouse olfactory bulb slices, we test how the two major classes of olfactory bulb interneurons differentially contribute to differences in MC versus TC response properties. We show that, whereas TCs respond to olfactory sensory neuron (OSN) stimulation with short latencies regardless of stimulation intensity, MC latencies correlate negatively with stimulation intensity. These differences between MCs and TCs are caused in part by weaker excitatory and stronger inhibitory currents onto MCs than onto TCs. These differences in inhibition between MCs and TCs are most pronounced during the first 150 ms after stimulation and are mediated by glomerular layer circuits. Therefore, blocking inhibition originating in the glomerular layer, but not granule-cell-mediated inhibition, reduces MC spike latency at weak stimulation intensities and distinct temporal patterns of odor-evoked responses in MCs and TCs emerge in part due to differences in glomerular-layer-mediated inhibition.SIGNIFICANCE STATEMENT Olfactory bulb mitral and tufted cells display different odor-evoked responses and are thought to form parallel channels of olfactory bulb output. Therefore, determining the circuit-level causes that drive these differences is vital. Here, we find that longer-latency responses in mitral cells, compared with tufted cells, are due to weaker excitation and stronger glomerular-layer-mediated inhibition.

A probabilistic approach to demixing odors

The olfactory system faces a hard problem: on the basis of noisy information from olfactory receptor neurons (the neurons that transduce chemicals to neural activity), it must figure out which odors are present in the world. Odors almost never occur in isolation, and different odors excite overlapping populations of olfactory receptor neurons, so the central challenge of the olfactory system is to demix its input. Because of noise and the large number of possible odors, demixing is fundamentally a probabilistic inference task. We propose that the early olfactory system uses approximate Bayesian inference to solve it. The computations involve a dynamical loop between the olfactory bulb and the piriform cortex, with cortex explaining incoming activity from the olfactory receptor neurons in terms of a mixture of odors. The model is compatible with known anatomy and physiology, including pattern decorrelation, and it performs better than other models at demixing odors.

Normalized Neural Representations of Complex Odors

The olfactory system removes correlations in natural odors using a network of inhibitory neurons in the olfactory bulb. It has been proposed that this network integrates the response from all olfactory receptors and inhibits them equally. However, how such global inhibition influences the neural representations of odors is unclear. Here, we study a simple statistical model of the processing in the olfactory bulb, which leads to concentration-invariant, sparse representations of the odor composition. We show that the inhibition strength can be tuned to obtain sparse representations that are still useful to discriminate odors that vary in relative concentration, size, and composition. The model reveals two generic consequences of global inhibition: (i) odors with many molecular species are more difficult to discriminate and (ii) receptor arrays with heterogeneous sensitivities perform badly. Comparing these predictions to experiments will help us to understand the role of global inhibition in shaping normalized odor representations in the olfactory bulb.

Neuromodulation of olfactory transformations

The olfactory bulb and piriform cortex are the best studied structures of the mammalian olfactory system and are heavily innervated by extrinsic neuromodulatory inputs. The state-dependent release of acetylcholine, norepinephrine, serotonin, and other neuromodulators into these olfactory structures alters a constellation of physiological parameters in neurons and synapses that together modify the computations performed on sensory signals. These modifications affect the specificity, detectability, discriminability, and other properties of odor representations and thereby govern perceptual performance. Whereas different neuromodulators have distinct cellular effects, and tend to be associated with nominally different functions, it also is clear that these purported functions overlap substantially, and that ad hoc hypotheses regarding the roles of particular neuromodulators may have reached the limits of their usefulness.

Adult Olfactory Bulb Neurogenesis

Most organisms use their olfactory system to detect and analyze chemical cues from the external world to guide essential behaviors. From worms to vertebrates, chemicals are detected by odorant receptors expressed by olfactory sensory neurons, which in vertebrates send an axon to the primary processing center called the olfactory bulb (OB). Within the OB, sensory neurons form excitatory synapses with projection neurons and with inhibitory interneurons. Thus, because of complex synaptic interactions, the output of a given projection neuron is determined not only by the sensory input, but also by the activity of local inhibitory interneurons that are regenerated throughout life in the process of adult neurogenesis. Herein, we discuss how it is optimized and why.

Population imaging at subcellular resolution supports specific and local inhibition by granule cells in the olfactory bulb

Information processing in early sensory regions is modulated by a diverse range of inhibitory interneurons. We sought to elucidate the role of olfactory bulb interneurons called granule cells (GCs) in odor processing by imaging the activity of hundreds of these cells simultaneously in mice. Odor responses in GCs were temporally diverse and spatially disperse, with some degree of non-random, modular organization. The overall sparseness of activation of GCs was highly correlated with the extent of glomerular activation by odor stimuli. Increasing concentrations of single odorants led to proportionately larger population activity, but some individual GCs had non-monotonic relations to concentration due to local inhibitory interactions. Individual dendritic segments could sometimes respond independently to odors, revealing their capacity for compartmentalized signaling in vivo. Collectively, the response properties of GCs point to their role in specific and local processing, rather than global operations such as response normalization proposed for other interneurons.

Perception as a closed-loop convergence process

Perception of external objects involves sensory acquisition via the relevant sensory organs. A widely-accepted assumption is that the sensory organ is the first station in a serial chain of processing circuits leading to an internal circuit in which a percept emerges. This open-loop scheme, in which the interaction between the sensory organ and the environment is not affected by its concurrent downstream neuronal processing, is strongly challenged by behavioral and anatomical data. We present here a hypothesis in which the perception of external objects is a closed-loop dynamical process encompassing loops that integrate the organism and its environment and converging towards organism-environment steady-states. We discuss the consistency of closed-loop perception (CLP) with empirical data and show that it can be synthesized in a robotic setup. Testable predictions are proposed for empirical distinction between open and closed loop schemes of perception.

Computational Modeling of Adult Neurogenesis

The restriction of adult neurogenesis to only a handful of regions of the brain is suggestive of some shared requirement for this dramatic form of structural plasticity. However, a common driver across neurogenic regions has not yet been identified. Computational studies have been invaluable in providing insight into the functional role of new neurons; however, researchers have typically focused on specific scales ranging from abstract neural networks to specific neural systems, most commonly the dentate gyrus area of the hippocampus. These studies have yielded a number of diverse potential functions for new neurons, ranging from an impact on pattern separation to the incorporation of time into episodic memories to enabling the forgetting of old information. This review will summarize these past computational efforts and discuss whether these proposed theoretical functions can be unified into a common rationale for why neurogenesis is required in these unique neural circuits.

Biophysical constraints on lateral inhibition in the olfactory bulb

The mitral cells (MCs) of the mammalian olfactory bulb (OB) constitute one of two populations of principal neurons (along with middle/deep tufted cells) that integrate afferent olfactory information with top-down inputs and intrinsic learning and deliver output to downstream olfactory areas. MC activity is regulated in part by inhibition from granule cells, which form reciprocal synapses with MCs along the extents of their lateral dendrites. However, with MC lateral dendrites reaching over 1.5 mm in length in rats, the roles of distal inhibitory synapses pose a quandary. Here, we systematically vary the properties of a MC model to assess the capacity of inhibitory synaptic inputs on lateral dendrites to influence afferent information flow through MCs. Simulations using passivized models with varying dendritic morphologies and synaptic properties demonstrated that, even with unrealistically favorable parameters, passive propagation fails to convey effective inhibitory signals to the soma from distal sources. Additional simulations using an active model exhibiting action potentials, subthreshold oscillations, and a dendritic morphology closely matched to experimental values further confirmed that distal synaptic inputs along the lateral dendrite could not exert physiologically relevant effects on MC spike timing at the soma. Larger synaptic conductances representative of multiple simultaneous inputs were not sufficient to compensate for the decline in signal with distance. Reciprocal synapses on distal MC lateral dendrites may instead serve to maintain a common fast oscillatory clock across the OB by delaying spike propagation within the lateral dendrites themselves.

Rapid Feedforward Inhibition and Asynchronous Excitation Regulate Granule Cell Activity in the Mammalian Main Olfactory Bulb

Granule cell-mediated inhibition is critical to patterning principal neuron activity in the olfactory bulb, and perturbation of synaptic input to granule cells significantly alters olfactory-guided behavior. Despite the critical role of granule cells in olfaction, little is known about how sensory input recruits granule cells. Here, we combined whole-cell patch-clamp electrophysiology in acute mouse olfactory bulb slices with biophysical multicompartmental modeling to investigate the synaptic basis of granule cell recruitment. Physiological activation of sensory afferents within single glomeruli evoked diverse modes of granule cell activity, including subthreshold depolarization, spikelets, and suprathreshold responses with widely distributed spike latencies. The generation of these diverse activity modes depended, in part, on the asynchronous time course of synaptic excitation onto granule cells, which lasted several hundred milliseconds. In addition to asynchronous excitation, each granule cell also received synchronous feedforward inhibition. This inhibition targeted both proximal somatodendritic and distal apical dendritic domains of granule cells, was reliably recruited across sniff rhythms, and scaled in strength with excitation as more glomeruli were activated. Feedforward inhibition onto granule cells originated from deep short-axon cells, which responded to glomerular activation with highly reliable, short-latency firing consistent with tufted cell-mediated excitation. Simulations showed that feedforward inhibition interacts with asynchronous excitation to broaden granule cell spike latency distributions and significantly attenuates granule cell depolarization within local subcellular compartments. Collectively, our results thus identify feedforward inhibition onto granule cells as a core feature of olfactory bulb circuitry and establish asynchronous excitation and feedforward inhibition as critical regulators of granule cell activity.

SIGNIFICANCE STATEMENT

Inhibitory granule cells are involved critically in shaping odor-evoked principal neuron activity in the mammalian olfactory bulb, yet little is known about how sensory input activates granule cells. Here, we show that sensory input to the olfactory bulb evokes a barrage of asynchronous synaptic excitation and highly reliable, short-latency synaptic inhibition onto granule cells via a disynaptic feedforward inhibitory circuit involving deep short-axon cells. Feedforward inhibition attenuates local depolarization within granule cell dendritic branches, interacts with asynchronous excitation to suppress granule cell spike-timing precision, and scales in strength with excitation across different levels of sensory input to normalize granule cell firing rates.

An Interglomerular Circuit Gates Glomerular Output and Implements Gain Control in the Mouse Olfactory Bulb

Odors elicit distributed activation of glomeruli in the olfactory bulb (OB). Crosstalk between co-active glomeruli has been proposed to perform a variety of computations, facilitating efficient extraction of sensory information by the cortex. Dopaminergic/GABAergic cells in the OB, which can be identified by their expression of the dopamine transporter (DAT), provide the earliest opportunity for such crosstalk. Here we show in mice that DAT+ cells carry concentration-dependent odor signals and broadcast focal glomerular inputs throughout the OB to cause suppression of mitral/tufted (M/T) cell firing, an effect that is mediated by the external tufted (ET) cells coupled to DAT+ cells via chemical and electrical synapses. We find that DAT+ cells implement gain control and decorrelate odor representations in the M/T cell population. Our results further indicate that ET cells are gatekeepers of glomerular output and prime determinants of M/T responsiveness.

Stable odor recognition by a neuro-adaptive electronic nose

Sensitivity, selectivity and stability are decisive properties of sensors. In chemical gas sensors odor recognition can be severely compromised by poor signal stability, particularly in real life applications where the sensors are exposed to unpredictable sequences of odors under changing external conditions. Although olfactory receptor neurons in the nose face similar stimulus sequences under likewise changing conditions, odor recognition is very stable and odorants can be reliably identified independently from past odor perception. We postulate that appropriate pre-processing of the output signals of chemical sensors substantially contributes to the stability of odor recognition, in spite of marked sensor instabilities. To investigate this hypothesis, we use an adaptive, unsupervised neural network inspired by the glomerular input circuitry of the olfactory bulb. Essentially the model reduces the effect of the sensors’ instabilities by utilizing them via an adaptive multicompartment feed-forward inhibition. We collected and analyzed responses of a 4 × 4 gas sensor array to a number of volatile compounds applied over a period of 18 months, whereby every sensor was sampled episodically. The network conferred excellent stability to the compounds’ identification and was clearly superior over standard classifiers, even when one of the sensors exhibited random fluctuations or stopped working at all.

Posttraining ablation of adult-generated olfactory granule cells degrades odor-reward memories

Proliferation of neural progenitor cells in the subventricular zone leads to the continuous generation of new olfactory granule cells (OGCs) throughout life. These cells synaptically integrate into olfactory bulb circuits after ∼2 weeks and transiently exhibit heightened plasticity and responses to novel odors. Although these observations suggest that adult-generated OGCs play important roles in olfactory-related memories, global suppression of olfactory neurogenesis does not typically prevent the formation of odor-reward memories, perhaps because residual OGCs can compensate. Here, we used a transgenic strategy to selectively ablate large numbers of adult-generated OGCs either before or after learning in mice. Consistent with previous studies, pretraining ablation of adult-generated OGCs did not prevent the formation of an odor-reward memory, presumably because existing OGCs can support memory formation in their absence. However, ablation of a similar cohort of adult-generated OGCs after training impaired subsequent memory expression, indicating that if these cells are available at the time of training, they play an essential role in subsequent expression of odor-reward memories. Memory impairment was associated with the loss of adult-generated OGCs that were >10 d in age and did not depend on the developmental stage in which they were generated, suggesting that, once sufficiently mature, OGCs generated during juvenility and adulthood play similar roles in the expression of odor-reward memories. Finally, ablation of adult-generated OGCs 1 month after training did not produce amnesia, indicating that adult-generated OGCs play a time-limited role in the expression of odor-reward memories.

Learning modulation of odor representations: new findings from Arc-indexed networks

We first review our understanding of odor representations in rodent olfactory bulb (OB) and anterior piriform cortex (APC). We then consider learning-induced representation changes. Finally we describe the perspective on network representations gained from examining Arc-indexed odor networks of awake rats. Arc-indexed networks are sparse and distributed, consistent with current views. However Arc provides representations of repeated odors. Arc-indexed repeated odor representations are quite variable. Sparse representations are assumed to be compact and reliable memory codes. Arc suggests this is not necessarily the case. The variability seen is consistent with electrophysiology in awake animals and may reflect top-down cortical modulation of context. Arc-indexing shows that distinct odors share larger than predicted neuron pools. These may be low-threshold neuronal subsets. Learning’s effect on Arc-indexed representations is to increase the stable or overlapping component of rewarded odor representations. This component can decrease for similar odors when their discrimination is rewarded. The learning effects seen are supported by electrophysiology, but mechanisms remain to be elucidated.

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.

A simple model of optimal population coding for sensory systems

A fundamental task of a sensory system is to infer information about the environment. It has long been suggested that an important goal of the first stage of this process is to encode the raw sensory signal efficiently by reducing its redundancy in the neural representation. Some redundancy, however, would be expected because it can provide robustness to noise inherent in the system. Encoding the raw sensory signal itself is also problematic, because it contains distortion and noise. The optimal solution would be constrained further by limited biological resources. Here, we analyze a simple theoretical model that incorporates these key aspects of sensory coding, and apply it to conditions in the retina. The model specifies the optimal way to incorporate redundancy in a population of noisy neurons, while also optimally compensating for sensory distortion and noise. Importantly, it allows an arbitrary input-to-output cell ratio between sensory units (photoreceptors) and encoding units (retinal ganglion cells), providing predictions of retinal codes at different eccentricities. Compared to earlier models based on redundancy reduction, the proposed model conveys more information about the original signal. Interestingly, redundancy reduction can be near-optimal when the number of encoding units is limited, such as in the peripheral retina. We show that there exist multiple, equally-optimal solutions whose receptive field structure and organization vary significantly. Among these, the one which maximizes the spatial locality of the computation, but not the sparsity of either synaptic weights or neural responses, is consistent with known basic properties of retinal receptive fields. The model further predicts that receptive field structure changes less with light adaptation at higher input-to-output cell ratios, such as in the periphery.

Studies of the computational principles of sensory coding have largely focused on the redundancy reduction hypothesis, which posits that a neural population should encode the raw sensory signal efficiently by reducing its redundancy. Models based on this idea, however, have not taken into account some important aspects of sensory systems. First, neurons are noisy, and therefore, some redundancy in the code can be useful for transmitting information reliably. Second, the sensory signal itself is noisy, which should be counteracted as early as possible in the sensory pathway. Finally, neural resources such as the number of neurons are limited, which should strongly affect the form of the sensory code. Here we examine a simple model that takes all these factors into account. We find that the model conveys more information compared to redundancy reduction. When applied to the retina, the model provides a unified functional account for several known properties of retinal coding and makes novel predictions that have yet to be tested experimentally. The generality of the framework allows it to model a wide range of conditions and can be applied to predict optimal sensory coding in other systems.

A spiking neural network model of self-organized pattern recognition in the early mammalian olfactory system

Olfactory sensory information passes through several processing stages before an odor percept emerges. The question how the olfactory system learns to create odor representations linking those different levels and how it learns to connect and discriminate between them is largely unresolved. We present a large-scale network model with single and multi-compartmental Hodgkin-Huxley type model neurons representing olfactory receptor neurons (ORNs) in the epithelium, periglomerular cells, mitral/tufted cells and granule cells in the olfactory bulb (OB), and three types of cortical cells in the piriform cortex (PC). Odor patterns are calculated based on affinities between ORNs and odor stimuli derived from physico-chemical descriptors of behaviorally relevant real-world odorants. The properties of ORNs were tuned to show saturated response curves with increasing concentration as seen in experiments. On the level of the OB we explored the possibility of using a fuzzy concentration interval code, which was implemented through dendro-dendritic inhibition leading to winner-take-all like dynamics between mitral/tufted cells belonging to the same glomerulus. The connectivity from mitral/tufted cells to PC neurons was self-organized from a mutual information measure and by using a competitive Hebbian-Bayesian learning algorithm based on the response patterns of mitral/tufted cells to different odors yielding a distributed feed-forward projection to the PC. The PC was implemented as a modular attractor network with a recurrent connectivity that was likewise organized through Hebbian-Bayesian learning. We demonstrate the functionality of the model in a one-sniff-learning and recognition task on a set of 50 odorants. Furthermore, we study its robustness against noise on the receptor level and its ability to perform concentration invariant odor recognition. Moreover, we investigate the pattern completion capabilities of the system and rivalry dynamics for odor mixtures.

Parvalbumin-expressing interneurons linearly control olfactory bulb output

In the olfactory bulb, odor representations by principal mitral cells are modulated by local inhibitory circuits. While dendrodendritic synapses between mitral and granule cells are typically thought to be a major source of this modulation, the contributions of other inhibitory neurons remain unclear. Here we demonstrate the functional properties of olfactory bulb parvalbumin-expressing interneurons (PV cells) and identify their important role in odor coding. Using paired recordings, we find that PV cells form reciprocal connections with the majority of nearby mitral cells, in contrast to the sparse connectivity between mitral and granule cells. In vivo calcium imaging in awake mice reveals that PV cells are broadly tuned to odors. Furthermore, selective PV cell inactivation enhances mitral cell responses in a linear fashion while maintaining mitral cell odor preferences. Thus, dense connections between mitral and PV cells underlie an inhibitory circuit poised to modulate the gain of olfactory bulb output.

Dissecting local circuits: parvalbumin interneurons underlie broad feedback control of olfactory bulb output

In the mouse olfactory bulb, information from sensory neurons is extensively processed by local interneurons before being transmitted to the olfactory cortex by mitral and tufted (M/T) cells. The precise function of these local networks remains elusive because of the vast heterogeneity of interneurons, their diverse physiological properties, and their complex synaptic connectivity. Here we identified the parvalbumin interneurons (PVNs) as a prominent component of the M/T presynaptic landscape by using an improved rabies-based transsynaptic tracing method for local circuits. In vivo two-photon-targeted patch recording revealed that PVNs have exceptionally broad olfactory receptive fields and exhibit largely excitatory and persistent odor responses. Transsynaptic tracing indicated that PVNs receive direct input from widely distributed M/T cells. Both the anatomical and functional extent of this M/T→PVN→M/T circuit contrasts with the narrowly confined M/T→granule cell→M/T circuit, suggesting that olfactory information is processed by multiple local circuits operating at distinct spatial scales.

Perceptual spaces: mathematical structures to neural mechanisms

A central goal of neuroscience is to understand how populations of neurons build and manipulate representations of percepts that provide useful information about the environment. This symposium explores the fundamental properties of these representations and the perceptual spaces in which they are organized. Spanning the domains of color, visual texture, environmental sound, music, tactile quality, and odor, we show how the geometric structures of perceptual spaces can be determined experimentally and how these structures provide insights into the principles of neural coding and the neural mechanisms that generate the codes, and into the neural processing of complex sensory stimuli. The diversity of the neural architecture in these different sensory systems provides an opportunity to compare their different solutions to common problems: the need for dimensionality reduction, strategies for topographic or nontopographic mapping, the utility of the higher-order statistical structure inherent in natural sensory stimuli, and the constraints of neural hardware.

Early olfactory processing in Drosophila: mechanisms and principles

In the olfactory system of Drosophila melanogaster, it is relatively straightforward to target in vivo measurements of neural activity to specific processing channels. This, together with the numerical simplicity of the Drosophila olfactory system, has produced rapid gains in our understanding of Drosophila olfaction. This review summarizes the neurophysiology of the first two layers of this system: the peripheral olfactory receptor neurons and their postsynaptic targets in the antennal lobe. We now understand in some detail the cellular and synaptic mechanisms that shape odor representations in these neurons. Together, these mechanisms imply that interesting neural adaptations to environmental statistics have occurred. These mechanisms also place some fundamental constraints on early sensory processing that pose challenges for higher brain regions. These findings suggest some general principles with broad relevance to early sensory processing in other modalities.

Temporal processing in the olfactory system: can we see a smell?

Sensory processing circuits in the visual and olfactory systems receive input from complex, rapidly changing environments. Although patterns of light and plumes of odor create different distributions of activity in the retina and olfactory bulb, both structures use what appears on the surface similar temporal coding strategies to convey information to higher areas in the brain. We compare temporal coding in the early stages of the olfactory and visual systems, highlighting recent progress in understanding the role of time in olfactory coding during active sensing by behaving animals. We also examine studies that address the divergent circuit mechanisms that generate temporal codes in the two systems, and find that they provide physiological information directly related to functional questions raised by neuroanatomical studies of Ramon y Cajal over a century ago. Consideration of differences in neural activity in sensory systems contributes to generating new approaches to understand signal processing.