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Axons from the olfactory bulb (OB) project to multiple central structures of the brain, many of which, in turn, send axons back into the OB and/or to one another. These secondary sensory regions underlie many aspects of odor representation, valence, and learning, as well as serving some nonolfactory functions, though many details remain unclear. We here describe the connectivity and essential structural and functional properties of these postbulbar olfactory regions in the mammalian brain., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Long-term fear memory formation in the hippocampus and neocortex depends upon brain-derived neurotrophic factor (BDNF) signaling after acquisition. Incremental, appetitive odor discrimination learning is thought to depend substantially on the differentiation of adult-born neurons within the olfactory bulb (OB)-a process that is closely associated with BDNF signaling. We sought to elucidate the role of neurotrophin signaling within the OB on odor memory consolidation. Male mice were trained on odor-reward associative discriminations after bilateral infusion of the kinase inhibitor K252a, or vehicle control, into the OB. K252a is a partially selective inhibitor of tyrosine kinase (Trk) receptors, including the TrkB receptor for BDNF, though it also inhibits other plasticity-related kinases such as PKC and CaMKII/IV. K252a infusion into the OB did not impair odor acquisition or short-term (2 h) memory for the learned discriminations, but significantly impaired long-term (48 h) odor memory (LTM). This LTM deficit also was associated with reduced selectivity for the conditioned odorant in a reward-seeking digging task. Infusions of K252a immediately prior to testing did not impair LTM recall. These results indicate that kinase activation in the OB is required for the consolidation of odor memory of incrementally acquired information., (© 2018 Tong et al.; Published by Cold Spring Harbor Laboratory Press.)

Generative models are computational models designed to generate appropriate values for all of their embedded variables, thereby simulating the response properties of a complex system based on the coordinated interactions of a multitude of physical mechanisms. In systems neuroscience, generative models are generally biophysically based compartmental models of neurons and networks that are explicitly multiscale, being constrained by experimental data at multiple levels of organization from cellular membrane properties to large-scale network dynamics. As such, they are able to explain the origins of emergent properties in complex systems, and serve as tests of sufficiency and as quantitative instantiations of working hypotheses that may be too complex to simply intuit. Moreover, when adequately constrained, generative biophysical models are able to predict novel experimental outcomes, and consequently are powerful tools for experimental design. We here outline a general strategy for the iterative design and implementation of generative, multiscale biophysical models of neural systems. We illustrate this process using our ongoing, iteratively developing model of the mammalian olfactory bulb. Because the olfactory bulb exhibits diverse and interesting properties at multiple scales of organization, it is an attractive system in which to illustrate the value of generative modeling across scales.

Like other sensory systems, the olfactory system transduces specific features of the external environment and must construct an organized sensory representation from these highly fragmented inputs. As with these other systems, this representation is not accurate per se, but is constructed for utility, and emphasizes certain, presumably useful, features over others. I here describe the cellular and circuit mechanisms of the peripheral olfactory system that underlie this process of sensory construction, emphasizing the distinct architectures and properties of the two prominent computational layers in the olfactory bulb. Notably, while the olfactory system solves essentially similar conceptual problems to other sensory systems, such as contrast enhancement, activity normalization, and extending dynamic range, its peculiarities often require qualitatively different computational algorithms than are deployed in other sensory modalities. In particular, the olfactory modality is intrinsically high dimensional, and lacks a simple, externally defined basis analogous to wavelength or pitch on which elemental odor stimuli can be quantitatively compared. Accordingly, the quantitative similarities of the receptive fields of different odorant receptors (ORs) vary according to the statistics of the odor environment. To resolve these unusual challenges, the olfactory bulb appears to utilize unique nontopographical computations and intrinsic learning mechanisms to perform the necessary high-dimensional, similarity-dependent computations. In sum, the early olfactory system implements a coordinated set of early sensory transformations directly analogous to those in other sensory systems, but accomplishes these with unique circuit architectures adapted to the properties of the olfactory modality., (© 2014 Elsevier B.V. All rights reserved.)

The perceptual differentiation of odors can be measured behaviorally using generalization gradients. The steepness of these gradients defines a form of olfactory acuity for odor quality that depends on neural circuitry within the olfactory bulb and is regulated by cholinergic activity therein as well as by associative learning. Using this system as a reduced model for age-related cognitive decline, we show that aged mice, while maintaining almost the same baseline behavioral performance as younger mice, are insensitive to the effects of acutely elevated acetylcholine, which sharpens generalization gradients in young adult mice. Moreover, older mice exhibit evidence of chronically elevated acetylcholine levels in the olfactory bulb, suggesting that their insensitivity to further elevated levels of acetylcholine may arise because the maximum capacity of the system to respond to acetylcholine has already been reached. We propose a model in which an underlying, age-related, progressive deficit is mitigated by a compensatory cholinergic feedback loop that acts to retard the behavioral effects of what would otherwise be a substantial age-related decline in olfactory plasticity. We also treated mice with 10-day regimens of olfactory environmental enrichment and/or repeated systemic injections of the acetylcholinesterase inhibitor physostigmine. Each treatment alone sharpened odor quality acuity, but administering both treatments together had no greater effect than either alone. Age was not a significant main effect in this study, suggesting that some capacity for acetylcholine-dependent plasticity is still present in aged mice despite their sharply reduced ability to respond to acute increases in acetylcholine levels. These results suggest a dynamical framework for understanding age-related decline in neural circuit processing in which the direct effects of aging can be mitigated, at least temporarily, by systemic compensatory responses. In particular, a decline in cholinergic efficacy can precede any breakdown in cholinergic production, which may help explain the limited effectiveness of cholinergic replacement therapies in combating cognitive decline., (Copyright © 2010 Elsevier Inc. All rights reserved.)

Sensory representations are repeatedly transformed by neural computations that determine which of their attributes can be effectively processed at each stage. Whereas some early computations are common across multiple sensory systems, they can utilize dissimilar underlying mechanisms depending on the properties of each modality. Recent work in the olfactory bulb has substantially clarified the neural algorithms underlying early odor processing. The high-dimensionality of odor space strictly limits the utility of topographical representations, forcing similarity-dependent computations such as decorrelation to employ unusual neural algorithms. The distinct architectures and properties of the two prominent computational layers in the olfactory bulb suggest that the bulb is directly comparable not only to the retina but also to primary visual cortex., (Copyright 2009 Elsevier Ltd. All rights reserved.)

Microcircuits in the olfactory bulb have long received particular attention from both experimentalists and theoreticians, due in part to an abundance of dendrodendritic interactions and other specialized modifications to the canonical cortical circuit architecture. Recent experimental and theoretical results have elucidated the mechanisms and function of these circuits and their presumed contributions to olfactory stimulus processing and odor perception. We here review the architecture and functionality of a prominent olfactory bulb microcircuit: the glomerular network.

Mitral cells, the principal output neurons of the olfactory bulb, receive direct synaptic activation from primary sensory neurons. Shunting inhibitory inputs delivered by granule cell interneurons onto mitral cell lateral dendrites, while poorly positioned to prevent spike initiation, are believed to influence spike timing and underlie coordinated field potential oscillations. We investigated this phenomenon in a reduced compartmental mitral cell model suitable for incorporation into network simulations. Lateral dendritic shunt conductances delayed spiking to a degree dependent on both their electrotonic distance and phase of onset. Moreover, when the afferent activation of mitral cells was loosely coordinated in time, recurrent inhibition significantly narrowed the distribution of mitral cell spike times, illustrating a tendency towards coordinated synchronous activity. However, if mitral cell activity was initially disorganized, recurrent inhibition actually increased the variance in spike timing. This result suggests an essential role for early mechanisms of temporal coordination in olfaction, such as sniffing and the initial synchronization of mitral cell intrinsic oscillations by periglomerular cell-mediated inhibition.

The perceptual quality of odors usually is robust to variability in concentration. However, maps of neural activation across the olfactory bulb glomerular layer are not stable in this respect; rather, glomerular odor representations both broaden and intensify as odorant concentrations are increased. The relative levels of activation among glomeruli, in contrast, remain relatively stable across concentrations, suggesting that the representation of odor quality may rely on these relational activity patterns. However, the neural normalization mechanisms enabling extraction of such relational representations are unclear. Using glomerular imaging activity profiles from the rat olfactory bulb together with computational modeling, we here show that (i) global normalization preserves concentration-independent odor-quality information; (ii) perceptual similarities, as assessed behaviorally, are better predicted by normalized than by raw bulbar activity profiles; and (iii) a recurrent excitatory circuit recently described in the olfactory bulb is capable of performing such normalization. We show that global feed-forward normalization in a sensory system is behaviorally relevant, and that a center-surround neural architecture does not necessarily imply center-surround function.

Cholinergic neuromodulation in the olfactory bulb has been hypothesized to regulate mitral cell molecular receptive ranges and the behavioral discrimination of similar odorants. We tested the effects of cholinergic modulation in the olfactory bulb of cannulated rats by bilaterally infusing cholinergic agents into the olfactory bulbs and measuring the rats' performances on separate spontaneous and motivated odor-discrimination tasks. Specifically, 6 microL/bulb infusions of vehicle (0.9% saline), the muscarinic antagonist scopolamine (7.6 mM and 38 mM), the nicotinic antagonist mecamylamine hydrochloride (3.8 mM and 19 mM), a combination of both antagonists, or the acetylcholinesterase inhibitor neostigmine (8.7 mM) were made 20 min prior to testing on an olfactory cross-habituation task or a rewarded, forced-choice odor-discrimination task. Spontaneous discrimination between chemically related odorants was abolished when nicotinic receptors were blocked in the olfactory bulb, and enhanced when the efficacy of cholinergic inputs was increased with neostigmine. Blocking muscarinic receptors reduced but did not abolish odor discrimination. Interestingly, no behavioral effects of modulating either nicotinic or muscarinic receptors were observed when rats were trained on a reward-motivated odor-discrimination task. Computational modeling of glomerular circuitry demonstrates that known nicotinic cholinergic effects on bulbar neurons suffice to explain these results.

In the olfactory system, the contribution of dynamical properties such as neuronal oscillations and spike synchronization to the representation of odor stimuli is a matter of substantial debate. While relatively simple computational models have sufficed to guide current research in large-scale network dynamics, less attention has been paid to modeling the membrane dynamics in bulbar neurons that may be equally essential to sensory processing. We here present a reduced, conductance-based compartmental model of olfactory bulb mitral cells that exhibits the complex dynamical properties observed in these neurons. Specifically, model neurons exhibit intrinsic subthreshold oscillations with voltage-dependent frequencies that shape the timing of stimulus-evoked action potentials. These oscillations rely on a persistent sodium conductance, an inactivating potassium conductance, and a calcium-dependent potassium conductance and are reset via inhibitory input such as that delivered by periglomerular cell shunt inhibition. Mitral cells fire bursts, or clusters, of spikes when continuously stimulated. Burst properties depend critically on multiple currents, but a progressive deinactivation of I(A) over the course of a burst is an important regulator of burst termination. Each of these complex properties exhibits appropriate dynamics and pharmacology as determined by electrophysiological studies. Additionally, we propose that a second, inconsistently observed form of infrathreshold bistability in mitral cells may derive from the activation of ATP-activated potassium currents responding to hypoxic conditions. We discuss the integration of these cellular properties in the larger context of olfactory bulb network operations.

Behavior genetics studies in mice demand efficient training protocols for rapid phenotypic screening. However, the capacity of neonatal mice to form and retain associative memories has been difficult to study due to their limited sensorimotor capacities. The present study describes a method for robust, naturalistic associative learning in neonatal mice as young as 3 days old. After removal of the dam from the home cage for 2 h, preweanling CD-1 mice of ages 3, 5, and 10 days postnatal were conditioned to associate an arbitrary odorant with the suckling and milk delivery that ensued upon her return to the home cage. After a second maternal deprivation, neonates were tested on their acquired preference for that odorant. Neonates exhibited a learned preference for the conditioned odorant over a novel control odorant. No learning was observed without deprivation, that is, when the dam was removed only briefly for scenting. One-trial learning sufficed to show clear preferences for the conditioned odorant, although repeated training (three sessions over 8 days) significantly increased the expression of preference. The development of neonatal associative learning protocols requiring minimal human intervention is important for the behavioral phenotyping of mutant and transgenic strains, particularly those modeling developmental disorders.

Odorant sampling behaviors such as sniffing bring odorant molecules into contact with olfactory receptor neurons (ORNs) to initiate the sensory mechanisms of olfaction. In rodents, inspiratory airflow through the nose is structured and laminar; consequently, the spatial distribution of adsorbed odorant molecules during inspiration is predictable. Physicochemical properties such as water solubility and volatility, collectively called sorptiveness, interact with behaviorally regulable variables such as inspiratory flow rate to determine the pattern of odorant deposition along the inspiratory path. Populations of ORNs expressing the same odorant receptor are distributed in strictly delimited regions along this inspiratory path, enabling different deposition patterns of the same odorant to evoke different patterns of neuronal activation across the olfactory epithelium and in the olfactory bulb. We propose that both odorant sorptive properties and the regulation of sniffing behavior may contribute to rodents' olfactory capacities by this mechanism. In particular, we suggest that the motor regulation of sniffing behavior is substantially utilized for purposes of "zonation" or the direction of odorant molecules to defined intranasal regions and hence toward distinct populations of receptor neurons, pursuant to animals' sensory goals.

Olfactory receptor neurons (ORNs) expressing the same odorant receptor gene share ligand-receptor affinity profiles and converge onto common glomerular targets in the brain. The activation patterns of different ORN populations, evoked by differential binding of odorant molecular moieties, constitute the primary odor representation. However, odorants possess properties other than receptor-binding sites that can contribute to odorant discrimination. Among terrestrial vertebrates, odorant sorptiveness--volatility and water solubility--imposes physicochemical constraints on migration through the nose during inspiration. The non-uniform distributions of ORN populations along the inspiratory axis enable sorptiveness to modify odor representations by affecting the number of molecules reaching different receptors during a sniff. Animals can then modify and analyze odor representation further by the dynamic regulation of sniffing.

Computational models are increasingly essential to systems neuroscience. Models serve as proofs of concept, tests of sufficiency, and as quantitative embodiments of working hypotheses and are important tools for understanding and interpreting complex data sets. In the olfactory system, models have played a particularly prominent role in framing contemporary theories and presenting novel hypotheses, a role that will only grow as the complexity and intricacy of experimental data continue to increase. This review will attempt to provide a comprehensive, functional overview of computational ideas in olfaction and outline a computational framework for olfactory processing based on the insights provided by these diverse models and their supporting data.

Dopaminergic modulation of cortical activity has been implicated in the formation of reward associations. There is abundant evidence for dopaminergic effects on olfactory processing. Using an olfactory discrimination task, the authors show that D1 and D2 dopamine receptors can regulate rats' olfactory discrimination capacities and that the effects of receptor activation functionally oppose one another. Injection of either the D1 agonist SKF 38393 (10 mg/kg) or the D2 antagonist spiperone (0.62 mg/kg) facilitated the discrimination of similar odorants but had no effect on the discrimination of dissimilar odorants, whereas both the D, antagonist SCH 23390 (0.025 mg/kg) and the D2 agonist quinpirole (0.2 mg/kg) significantly impaired rats' ability to discriminate similar and dissimilar odorants.

Acuity is fundamental to sensory systems, establishing the foundation for detectable differences in stimulus quality and consequently shaping animals' sensory capacities. In the olfactory system, which samples intrinsically high-dimensional chemical information, acuity for odor quality is measurable by means of ad hoc dimensions based on behaviorally confirmed sets of sequentially similar odorants. The authors measure olfactory acuity in mice using a rewarded forced-choice odor generalization task and show that mice exhibit greater olfactory acuity in response to higher concentration (1,0 Pa) odorants than to lower concentration (0.01 Pa) odorants. Results suggest that the dynamic modulation of sensory acuity--not necessarily its maximization--is an important component of olfactory processing and reflects the salience of odorant stimuli., ((c) 2003 APA)

The means by which olfactory systems enable the consistent recognition of biologically meaningful odors that may vary in composition over time is a central problem in olfaction. Experiments in honeybees have suggested a solution to one aspect of this problem by demonstrating that the learning of components in an odor mixture suppresses subsequent learning about additional components that are later added to that mixture. We here show, in rats, that intramodal olfactory blocking is also exhibited in vertebrates, and furthermore that the specific characteristics of this blocking are similar to those observed in intermodal blocking studies. Using an olfactory digging task, we submitted two groups of rats to the following olfactory training protocol: one group was first trained (five trials) on an odor (A), followed by five training trials on a binary mixture (A+B), while the second group was similarly trained on a different odor (C) followed by the binary mixture (A+B). After training, both groups' unrewarded responses to the mixture (A+B), odor (B), and an unconditioned control odor (X) were measured. For four out of five odor sets used in this experiment, a significant difference in digging time was observed between the responses of the two groups to odor B (P<.01), but not between their responses to the binary mixture (A+B) or to the control odor (X). These results demonstrate that pretraining rats with an odorant blocks subsequent learning about another odorant when the latter is presented simultaneously with the pretrained odorant, indicating that the components of a mixture are at least partially perceived as independent elements of this mixture.

Spatial patterns of glomerular activity in the vertebrate olfactory bulb and arthropod antennal lobe reflect an important component of first-order olfactory representation and contribute to odorant identification. Higher concentration odor stimuli evoke broader glomerular activation patterns, resulting in greater spatial overlap among different odor representations. However, behavioral studies demonstrate results contrary to what these data might suggest: Honeybees are more, not less, able to discriminate among odorants applied at higher concentrations. Using a computational model of the honeybee antennal lobe, the authors show that changes in synchronization patterns among antennal lobe projection neurons, as observed electrophysiologically, could parsimoniously underlie these observations. The results suggest that stimulus salience, as defined behaviorally, is directly correlated with the degree of synchronization among second-order olfactory neurons.

Carbon chain length in several classes of straight-chain aliphatic odorants has been proposed as a model axis of similarity for olfactory research, on the basis of successes of studies in insect and vertebrate species. To assess the influence of task on measured perceptual similarities among odorants and to demonstrate that the systematic similarities observed within homologous odorant series are not task specific, the authors compare 3 different behavioral paradigms for rats (olfactory habituation, generalization, and discrimination). Although overall patterns of odorant similarity are consistent across all 3 of these paradigms, both quantitative measurements of perceptual similarity and comparability with 2-deoxyglucose imaging data from the olfactory bulb are dependent on the specific behavioral tasks used. Thus, behavioral indices of perceptual similarity are affected by task parameters such as learning and reward associations.

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 odor scene 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. Author summary: We understand most sensory systems by comparing the responses of the system against objective external physical measurements. For example, we know that our ability to distinguish small changes in color is greater for some colors than for others, and that we can distinguish sounds more acutely when they are within the range of pitches used for speech. Similar principles presumably apply to the sense of smell, but odorous chemicals are harder to physically quantify than light or sound because they cannot be organized in terms of a straightforward physical variable like wavelength or frequency. That said, the physical properties of interactions between chemicals and cellular receptors (such as those in the olfactory system) are well understood. What we lack is a systematic framework within which these pharmacological principles can be organized to study odor sampling in the way that we have long studied visual and auditory sampling. We here propose and describe such a framework for odor sampling, and show that it successfully replicates some established but unexplained experimental results. [ABSTRACT FROM AUTHOR]

We have developed a spiking neural network (SNN) algorithm for signal restoration and identification based on principles extracted from the mammalian olfactory system and broadly applicable to input from arbitrary sensor arrays. For interpretability and development purposes, we here examine the properties of its initial feedforward projection. Like the full algorithm, this feedforward component is fully spike timing-based, and utilizes online learning based on local synaptic rules such as spike timing-dependent plasticity (STDP). Using an intermediate metric to assess the properties of this initial projection, the feedforward network exhibits high classification performance after few-shot learning without catastrophic forgetting, and includes a none of the above outcome to reflect classifier confidence. We demonstrate online learning performance using a publicly available machine olfaction dataset with challenges including relatively small training sets, variable stimulus concentrations, and 3 years of sensor drift. [ABSTRACT FROM AUTHOR]

We present a computational model of the mammalian olfactory bulb (OB) designed to investigate how cholinergic inputs modulate olfactory sensory representations. The model integrates experimental data derived from diverse physiological studies of cholinergic modulation of OB circuitry into a simulation of bulbar responses to realistic odorants. Experimentally-observed responses to a homologous series of odorants (unbranched aliphatic aldehydes) were simulated; realistic cholinergic inputs to the OB model served to increase the discriminability of the bulbar responses generated to very similar odorants. This simulation predicted, correctly, that missing cholinergic inputs to the OB would result in greater generalization between similar aliphatic aldehydes. Based on the assumption that the overlap between the neural representations of two sensory stimuli is predictive of their perceptual similarity, we tested this prediction in a behavioral experiments with rats. We show that, indeed, rats with selective lesions of cholinergic neurons that project to the OB and cortex discriminate less well between aliphatic aldehydes with similar carbon chain lengths than do rats that received sham lesions. [Copyright &y& Elsevier]

Habituation is a simple form of memory, yet its neurobiological mechanisms are only beginning to be understood in mammals. In the olfactory system, the neural correlates of habituation at a fast experimental timescale involving very short intertrial intervals (tens of seconds) have been shown to depend on synaptic adaptation in olfactory cortex. In contrast, behavioral habituation to odorants on a longer timescale with intertrial intervals of several minutes depends on processes in the olfactory bulb, as demonstrated by pharmacological studies. We here show that behavioral habituation to odorants on this longer timescale has a neuronal activity correlate in the olfactory bulb. Spiking responses of mitral cells in the rat olfactory bulb adapt to, and recover from, repeated odorant stimulation with 5-rain intertrial intervals with a time course similar to that of behavioral habituation. Moreover, both the behavioral and neuronal effects of odor habituation require functioning N-methyl-D-aspartic acid receptors in the olfactory bulb. [ABSTRACT FROM AUTHOR]