Strong single-fiber sensory inputs to olfactory cortex: implications for olfactory coding

Olfactory information is first encoded in a combinatorial fashion by olfactory bulb glomeruli, which individually represent distinct chemical features of odors. This information is then transmitted to piriform (olfactory) cortex, via axons of olfactory bulb mitral and tufted (M/T) cells, where it is presumed to form the odor percept. However, mechanisms governing the integration of sensory information in mammalian olfactory cortex are unclear. Here we show that single M/T cells can make powerful connections with cortical pyramidal cells, and coincident input from few M/T cells is sufficient to elicit spike output. These findings suggest that odor coding is broad and distributed in olfactory cortex.     

Sparse Distributed Representation of Odors in a Large-scale Olfactory Bulb Circuit

In the olfactory bulb, lateral inhibition mediated by granule cells has been suggested to modulate the timing of mitral cell firing, thereby shaping the representation of input odorants. Current experimental techniques, however, do not enable a clear study of how the mitral-granule cell network sculpts odor inputs to represent odor information spatially and temporally. To address this critical step in the neural basis of odor recognition, we built a biophysical network model of mitral and granule cells, corresponding to 1/100th of the real system in the rat, and used direct experimental imaging data of glomeruli activated by various odors. The model allows the systematic investigation and generation of testable hypotheses of the functional mechanisms underlying odor representation in the olfactory bulb circuit. Specifically, we demonstrate that lateral inhibition emerges within the olfactory bulb network through recurrent dendrodendritic synapses when constrained by a range of balanced excitatory and inhibitory conductances. We find that the spatio-temporal dynamics of lateral inhibition plays a critical role in building the glomerular-related cell clusters observed in experiments, through the modulation of synaptic weights during odor training. Lateral inhibition also mediates the development of sparse and synchronized spiking patterns of mitral cells related to odor inputs within the network, with the frequency of these synchronized spiking patterns also modulated by the sniff cycle.     

Parallel odor processing by two anatomically distinct olfactory bulb target structures

The olfactory cortex encompasses several anatomically distinct regions each hypothesized to provide differential representation and processing of specific odors. Studies exploring whether or not the diversity of olfactory bulb input to olfactory cortices has functional meaning, however, are lacking. Here we tested whether two anatomically major olfactory cortical structures, the olfactory tubercle (OT) and piriform cortex (PCX), differ in their neural representation and processing dynamics of a small set of diverse odors by performing in vivo extracellular recordings from the OT and PCX of anesthetized mice. We found a wealth of similarities between structures, including odor-evoked response magnitudes, breadth of odor tuning, and odor-evoked firing latencies. In contrast, only few differences between structures were found, including spontaneous activity rates and odor signal-to-noise ratios. These results suggest that despite major anatomical differences in innervation by olfactory bulb mitral/tufted cells, the basic features of odor representation and processing, at least within this limited odor set, are similar within the OT and PCX. We predict that the olfactory code follows a distributed processing stream in transmitting behaviorally and perceptually-relevant information from low-level stations.     

An olfactory recognition model based on spatio-temporal encoding of odor quality in the olfactory bulb

In order to study the problem how the olfactory neural system processes the odorant molecular information for constructing the olfactory image of each object, we present a dynamic model of the olfactory bulb constructed on the basis of well-established experimental and theoretical results. The information relevant to a single odor, i.e. its constituent odorant molecules and their mixing ratios, are encoded into a spatio-temporal pattern of neural activity in the olfactory bulb, where the activity pattern corresponds to a limit cycle attractor in the mitral cell network. The spatio-temporal pattern consists of a temporal sequence of spatial firing patterns: each constituent molecule is encoded into a single spatial pattern, and the order of magnitude of the mixing ratio is encoded into the temporal sequence. The formation of a limit cycle attractor under the application of a novel odor is carried out based on the intensity-to-time-delay encoding scheme. The dynamic state of the olfactory bulb, which has learned many odors, becomes a randomly itinerant state in which the current firing state of the bulb itinerates randomly among limit cycle attractors corresponding to the learned odors. The recognition of an odor is generated by the dynamic transition in the network from the randomly itinerant state to a limit cycle attractor state relevant to the odor, where the transition is induced by the short-term synaptic changes made according to the Hebbian rule under the application of the odor stimulus. Received: 28 July 1997 / Accepted in revised form: 6 May 1998     

A neural mechanism of hierarchical discrimination of odors in the olfactory cortex based on spatiotemporal encoding of odor information

We propose a neural mechanism for discrimination of different complex odors in the olfactory cortex based on the dynamical encoding scheme. Both constituent molecules of the odor and their mixing ratios are encoded simultaneously into a spatiotemporal activity pattern (limit cycle attractor) in the olfactory bulb [Hoshino O, Kashimori Y, Kambara T (1998) Biol Cybern 79:109–120]. We present a functional model of the olfactory cortex consisting of some dynamical mapping modules. Each dynamical map is represented by itinerancy among the limit cycle attractors. When a temporal sequence of spatial activity patterns corresponding to a complex odor is injected from the bulb to the network of the olfactory cortex, the neural activity state of each mapping module is fixed to a relevant spatial pattern injected. Recognition of an odor is accomplished by a combination of firing patterns fixed in all the mapping modules. The stronger the response strength of the component, the earlier the component is recognized. The hierarchical discrimination of an odor is made by recognizing the components in order of decreasing response strengths. Received: 28 November 1998 / Accepted in revised form: 17 December 1999     

Maintaining accuracy at the expense of speed: stimulus similarity defines odor discrimination time in mice

Odor discrimination times and their dependence on stimulus similarity were evaluated to test temporal and spatial models of odor representation in mice. In a go/no-go operant conditioning paradigm, discrimination accuracy and time were determined for simple monomolecular odors and binary mixtures of odors. Mice discriminated simple odors with an accuracy exceeding 95%. Binary mixtures evoking highly overlapping spatiotemporal patterns of activity in the olfactory bulb were discriminated equally well. However, while discriminating simple odors in less than 200 ms, mice required 70-100 ms more time to discriminate highly similar binary mixtures. We conclude that odor discrimination in mice is fast and stimulus dependent. Thus, the underlying neuronal mechanisms act on a fast timescale, requiring only a brief epoch of odor-specific spatiotemporal representations to achieve rapid discrimination of dissimilar odors. The fine discrimination of highly similar stimuli, however, requires temporal integration of activity, suggesting a tradeoff between accuracy and speed.     

A model of olfactory adaptation and sensitivity enhancement in the olfactory bulb

It has been suggested that the olfactory bulb, the first processing center after the sensory cells in the olfactory pathway, plays a role in olfactory adaptation, odor sensitivity enhancement by motivation and other olfactory psychophysical phenomena. In a mathematical model based on the bulbar anatomy and physiology, the inputs from the higher olfactory centers to the inhibitory cells in the bulb are shown to be able to modulate the response, and thus the sensitivity of the bulb to specific odor inputs. It follows that the bulb can decrease its sensitivity to a pre-existing and detected odor (adaptation) while remaining sensitive to new odors, or increase its sensitivity to interested searching odors. Other olfactory psychophysical phenomena such as cross-adaptation etc. are discussed as well.     

Associative cortex features in the first olfactory brain relay station

Synchronized firing of mitral cells (MCs) in the olfactory bulb (OB) has been hypothesized to help bind information together in olfactory cortex (OC). In this survey of synchronized firing by suspected MCs in awake, behaving vertebrates, we find the surprising result that synchronized firing conveys information on odor value ("Is it rewarded?") rather than odor identity ("What is the odor?"). We observed that as?mice learned to discriminate between odors, synchronous firing responses to the rewarded and unrewarded odors became divergent. Furthermore, adrenergic blockage decreases the magnitude of odor divergence of synchronous trains, suggesting that MCs contribute to decision-making through adrenergic-modulated synchronized firing. Thus, in the olfactory system information on stimulus reward is found in MCs one synapse away from the sensory neuron.     

Profound context-dependent plasticity of mitral cell responses in olfactory bulb

On the basis of its primary circuit it has been postulated that the olfactory bulb (OB) is analogous to the retina in mammals. In retina, repeated exposure to the same visual stimulus results in a neural representation that remains relatively stable over time, even as the meaning of that stimulus to the animal changes. Stability of stimulus representation at early stages of processing allows for unbiased interpretation of incoming stimuli by higher order cortical centers. The alternative is that early stimulus representation is shaped by previously derived meaning, which could allow more efficient sampling of odor space providing a simplified yet biased interpretation of incoming stimuli. This study helps place the olfactory system on this continuum of subjective versus objective early sensory representation. Here we show that odor responses of the output cells of the OB, mitral cells, change transiently during a go–no-go odor discrimination task. The response changes occur in a manner that increases the ability of the circuit to convey information necessary to discriminate among closely related odors. Remarkably, a switch between which of the two odors is rewarded causes mitral cells to switch the polarity of their divergent responses. Taken together these results redefine the function of the OB as a transiently modifiable (active) filter, shaping early odor representations in behaviorally meaningful ways.     

Modeling the olfactory bulb and its neural oscillatory processings

The olfactory bulb of mammals aids in the discrimination of odors. A mathematical model based on the bulbar anatomy and electrophysiology is described. Simulations of the highly non-linear model produce a 35–60 Hz modulated activity which is coherent across the bulb. The decision states (for the odor information) in this system can be thought of as stable cycles, rather than point stable states typical of simpler neuro-computing models. Analysis shows that a group of coupled non-linear oscillators are responsible for the oscillatory activities. The output oscillation pattern of the bulb is determined by the odor input. The model provides a framework in which to understand the transform between odor input and the bulbar output to olfactory cortex. There is significant correspondence between the model behavior and observed electrophysiology.     

Appetitive odor learning does not change olfactory coding in a subpopulation of honeybee antennal lobe neurons

Odors elicit spatio-temporal patterns of activity in the olfactory bulb of vertebrates and the antennal lobe of insects. There have been several reports of changes in these patterns following olfactory learning. These studies pose a conundrum: how can an animal learn to efficiently respond to a particular odor with an adequate response, if its primary representation already changes during this process? In this study, we offer a possible solution for this problem. We measured odor-evoked calcium responses in a subpopulation of uniglomerular AL output neurons in honeybees. We show that their responses to odors are remarkably resistant to plasticity following a variety of appetitive olfactory learning paradigms. There was no significant difference in the changes of odor-evoked activity between single and multiple trial forward or backward conditioning, differential conditioning, or unrewarded successive odor stimulation. In a behavioral learning experiment we show that these neurons are necessary for conditioned odor responses. We conclude that these uniglomerular projection neurons are necessary for reliable odor coding and are not modified by learning in this paradigm. The role that other projection neurons play in olfactory learning remains to be investigated.     

Associative Memory and Segmentation in an Oscillatory Neural Model of the Olfactory Bulb

We discuss the first few stages of olfactory processing in the framework of a layered neural network. Its central component is an oscillatory associative memory, describing the external plexiform layer, that consists of inhibitory and excitatory neurons with dendrodendritic interactions. We explore the computational properties of this neural network and point out its possible functional role in the olfactory bulb. When receiving a complex input that is composed of several odors, the network segments it into its components. This is done in two stages. First, multiple odor input is preprocessed in the glomerular layer via a decorrelation mechanism that relies on temporal independence of odor sources. Second, as the recall process of a pattern consists of associative convergence to an oscillatory attractor, multiple inputs are identified by alternate dominance of memory patterns during different sniff cycles. This could explain how quick analysis of mixed odors is subserved by the rapid sniffing behavior of highly olfactory animals. When one of the odors is much stronger than the rest, the network converges onto it, thus displaying odor masking.     

Friends and foes from an ant brain's point of view--neuronal correlates of colony odors in a social insect

Background

Successful cooperation depends on reliable identification of friends and foes. Social insects discriminate colony members (nestmates/friends) from foreign workers (non-nestmates/foes) by colony-specific, multi-component colony odors. Traditionally, complex processing in the brain has been regarded as crucial for colony recognition. Odor information is represented as spatial patterns of activity and processed in the primary olfactory neuropile, the antennal lobe (AL) of insects, which is analogous to the vertebrate olfactory bulb. Correlative evidence indicates that the spatial activity patterns reflect odor-quality, i.e., how an odor is perceived. For colony odors, alternatively, a sensory filter in the peripheral nervous system was suggested, causing specific anosmia to nestmate colony odors. Here, we investigate neuronal correlates of colony odors in the brain of a social insect to directly test whether they are anosmic to nestmate colony odors and whether spatial activity patterns in the AL can predict how odor qualities like “friend” and “foe” are attributed to colony odors.

Methodology/Principal Findings

Using ant dummies that mimic natural conditions, we presented colony odors and investigated their neuronal representation in the ant Camponotus floridanus. Nestmate and non-nestmate colony odors elicited neuronal activity: In the periphery, we recorded sensory responses of olfactory receptor neurons (electroantennography), and in the brain, we measured colony odor specific spatial activity patterns in the AL (calcium imaging). Surprisingly, upon repeated stimulation with the same colony odor, spatial activity patterns were variable, and as variable as activity patterns elicited by different colony odors.

Conclusions

Ants are not anosmic to nestmate colony odors. However, spatial activity patterns in the AL alone do not provide sufficient information for colony odor discrimination and this finding challenges the current notion of how odor quality is coded. Our result illustrates the enormous challenge for the nervous system to classify multi-component odors and indicates that other neuronal parameters, e.g., precise timing of neuronal activity, are likely necessary for attribution of odor quality to multi-component odors.     

Odor similarity does not influence the time needed for odor processing

The brain's link between perception and action involves several steps, which include stimulus transduction, neuronal coding of the stimulus, comparison to a memory template and choice of an appropriate behavioral response. All of these need time, and many studies report that the time needed to compare two stimuli correlates inversely with the perceived distance between them. We developed a behavioral assay in which we tested the time that a honeybee needs to discriminate between odors consisting of mixtures of two components, and included both very similar and very different stimuli spanning four log-concentration ranges. Bees learned to discriminate all odors, including very similar odors and the same odor at different concentrations. Even though discriminating two very similar odors appears to be a more difficult task than discriminating two very distinct substances, we found that the time needed to make a choice for or against an odor was independent of odor similarity. Our data suggest that, irrespective of the nature of the olfactory code, the bee olfactory system evaluates odor quality after a constant interval. This may ensure that odors are only assessed after the olfactory network has optimized its representation.     

Maturation of odor representation in the honeybee antennal lobe

The antennal lobe (AL) is the first center for processing odors in the insect brain, as is the olfactory bulb (OB) in vertebrates. Both the AL and the OB have a characteristic glomerular structure; odors sensed by olfactory receptor neurons are represented by patterns of glomerular activity. Little is known about when and how an odor begins to be perceived in a developing brain. We address this question by using calcium imaging to monitor odor-evoked neural activity in the ALs of bees of different ages. We find that odor-evoked neural activity already occurs in the ALs of bees as young as 1 or 2 days. In young bees, the responses to odors are relatively weak and restricted to a small number of glomeruli. However, different odors already evoke responses in different combinations of glomeruli. In mature bees, the responses are stronger and are evident in more glomeruli, but continue to have distinct odor-dependent signatures. Our findings indicate that the specific glomerular patterns for odors are conserved during the development, and that odor representations are fully developed in the AL during the first 2 weeks following emergence.     

Altered odor-induced expression of c-fos and arg 3.1 immediate early genes in the olfactory system after familiarization with an odor

In adult rats, repeated exposure to an odorant, in absence of any experimentally delivered reinforcement, leads to a drastic decrease in mitral/tufted (M/T) cell responsiveness, not only for the familiar odor but also for other novel odors. In the present study, using two different and complementary in situ hybridization methods, we analyzed the effect of familiarization with an odorant on c-fos and arg 3.1 mRNA expression levels, and we examined the odor specificity of this effect. Odor exposure induces a specific increase in c-fos and arg 3.1 expression in some particular olfactory bulb quadrants. Previous familiarization with the test odor results in a decreased expression of both IEGs in these quadrants, leading to the alteration of the odor-specific pattern of c-fos and arg 3.1 expression. In contrast, this odor-specific pattern is not affected when different odors are used for familiarization and test. Similarly, an odor-specific familiarization effect leading to a reduced c-fos and arg 3.1 expression was also detected in the cingulate cortex and in the anterior piriform cortex. These results support our hypothesis that the decrease in M/T cell responsiveness following a preceding familiarization with an odorant may be related to a particular form of synaptic plasticity involving changes at the genomic level, and reveals further insight in olfactory information processing and the cellular mechanisms underlying familiarization in the olfactory system.     

Olfactory perceptual decision-making is biased by motivational state

Growing evidence suggests that internal factors influence how we perceive the world. However, it remains unclear whether and how motivational states, such as hunger and satiety, regulate perceptual decision-making in the olfactory domain. Here, we developed a novel behavioral task involving mixtures of food and nonfood odors (i.e., cinnamon bun and cedar; pizza and pine) to assess olfactory perceptual decision-making in humans. Participants completed the task before and after eating a meal that matched one of the food odors, allowing us to compare perception of meal-matched and non-matched odors across fasted and sated states. We found that participants were less likely to perceive meal-matched, but not non-matched, odors as food dominant in the sated state. Moreover, functional magnetic resonance imaging (fMRI) data revealed neural changes that paralleled these behavioral effects. Namely, odor-evoked fMRI responses in olfactory/limbic brain regions were altered after the meal, such that neural patterns for meal-matched odor pairs were less discriminable and less food-like than their non-matched counterparts. Our findings demonstrate that olfactory perceptual decision-making is biased by motivational state in an odor-specific manner and highlight a potential brain mechanism underlying this adaptive behavior.

Growing evidence suggests that internal factors influence how we perceive the world; this study shows that food intake influences how humans perceive food odors, such as the scent of cinnamon buns. This effect is specific to meal-matched odors, and is paralleled by changes in odor-evoked brain activity.     

Perceptual blending in odor mixtures depends on the nature of odorants and human olfactory expertise

Our olfactory system is confronted with complex mixtures of odorants, often recognized as single entities due to odor blending (e.g., coffee). In contrast, we are also able to discriminate odors from complex mixtures (e.g., off-odors). Therefore, the olfactory system is able to engage either configural or elemental processes when confronted with mixtures. However, the rules that govern the involvement of these processes during odor perception remain poorly understood. In our first experiment, we examined whether simple odorant mixtures (binary/ternary) could elicit configural perception. Twenty untrained subjects were asked to evaluate the odor typicality of mixtures and their constituents. The results revealed a significant increase in odor typicality in some but not all mixtures as compared with the single components, which suggest that perceptual odor blending can occur only in specific mixtures (configural processing). In our second experiment, we tested the hypothesis that general olfactory expertise can improve elemental perception of mixtures. Thirty-two trained subjects evaluated the odor typicality of the stimuli presented during the first experiment, and their responses were compared with those obtained from the untrained panelists. The results support the idea that general training with odors increases the elemental perception of binary and ternary blending mixtures.     

Cortical feedback and gating in odor discrimination and generalization

A central question in neuroscience is how context changes perception. In the olfactory system, for example, experiments show that task demands can drive divergence and convergence of cortical odor responses, likely underpinning olfactory discrimination and generalization. Here, we propose a simple statistical mechanism for this effect based on unstructured feedback from the central brain to the olfactory bulb, which represents the context associated with an odor, and sufficiently selective cortical gating of sensory inputs. Strikingly, the model predicts that both convergence and divergence of cortical odor patterns should increase when odors are initially more similar, an effect reported in recent experiments. The theory in turn predicts reversals of these trends following experimental manipulations and in neurological conditions that increase cortical excitability.     

Rat olfactory bulb mitral cells receive sparse glomerular inputs

Center-surround receptive fields are a fundamental unit of brain organization. It has been proposed that olfactory bulb mitral cells exhibit this functional circuitry, with excitation from one glomerulus and inhibition from a broad field of glomeruli within reach of the lateral dendrites. We investigated this hypothesis using a combination of in vivo intrinsic imaging, single-unit recording, and a large panel of odors. Assuming a broad inhibitory field, a mitral cell would be influenced by >100 contiguous glomeruli and should respond to many odors. Instead, the observed response rate was an order of magnitude lower. A quantitative model indicates that mitral cell responses can be explained by just a handful of glomeruli. These glomeruli are spatially dispersed on the bulb and represent a broad range of odor sensitivities. We conclude that mitral cells do not have center-surround receptive fields. Instead, each mitral cell performs a specific computation combining a small and diverse set of glomerular inputs.