Faculty Bibliography

Sampling regulates stimulus intensity and temporal dynamics at the sense organ. Despite variations in sampling behavior, animals must make veridical perceptual judgments about external stimuli. In olfaction, odor sampling varies with respiration, which influences neural responses at the olfactory periphery. Nevertheless, rats were able to perform fine odor intensity judgments despite variations in sniff kinetics. To identify the features of neural activity supporting stable intensity perception, in awake mice we measured responses of mitral/tufted (MT) cells to different odors and concentrations across a range of sniff frequencies. Amplitude and latency of the MT cells' responses vary with sniff duration. A fluid dynamics (FD) model based on odor concentration kinetics in the intranasal cavity can account for this variability. Eliminating sniff waveform dependence of MT cell responses using the FD model allows for significantly better decoding of concentration. This suggests potential schemes for sniff waveform invariant odor concentration coding.

Humans can identify visual objects independently of view angle and lighting, words independently of volume and pitch, and smells independently of concentration. The computational principles underlying invariant object recognition remain mostly unknown. Here we propose that, in olfaction, a small and relatively stable set comprised of the earliest activated receptors forms a code for concentration-invariant odor identity. One prediction of this "primacy coding" scheme is that decisions based on odor identity can be made solely using early odor-evoked neural activity. Using an optogenetic masking paradigm, we define the sensory integration time necessary for odor identification and demonstrate that animals can use information occurring <100 ms after inhalation onset to identify odors. Using multi-electrode array recordings of odor responses in the olfactory bulb, we find that concentration-invariant units respond earliest and at latencies that are within this behaviorally-defined time window. We propose a computational model demonstrating how such a code can be read by neural circuits of the olfactory system.

Humans can identify visual objects independently of view angle and lighting, words independently of volume and pitch, and smells independently of concentration. The computational principles underlying invariant object recognition remain mostly unknown. Here we propose that, in olfaction, a small and relatively stable set made of the earliest activated receptors forms a code for concentration invariant odor identity. One prediction of this "primacy coding" scheme is that decisions based on odor identity can be made solely using early odor-evoked neural activity. Using an optogenetic masking paradigm, we define the sensory integration time necessary for odor identification and demonstrate that animals can use information occurring <100 ms after inhalation onset to identify odors. Using multi-electrode array recordings of odor responses in the olfactory bulb, we find that concentration invariant units respond earliest and at latencies that are within this behaviorally-defined time window. We propose a computational model demonstrating how such a code can be read by neural circuits of the olfactory system

A fundamental question in olfaction is how individual olfactory receptors contribute to odor perception. The Trace Amine- Associated Receptors (TAARs) are a small set of evolutionarily conserved main olfactory receptors that respond preferentially to amines and that contribute significantly to amine perception. We are using a combination of gene targeting, electrophysiology, in vivo imaging, and behavior to dissect the contribution of individual TAARs to amine sensitivity. Odorant detection thresholds were measured in mice lacking specific TAAR genes using a go-no go behavioral assay. Genetic deletion of all olfactory TAARs causes a 10-fold decrease in sensitivity to isopentylamine and a 50-fold decrease in sensitivity to phenylethylamine. This indicates that TAARs play a significant role in determining behavioral sensitivity to amines. Our electrophysiological and in vivo imaging experiments indicate that the TAARs are broadly tuned to amines. Phenylethylamine preferentially activates TAAR4, and isopentylamine activates both TAAR4 and TAAR3, with TAAR3 being slightly more sensitive. Genetic deletion of TAAR4 by itself elicits a 10-fold decrease in sensitivity to phenylethylamine, indicating that TAAR4 is the most sensitive receptor for this odorant. Behavioral threshold for isopenylamine is not affected by TAAR4 deletion, indicating that isopentylamine sensitivity may be set by TAAR3, or may be set by either TAAR3 or TAAR4. Our results indicate that single olfactory receptors can contribute significantly to odor detection, and that the TAARs are most likely the most sensitive amine receptors. More generally, our approach allows us to characterize for the first time in mammals how chemical detection at the molecular level relates to olfactory performance at the behavioral level

Temporal limits on perceptual decisions set strict boundaries on the possible underlying neural computations. How odor information is encoded in the olfactory system is still poorly understood. Here, we sought to define the limit on the speed of olfactory processing. To achieve this, we trained mice to discriminate different odor concentrations in a novel behavioral setup with precise odor delivery synchronized to the sniffing cycle. Mice reported their choice by moving a horizontal treadmill with their front limbs. We found that mice reported discriminations of 75% accuracy in 70-90 ms after odor inhalation. For a low concentration and nontrigeminal odorant, this time was 90-140 ms, showing that mice process odor information rapidly even in the absence of trigeminal stimulation. These response times establish, after accounting for odor transduction and motor delays, that olfactory processing can take tens of milliseconds. This study puts a strong limit on the underlying neural computations and suggests that the action potentials forming the neural basis for these decisions are fired in a few tens of milliseconds. SIGNIFICANCE STATEMENT: Understanding how sensory information is processed requires different approaches that span multiple levels of investigation from genes to neurons to behavior. Limits on behavioral performance constrain the possible neural mechanisms responsible for specific computations. Using a novel behavioral paradigm, we established that mice can make decisions about odor intensity surprisingly fast. After accounting for sensory and motor delays, the limit on some olfactory neural computations can be as low as a few tens of milliseconds, which suggests that only the first action potentials across a population of neurons contribute to these computations.

Stimulus intensity is a fundamental perceptual feature in all sensory systems. In olfaction, perceived odor intensity depends on at least two variables: odor concentration; and duration of the odor exposure or adaptation. To examine how neural activity at early stages of the olfactory system represents features relevant to intensity perception, we studied the responses of mitral/tufted cells (MTCs) while manipulating odor concentration and exposure duration. Temporal profiles of MTC responses to odors changed both as a function of concentration and with adaptation. However, despite the complexity of these responses, adaptation and concentration dependencies behaved similarly. These similarities were visualized by principal component analysis of average population responses and were quantified by discriminant analysis in a trial-by-trial manner. The qualitative functional dependencies of neuronal responses paralleled psychophysics results in humans. We suggest that temporal patterns of MTC responses in the olfactory bulb contribute to an internal perceptual variable: odor intensity.

BACKGROUND: Recording of physiological parameters in behaving mice has seen an immense increase over recent years driven by, for example, increased miniaturization of recording devices. One parameter particularly important for odorant-driven behaviors is the breathing frequency, since the latter dictates the rate of odorant delivery to the nasal cavity and the olfactory receptor neurons located therein. NEW METHOD: Typically, breathing patterns are monitored by either measuring the breathing-induced temperature or pressure changes in the nasal cavity. Both require the implantation of a nasal cannula and tethering of the mouse to either a cable or tubing. To avoid these limitations we used an implanted pressure sensor which reads the thoracic pressure and transmits the data telemetrically, thus making it suitable for experiments which require a freely moving animal. RESULTS: Mice performed a Go/NoGo odorant-driven behavioral task with the implanted pressure sensor, which proved to work reliably to allow recording of breathing signals over several weeks from a given animal. COMPARISON TO EXISTING METHOD(S): We simultaneously recorded the thoracic and nasal pressure changes and found that measuring the thoracic pressure change yielded similar results compared to measurements of nasal pressure changes. CONCLUSION: Telemetrically recorded breathing signals are a feasible method to monitor odorant-guided behavioral changes in breathing rates. Its advantages are most significant when recording from a freely moving animal over several weeks. The advantages and disadvantages of different methods to record breathing patterns are discussed.

A classic problem in neuroscience is how temporal sequences (TSs) can be recognized. This problem is exemplified in the olfactory system, where an odor is defined by the TS of olfactory bulb (OB) output that occurs during a sniff. This sequence is discrete because the output is subdivided by gamma frequency oscillations. Here we propose a new class of "brute-force" solutions to recognition of discrete sequences. We demonstrate a network architecture in which there are a small number of modules, each of which provides a persistent snapshot of what occurs in a different gamma cycle. The collection of these snapshots forms a spatial pattern (SP) that can be recognized by standard attractor-based network mechanisms. We will discuss the implications of this strategy for recognizing odor-specific sequences generated by the OB.