Dynamics of odor sampling strategies in mice

Mammalian olfactory receptor neurons in the nasal cavity are stimulated by odorants carried by the inhaled air and their activation is therefore tied to and driven by the breathing or sniffing frequency. Sniffing frequency can be deliberately modulated to alter how odorants stimulate olfactory receptor neurons, giving the animal control over the frequency of odorant exposure to potentially aid odorant detection and discrimination. We monitored sniffing behaviors and odorant discrimination ability of freely-moving mice while they sampled either decreasing concentrations of target odorants or sampled a fixed target odorant concentration in the presence of a background of increasing odorant concentrations, using a Go-NoGo behavioral paradigm. This allowed us to ask how mice alter their odorant sampling duration and sampling (sniffing) frequency depending on the demands of the task and its difficulty. Mice showed an anticipatory increase in sniffing rate prior to odorant exposure and chose to sample for longer durations when exposed to odorants as compared to the solvent control odorant. Similarly, mice also took more odorant sampling sniffs when exposed to target odorants compared to the solvent control odorant. In general, odorant sampling strategies became more similar the more difficult the task was, e.g. the lower the target odorant concentration or the lower the target odorant contrast relative to the background odorant, suggesting that sniffing patterns are not preset, but are dynamically modulated by the particular task and its difficulty

Odor sampling strategies in mice with genetically altered olfactory responses

Peripheral sensory cells and the central neuronal circuits that monitor environmental changes to drive behaviors should be adapted to match the behaviorally relevant kinetics of incoming stimuli, be it the detection of sound frequencies, the speed of moving objects or local temperature changes. Detection of odorants begins with the activation of olfactory receptor neurons in the nasal cavity following inhalation of air and airborne odorants carried therein. Thus, olfactory receptor neurons are stimulated in a rhythmic and repeated fashion that is determined by the breathing or sniffing frequency that can be controlled and altered by the animal. This raises the question of how the response kinetics of olfactory receptor neurons are matched to the imposed stimulation frequency and if, vice versa, the kinetics of olfactory receptor neuron responses determine the sniffing frequency. We addressed this question by using a mouse model that lacks the K+-dependent Na+/Ca2+ exchanger 4 (NCKX4), which results in markedly slowed response termination of olfactory receptor neuron responses and hence changes the temporal response kinetics of these neurons. We monitored sniffing behaviors of freely moving wildtype and NCKX4 knockout mice while they performed olfactory Go/NoGo discrimination tasks. Knockout mice performed with similar or, surprisingly, better accuracy compared to wildtype mice, but chose, depending on the task, different odorant sampling durations depending on the behavioral demands of the odorant identification task. Similarly, depending on the demands of the behavioral task, knockout mice displayed a lower basal breathing frequency prior to odorant sampling, a possible mechanism to increase the dynamic range for changes in sniffing frequency during odorant sampling. Overall, changes in sniffing behavior between wildtype and NCKX4 knockout mice were subtle, suggesting that, at least for the particular odorant-driven task we used, slowed response termination of the odorant-induced receptor neuron response either has a limited detrimental effect on odorant-driven behavior or mice are able to compensate via an as yet unknown mechanism

The functional relevance of olfactory marker protein in the vertebrate olfactory system: a never-ending story

Olfactory marker protein (OMP) was first described as a protein expressed in olfactory receptor neurons (ORNs) in the nasal cavity. In particular, OMP, a small cytoplasmic protein, marks mature ORNs and is also expressed in the neurons of other nasal chemosensory systems: the vomeronasal organ, the septal organ of Masera, and the Grueneberg ganglion. While its expression pattern was more easily established, OMP’s function remained relatively vague. To date, most of the work to understand OMP’s role has been done using mice lacking OMP. This mostly phenomenological work has shown that OMP is involved in sharpening the odorant response profile and in quickening odorant response kinetics of ORNs and that it contributes to targeting of ORN axons to the olfactory bulb to refine the glomerular response map. Increasing evidence shows that OMP acts at the early stages of olfactory transduction by modulating the kinetics of cAMP, the second messenger of olfactory transduction. However, how this occurs at a mechanistic level is not understood, and it might also not be the only mechanism underlying all the changes observed in mice lacking OMP. Recently, OMP has been detected outside the nose, including the brain and other organs. Although no obvious logic has become apparent regarding the underlying commonality between nasal and extranasal expression of OMP, a broader approach to diverse cellular systems might help unravel OMP’s functions and mechanisms of action inside and outside the nose

Ontogeny of synaptophysin and synaptoporin in the central nervous system

The expression of the synaptic vesicle antigens synaptophysin (SY) and synaptoporin (SO) was studied in the rat striatum, which contains a nearly homogeneous population of GABAergic neurons. In situ hybridization revealed high levels of SY transcripts in the striatal anlage from embryonic day (E) 14 until birth. In contrast. SO hybridization signals were low, and no immunoreactive cell bodies were detected at these stages of development. At E 14, SY-immunoreactivity was restricted to perikarya. In later prenatal stages of development SY-immunoreactivity appeared in puncta (identified as terminals containing immunostained synaptic vesicles), fibers, thick fiber bundles and ‘patches’. In postnatal and adult animals, perikarya of striatal neurons exhibited immunoreaction for SO; ultrastructurally SO antigen was found in the Golgi apparatus and in multivesicular bodies. SO-positive boutons were rare in the striatum. In the neuropil, numerous presynaptic terminals positive for SY were observed. Our data indicate that the expression of synaptic vesicle proteins in GABAergic neurons of the striatum is developmentally regulated. Whereas SY is prevalent during embryonic development, SO is the major synaptic vesicle antigen expressed postnatally by striatal neurons which project to the globus pallidus and the substantia nigra. In contrast synapses of striatal afferents (predominantly from cortex, thalamus and substantia nigra) contain SY

Machine learning for automatic prediction of the quality of electrophysiological recordings

The quality of electrophysiological recordings varies a lot due to technical and biological variability and neuroscientists inevitably have to select “good” recordings for further analyses. This procedure is time-consuming and prone to selection biases. Here, we investigate replacing human decisions by a machine learning approach. We define 16 features, such as spike height and width, select the most informative ones using a wrapper method and train a classifier to reproduce the judgement of one of our expert electrophysiologists. Generalisation performance is then assessed on unseen data, classified by the same or by another expert. We observe that the learning machine can be equally, if not more, consistent in its judgements as individual experts amongst each other. Best performance is achieved for a limited number of informative features; the optimal feature set being different from one data set to another. With 80–90% of correct judgements, the performance of the system is very promising within the data sets of each expert but judgments are less reliable when it is used across sets of recordings from different experts. We conclude that the proposed approach is relevant to the selection of electrophysiological recordings, provided parameters are adjusted to different types of experiments and to individual experimenters

The Na(+)/Ca(2+) exchanger NCKX4 governs termination and adaptation of the mammalian olfactory response

Sensory perception requires accurate encoding of stimulus information by sensory receptor cells. We identified NCKX4, a potassium-dependent Na(+)/Ca(2+) exchanger, as being necessary for rapid response termination and proper adaptation of vertebrate olfactory sensory neurons (OSNs). Nckx4(-/-) (also known as Slc24a4) mouse OSNs displayed substantially prolonged responses and stronger adaptation. Single-cell electrophysiological analyses revealed that the majority of Na(+)-dependent Ca(2+) exchange in OSNs relevant to sensory transduction is a result of NCKX4 and that Nckx4(-/-) mouse OSNs are deficient in encoding action potentials on repeated stimulation. Olfactory-specific Nckx4(-/-) mice had lower body weights and a reduced ability to locate an odorous source. These results establish the role of NCKX4 in shaping olfactory responses and suggest that rapid response termination and proper adaptation of peripheral sensory receptor cells tune the sensory system for optimal perception

Optimal Experimental Design for Biophysical Modelling in Multidimensional Diffusion MRI

Computational models of biophysical tissue properties have been widely used in diffusion MRI (dMRI) research to elucidate the link between microstructural properties and MR signal formation. For brain tissue, the research community has developed the so-called Standard Model (SM) that has been widely used. However, in clinically applicable acquisition protocols, the inverse problem that recovers the SM parameters from a set of MR diffusion measurements using pairs of short pulsed field gradients was shown to be ill-posed. Multidimensional dMRI was shown to solve this problem by combining linear and planar tensor encoding data. Given sufficient measurements, multiple choices of b-tensor sets provide enough information to estimate all SM parameters. However, in the presence of noise, some sets will provide better results. In this work, we develop a framework for optimal experimental design of multidimensional dMRI sequences applicable to the SM. This framework is based on maximising the determinant of the Fisher information matrix, which is averaged over the full SM parameter space. This averaging provides a fairly objective information metric tailored for the expected signal but that only depends on the acquisition configuration. The optimisation of this metric can be further restricted to any subclass of desirable design constraints like, for instance, hardware-specific constraints. In this work, we compute the optimal acquisitions over the set of all b-tensors with fixed eigenvectors

Influences of Excluded Volume of Molecules on Signaling Processes on Biomembrane

We investigate the influences of the excluded volume of molecules on biochemical reaction processes on 2-dimensional surfaces using a model of signal transduction processes on biomembranes. We perform simulations of the 2-dimensional cell-based model, which describes the reactions and diffusion of the receptors, signaling proteins, target proteins, and crowders on the cell membrane. The signaling proteins are activated by receptors, and these activated signaling proteins activate target proteins that bind autonomously from the cytoplasm to the membrane, and unbind from the membrane if activated. If the target proteins bind frequently, the volume fraction of molecules on the membrane becomes so large that the excluded volume of the molecules for the reaction and diffusion dynamics cannot be negligible. We find that such excluded volume effects of the molecules induce non-trivial variations of the signal flow, defined as the activation frequency of target proteins, as follows. With an increase in the binding rate of target proteins, the signal flow varies by i) monotonically increasing; ii) increasing then decreasing in a bell-shaped curve; or iii) increasing, decreasing, then increasing in an S-shaped curve. We further demonstrate that the excluded volume of molecules influences the hierarchical molecular distributions throughout the reaction processes. In particular, when the system exhibits a large signal flow, the signaling proteins tend to surround the receptors to form receptor-signaling protein clusters, and the target proteins tend to become distributed around such clusters. To explain these phenomena, we analyze the stochastic model of the local motions of molecules around the receptor.Comment: 31 pages, 10 figure