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

A Selective PMCA Inhibitor Does Not Prolong the Electroolfactogram in Mouse

Within the cilia of vertebrate olfactory receptor neurons, Ca(2+) accumulates during odor transduction. Termination of the odor response requires removal of this Ca(2+), and prior evidence suggests that both Na(+)/Ca(2+) exchange and plasma membrane Ca(2+)-ATPase (PMCA) contribute to this removal.In intact mouse olfactory epithelium, we measured the time course of termination of the odor-induced field potential. Replacement of mucosal Na(+) with Li(+), which reduces the ability of Na(+)/Ca(2+) exchange to expel Ca(2+), prolonged the termination as expected. However, treating the epithelium with the specific PMCA inhibitor caloxin 1b1 caused no significant increase in the time course of response termination.Under these experimental conditions, PMCA does not contribute detectably to the termination of the odor response

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

Spatial Distribution of Calcium-Gated Chloride Channels in Olfactory Cilia

Background: In vertebrate olfactory receptor neurons, sensory cilia transduce odor stimuli into changes in neuronal membrane potential. The voltage changes are primarily caused by the sequential openings of two types of channel: a cyclic-nucleotide-gated (CNG) cationic channel and a calcium-gated chloride channel. In frog, the cilia are 25 to 200 mm in length, so the spatial distributions of the channels may be an important determinant of odor sensitivity. Principal Findings: To determine the spatial distribution of the chloride channels, we recorded from single cilia as calcium was allowed to diffuse down the length of the cilium and activate the channels. A computational model of this experiment allowed an estimate of the spatial distribution of the chloride channels. On average, the channels were concentrated in a narrow band centered at a distance of 29 % of the ciliary length, measured from the base of the cilium. This matches the location of the CNG channels determined previously. This non-uniform distribution of transduction proteins is consistent with similar findings in other cilia. Conclusions: On average, the two types of olfactory transduction channel are concentrated in the same region of the cilium

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

Search for the Higgs boson in events with missing transverse energy and b quark jets produced in proton-antiproton collisions at s**(1/2)=1.96 TeV

We search for the standard model Higgs boson produced in association with an electroweak vector boson in events with no identified charged leptons, large imbalance in transverse momentum, and two jets where at least one contains a secondary vertex consistent with the decay of b hadrons. We use ~1 fb-1 integrated luminosity of proton-antiproton collisions at s**(1/2)=1.96 TeV recorded by the CDF II experiment at the Tevatron. We find 268 (16) single (double) b-tagged candidate events, where 248 +/- 43 (14.4 +/- 2.7) are expected from standard model background processes. We place 95% confidence level upper limits on the Higgs boson production cross section for several Higgs boson masses ranging from 110 GeV/c2 to 140 GeV/c2. For a mass of 115 GeV/c2 the observed (expected) limit is 20.4 (14.2) times the standard model prediction.Comment: 8 pages, 2 figures, submitted to Phys. Rev. Let