Receptive field inference with localized priors

The linear receptive field describes a mapping from sensory stimuli to a one-dimensional variable governing a neuron's spike response. However, traditional receptive field estimators such as the spike-triggered average converge slowly and often require large amounts of data. Bayesian methods seek to overcome this problem by biasing estimates towards solutions that are more likely a priori, typically those with small, smooth, or sparse coefficients. Here we introduce a novel Bayesian receptive field estimator designed to incorporate locality, a powerful form of prior information about receptive field structure. The key to our approach is a hierarchical receptive field model that flexibly adapts to localized structure in both spacetime and spatiotemporal frequency, using an inference method known as empirical Bayes. We refer to our method as automatic locality determination (ALD), and show that it can accurately recover various types of smooth, sparse, and localized receptive fields. We apply ALD to neural data from retinal ganglion cells and V1 simple cells, and find it achieves error rates several times lower than standard estimators. Thus, estimates of comparable accuracy can be achieved with substantially less data. Finally, we introduce a computationally efficient Markov Chain Monte Carlo (MCMC) algorithm for fully Bayesian inference under the ALD prior, yielding accurate Bayesian confidence intervals for small or noisy datasets.     

Modeling the impact of common noise inputs on the network activity of retinal ganglion cells

Synchronized spontaneous firing among retinal ganglion cells (RGCs), on timescales faster than visual responses, has been reported in many studies. Two candidate mechanisms of synchronized firing include direct coupling and shared noisy inputs. In neighboring parasol cells of primate retina, which exhibit rapid synchronized firing that has been studied extensively, recent experimental work indicates that direct electrical or synaptic coupling is weak, but shared synaptic input in the absence of modulated stimuli is strong. However, previous modeling efforts have not accounted for this aspect of firing in the parasol cell population. Here we develop a new model that incorporates the effects of common noise, and apply it to analyze the light responses and synchronized firing of a large, densely-sampled network of over 250 simultaneously recorded parasol cells. We use a generalized linear model in which the spike rate in each cell is determined by the linear combination of the spatio-temporally filtered visual input, the temporally filtered prior spikes of that cell, and unobserved sources representing common noise. The model accurately captures the statistical structure of the spike trains and the encoding of the visual stimulus, without the direct coupling assumption present in previous modeling work. Finally, we examined the problem of decoding the visual stimulus from the spike train given the estimated parameters. The common-noise model produces Bayesian decoding performance as accurate as that of a model with direct coupling, but with significantly more robustness to spike timing perturbations.     

Lipoteichoic acid is an important microbe-associated molecular pattern of Lactobacillus rhamnosus GG

Background

Receptors with a single transmembrane (TM) domain are essential for the signal transduction across the cell membrane. NMR spectroscopy is a powerful tool to study structure of the single TM domain. The expression and purification of a TM domain in Escherichia coli (E.coli) is challenging due to its small molecular weight. Although ketosteroid isomerase (KSI) is a commonly used affinity tag for expression and purification of short peptides, KSI tag needs to be removed with the toxic reagent cyanogen bromide (CNBr).

Result

The purification of the TM domain of p75 neurotrophin receptor using a KSI tag with the introduction of a thrombin cleavage site is described herein. The recombinant fusion protein was refolded into micelles and was cleaved with thrombin. Studies showed that purified protein could be used for structural study using NMR spectroscopy.

Conclusions

These results provide another strategy for obtaining a single TM domain for structural studies without using toxic chemical digestion or acid to remove the fusion tag. The purified TM domain of p75 neurotrophin receptor will be useful for structural studies.