Sulfhydryl Binding Reagents Increase the Conductivity of the Light-Sensitive Channel and Inhibit Phototransduction in Retinal Rods

The mechanisms by which sulfhydryl (SH-) binding reagents modulate the light-sensitive conductance of retinal rods were investigated by current recording from single rods, by patch clamp recording from the plasma membrane of the rod outer segment (ROS), and by biochemical study of their effects on the light-induced hydrolysis of cyclic GMP. The electrophysiology, as well as measurements of the reagents' ability to traverse the ROS plasma membrane, was done on amphibian (Rona and Ambystoma) rods, and the biochemistry on bovine rods. The main SH-reagents used were N-ethyl-maleimide (NEM) and iodoacetamide (IAA). Both transiently increased rod current, but part of the large current could not be turned off by light. After a few minutes' exposure, NEM, but not IAA, caused a continuous decay of the rod's light sensitivity. In patch-clamp recordings from the ROS plasma membrane, the reagents increased conductivity both in the presence and absence of cGMP, consistent with the observation that the drug-induced current increase in intact rods involved both light-sensitive and light-insensitive components. In vitro, NEM was found to be a powerful inhibitor of cGMP hydrolysis, which can explain the gradual loss of light sensitivity in the rod and could initially contribute to the increased dark current via elevated cGMP levels. Thus, SH-reagents act both by modifying the light-sensitive channel and by inhibiting phototransduction inside the rod

An online spike detection and spike classification algorithm capable of instantaneous resolution of overlapping spikes

For the analysis of neuronal cooperativity, simultaneously recorded extracellular signals from neighboring neurons need to be sorted reliably by a spike sorting method. Many algorithms have been developed to this end, however, to date, none of them manages to fulfill a set of demanding requirements. In particular, it is desirable to have an algorithm that operates online, detects and classifies overlapping spikes in real time, and that adapts to non-stationary data. Here, we present a combined spike detection and classification algorithm, which explicitly addresses these issues. Our approach makes use of linear filters to find a new representation of the data and to optimally enhance the signal-to-noise ratio. We introduce a method called “Deconfusion” which de-correlates the filter outputs and provides source separation. Finally, a set of well-defined thresholds is applied and leads to simultaneous spike detection and spike classification. By incorporating a direct feedback, the algorithm adapts to non-stationary data and is, therefore, well suited for acute recordings. We evaluate our method on simulated and experimental data, including simultaneous intra/extra-cellular recordings made in slices of a rat cortex and recordings from the prefrontal cortex of awake behaving macaques. We compare the results to existing spike detection as well as spike sorting methods. We conclude that our algorithm meets all of the mentioned requirements and outperforms other methods under realistic signal-to-noise ratios and in the presence of overlapping spikes

A Model-Based Spike Sorting Algorithm for Removing Correlation Artifacts in Multi-Neuron Recordings

Jonathan W. Pillow is with UT Austin, Jonathon Shlens is with the Salk Institute, E. J. Chichilnisky is with the Salk Institute, and Eero P. Simoncelli is with New York University.We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call “binary pursuit”. The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth.This work was supported by: Royal Society Society USA/Canada Research Fellowship (JWP) (http://royalsociety.org/grants/); Center for Perceptual Systems, startup funding (JP) (http://www.utexas.edu/cola/centers/cps/); Sloan Research Fellowship (JWP) (http://www.sloan.org/); Miller Institute for Basic Research in Science (JS) (http://millerinstitute.berkeley.edu/); National Eye Institute (NEI) grant EY018003 (EJC, EPS); National Institutes of Health (NIH) Grant EY017736 (EJC); and Howard Hughes Medical Institute (EPS) (http://www.hhmi.org/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Psycholog

A cyclic-AMP-gated conductance in cochlear hair cells

AbstractThe patch clamp technique was used to record cAMP-dependent currents of the guinea pig cochlear hair cell plasma membrane. Data obtained indicate that the channels passing this current are moderately selective for monovalent cations and are effectively blocked by L-cis-diltiazem and reversibly blocked by 1 mM Mg2+ or Ca2+. The single-channel unit conductance estimated in the absence of divalent cations is about 16 pS. The results demonstrate that cyclic nucleotide-dependent channels of cochlear hair cells are virtually identical to the photoreceptor and olfactory ones