Comparison of Threshold and Tolerance Nociceptive Withdrawal Reflexes in Horses

The nociceptive withdrawal reflex (NWR) is used to investigate nociception in horses. The NWR threshold is a classical model endpoint. The aims of this study were to determine NWR tolerance and to compare threshold and tolerance reflexes in horses. In 12 horses, the NWR was evoked through electrical stimulation of the digital nerve and recorded via electromyography from the deltoid. Behavioral reactions were scored from 0 to 5 (tolerance). First, the individual NWR threshold was defined, then stimulation intensity was increased to tolerance. The median NWR threshold was 7.0 mA, whereas NWR tolerance was 10.7 mA. Upon visual inspection of the records, two main reflex components R1 (median latency 44 ms) and R2 (median latency 81 ms) were identified at threshold. Increasing stimulation intensity to tolerance led to a significant increase in the amplitude and duration of R1 and R2, whereas their latency decreased. At tolerance, a single burst of early, high-amplitude reflex activity, with a median latency of 39 ms, was detected in 15 out of 23 stimulations (65%). The results of this study suggest that (1) it is feasible to determine NWR tolerance in horses and (2) high-intensity stimuli initiate ultrafast bursts of reflex activity, which is well known in practice and has now been quantified using the NWR model.

Applying saliency-map analysis in searches for pulsars and fast radio bursts

Context. We investigate the use of saliency-map analysis to aid in searches for transient signals, such as fast radio bursts and individual pulses from radio pulsars. Aims. Our aim is to demonstrate that saliency maps provide the means to understand predictions from machine learning algorithms and can be implemented in pipelines used to search for transient events. Methods. We implemented a new deep learning methodology to predict whether any segment of the data contains a transient event. The algorithm was trained using real and simulated data sets. We demonstrate that the algorithm is able to identify such events. The output results are visually analysed via the use of saliency maps. Results. We find that saliency maps can produce an enhanced image of any transient feature without the need for de-dispersion or removal of radio frequency interference. The maps can be used to understand which features in the image were used in making the machine learning decision and to visualise the transient event. Even though the algorithm reported here was developed to demonstrate saliency-map analysis, we have detected a single burst event, in archival data, with dispersion measure of 41 cm−3 pc that is not associated with any currently known pulsar.

Interspike intervals within retinal spike bursts combinatorially encode multiple stimulus features

Neurons in various regions of the brain generate spike bursts. While the number of spikes within a burst has been shown to carry information, information coding by interspike intervals (ISIs) is less well understood. In particular, a burst with k spikes has k−1 intraburst ISIs, and these k−1 ISIs could theoretically encode k−1 independent values. In this study, we demonstrate that such combinatorial coding occurs for retinal bursts. By recording ganglion cell spikes from isolated salamander retinae, we found that intraburst ISIs encode oscillatory light sequences that are much faster than the light intensity modulation encoded by the number of spikes. When a burst has three spikes, the two intraburst ISIs combinatorially encode the amplitude and phase of the oscillatory sequence. Analysis of trial-to-trial variability suggested that intraburst ISIs are regulated by two independent mechanisms responding to orthogonal oscillatory components, one of which is common to bursts with different number of spikes. Therefore, the retina encodes multiple stimulus features by exploiting all degrees of freedom of burst spike patterns, i.e., the spike number and multiple intraburst ISIs.Author SummaryNeurons in various regions of the brain generate spike bursts. Bursts are typically composed of a few spikes generated within dozens of milliseconds, and individual bursts are separated by much longer periods of silence (∼hundreds of milliseconds). Recent evidence indicates that the number of spikes in a burst, the interspike intervals (ISIs), and the overall duration of a burst, as well as the timing of burst onset, encode information. However, it remains unknown whether multiple ISIs within a single burst encode multiple independent information contents. Here we demonstrate that such combinatorial ISI coding occurs for spike bursts in the retina. We recorded ganglion cell spikes from isolated salamander retinae stimulated with computer-generated movies. Visual response analyses indicated that multiple ISIs within a single burst combinatorially encode the phase and amplitude of oscillatory light sequences, which are different from the stimulus feature encoded by the spike number. The result demonstrates that the retina encodes multiple stimulus features by exploiting all degrees of freedom of burst spike patterns, i.e., the spike number and multiple intraburst ISIs. Because synaptic transmission in the visual system is highly sensitive to ISIs, the combinatorial ISI coding must have a major impact on visual information processing.

Effects of 22Ne sedimentation and metallicity on the local 40 pc white dwarf luminosity function

Aims. We analyzed the effect of the sedimentation of 22Ne on the local white dwarf luminosity function by studying scenarios under different Galactic metallicity models. Methods. We use an advanced population synthesis code based on Monte Carlo techniques to derive the synthetic luminosity function. The code incorporates the most recent and reliable cooling sequences and an accurate modeling of the observational biases under different scenarios. We first analyzed the case for a model with constant solar metallicity and compared the models with and without 22Ne sedimentation with the observed luminosity function for a pure thin-disk population. Then we analyzed the possible effects of a thick-disk contribution. We also studied model scenarios with different metallicities, including 22Ne sedimentation. The analysis was quantified from a statistical χ2-test value for the complete and also for the most significant regions of the white dwarf luminosity function. Finally, a best-fit model along with a disk age estimate was derived. Results. Models with constant solar metallicity cannot simultaneously reproduce the peak and cutoff of the white dwarf luminosity function. The additional release of energy due to 22Ne sedimentation piles up more objects in brighter bins of the faint end of the luminosity function. The contribution of a single-burst thick-disk population increases the number of stars in the magnitude interval centered around Mbol = 15.75. The metallicity model that follows a Twarog profile is disposable. Our best-fit model was obtained when a dispersion in metallicities of about solar metallicity was considered along with a 22Ne sedimentation model, a thick-disk contribution, and an age of the thin disk of 8.8 ± 0.2 Gyr. Conclusions. Our population synthesis model is able to reproduce the local white dwarf luminosity function with a high degree of precision when a dispersion in metallicities around a model with solar values is adopted. Although the effects of 22Ne sedimentation are only marginal and the contribution of a thick-disk population is minor, both of them help in better fitting the peak and the cutoff regions of the white dwarf luminosity function.