A model for the joint evaluation of burstiness and regularity in oscillatory spike trains

Poster presentation: Introduction The ability of neurons to emit different firing patterns is considered relevant for neuronal information processing. In dopaminergic neurons, prominent patterns include highly regular pacemakers with separate spikes and stereotyped intervals, processes with repetitive bursts and partial regularity, and irregular spike trains with nonstationary properties. In order to model and quantify these processes and the variability of their patterns with respect to pharmacological and cellular properties, we aim to describe the two dimensions of burstiness and regularity in a single model framework. Methods We present a stochastic spike train model in which the degree of burstiness and the regularity of the oscillation are described independently and with two simple parameters. In this model, a background oscillation with independent and normally distributed intervals gives rise to Poissonian spike packets with a Gaussian firing intensity. The variability of inter-burst intervals and the average number of spikes in each burst indicate regularity and burstiness, respectively. These parameters can be estimated by fitting the model to the autocorrelograms. This allows to assign every spike train a position in the two-dimensional space described by regularity and burstiness and thus, to investigate the dependence of the firing patterns on different experimental conditions. Finally, burst detection in single spike trains is possible within the model because the parameter estimates determine the appropriate bandwidth that should be used for burst identification. Results and Discussion We applied the model to a sample data set obtained from dopaminergic substantia nigra and ventral tegmental area neurons recorded extracellularly in vivo and studied differences between the firing activity of dopaminergic neurons in wildtype and K-ATP channel knock-out mice. The model is able to represent a variety of discharge patterns and to describe changes induced pharmacologically. It provides a simple and objective classification scheme for the observed spike trains into pacemaker, irregular and bursty processes. In addition to the simple classification, changes in the parameters can be studied quantitatively, also including the properties related to bursting behavior. Interestingly, the proposed algorithm for burst detection may be applicable also to spike trains with nonstationary firing rates if the remaining parameters are unaffected. Thus, the proposed model and its burst detection algorithm can be useful for the description and investigation of neuronal firing patterns and their variability with cellular and experimental conditions

The Statistics of the BATSE Spectral Features

The absence of a BATSE line detection in a gamma-ray burst spectrum during the mission's first six years has led to a statistical analysis of the occurrence of lines in the BATSE burst database; this statistical analysis will still be relevant if lines are detected. We review our methodology, and present new simulations of line detectability as a function of the line parameters. We also discuss the calculation of the number of ``trials'' in the BATSE database, which is necessary for our line detection criteria.Comment: 5 pages, 2 figures, AIPPROC LaTeX, to appear in "Gamma-Ray Bursts, 4th Huntsville Symposium," eds. C. Meegan, R. Preece and T. Koshu

IceCube Non-detection of GRBs: Constraints on the Fireball Properties

The increasingly deep limit on the neutrino emission from gamma-ray bursts (GRBs) with IceCube observations has reached the level that could put useful constraints on the fireball properties. We first present a revised analytic calculation of the neutrino flux, which predicts a flux an order of magnitude lower than that obtained by the IceCube collaboration. For benchmark model parameters (e.g. the bulk Lorentz factor is \Gamma=10^{2.5}, the observed variability time for long GRBs is t_v=0.01 s and the ratio between the energy in accelerated protons and in radiation is \eta_p=10 for every burst) in the standard internal shock scenario, the predicted neutrino flux from 215 bursts during the period of the 40-string and 59-string configurations is found to be a factor of ~3 below the IceCube sensitivity. However, if we accept the recently found inherent relation between the bulk Lorentz factor and burst energy, the expected neutrino flux increases significantly and the spectral peak shifts to lower energy. In this case, the non-detection then implies that the baryon loading ratio should be \eta_p<10 if the variability time of long GRBs is fixed to t_v=0.01 s. Instead, if we relax the standard internal shock scenario but keep to assume \eta_p=10, the non-detection constrains the dissipation radius to be R>4x10^{12} cm assuming the same dissipation radius for every burst and benchmark parameters for fireballs. We also calculate the diffuse neutrino flux from GRBs for different luminosity functions existing in the literature. The expected flux exceeds the current IceCube limit for some luminosity functions, and thus the non-detection constrains \eta_p<10 in such cases when the variability time of long GRBs is fixed to t_v=0.01 s.Comment: Accepted by ApJ, 14 pages, 5 figures, typos corrected, scheduled for the June 10, 2012, v752 - 1 issu

Gamma-ray Burst Afterglow with Continuous Energy Injection: Signature of a Highly-Magnetized Millisecond Pulsar

We investigate the consequences of a continuously injecting central engine on the gamma-ray burst afterglow emission, focusing more specifically on a highly-magnetized millisecond pulsar engine. For initial pulsar parameters within a certain region of the parameter space, the afterglow lightcurves are predicted to show a distinctive achromatic bump feature, the onset and duration of which range from minutes to months, depending on the pulsar and the fireball parameters. The detection of or upper limits on such features would provide constraints on the burst progenitor and on magnetar-like central engine models. An achromatic bump such as that in GRB 000301C afterglow may be caused by a millisecond pulsar with P0=3.4 millisecond and Bp=2.7e14 Gauss.Comment: 5 pages, emulateapj style, to appear in ApJ Letters, updated with the accepted version, a few corrections are mad

Damage monitoring in sandwich beams by modal parameter shifts: a comparative study of burst random and sine dwell vibration testing

This paper presents an experimental study on the effects of multi-site damage on the vibration response of honeycomb sandwich beams, damaged by two different ways i.e., impact damage and core-only damage simulating damage due to bird or stone impact or due to mishandling during assembly and maintenance. The variation of the modal parameters with different levels of impact energy and density of damage is studied. Vibration tests have been carried out with both burst random and sine dwell testing in order to evaluate the damping estimation efficiency of these methods in the presence of damage. Sine dwell testing is done in both up and down frequency directions in order to detect structural non-linearities. Results show that damping ratio is a more sensitive parameter for damage detection than the natural frequency. Design of experiments (DOE) highlighted density of damage as the factor having a more significant effect on the modal parameters and also proved that sine dwell testing is more suitable for damping estimation in the presence of damage as compared to burst random testing

A Bayesian method for single molecule, fluorescence burst analysis

There is currently great interest in determining physical parameters, e.g. fluorescence lifetime, of individual molecules that inform on environmental conditions, whilst avoiding the artefacts of ensemble averaging. Protein interactions, molecular dynamics and sub-species can all be studied. In a burst integrated fluorescence lifetime (BIFL) experiment, identification of fluorescent bursts from single molecules above background detection is a problem. This paper presents a Bayesian method for burst identification based on model selection and demonstrates the detection of bursts consisting of 10% signal amplitude. The method also estimates the fluorescence lifetime (and its error) from the burst data