Which spike train distance is most suitable for distinguishing rate and temporal coding?

Background: It is commonly assumed in neuronal coding that repeated presentations of a stimulus to a coding neuron elicit similar responses. One common way to assess similarity are spike train distances. These can be divided into spike-resolved, such as the Victor-Purpura and the van Rossum distance, and time-resolved, e.g. the ISI-, the SPIKE- and the RI-SPIKE-distance. New Method: We use independent steady-rate Poisson processes as surrogates for spike trains with fixed rate and no timing information to address two basic questions: How does the sensitivity of the different spike train distances to temporal coding depend on the rates of the two processes and how do the distances deal with very low rates? Results: Spike-resolved distances always contain rate information even for parameters indicating time coding. This is an issue for reasonably high rates but beneficial for very low rates. In contrast, the operational range for detecting time coding of time-resolved distances is superior at normal rates, but these measures produce artefacts at very low rates. The RI-SPIKE-distance is the only measure that is sensitive to timing information only. Comparison with Existing Methods: While our results on rate-dependent expectation values for the spike-resolved distances agree with \citet{Chicharro11}, we here go one step further and specifically investigate applicability for very low rates. Conclusions: The most appropriate measure depends on the rates of the data being analysed. Accordingly, we summarize our results in one table that allows an easy selection of the preferred measure for any kind of data.Comment: 14 pages, 6 Figures, 1 Tabl

PySpike - A Python library for analyzing spike train synchrony

Understanding how the brain functions is one of the biggest challenges of our time. The analysis of experimentally recorded neural firing patterns (spike trains) plays a crucial role in addressing this problem. Here, the PySpike library is introduced, a Python package for spike train analysis providing parameter-free and time-scale independent measures of spike train synchrony. It allows to compute similarity and dissimilarity profiles, averaged values and distance matrices. Although mainly focusing on neuroscience, PySpike can also be applied in other contexts like climate research or social sciences. The package is available as Open Source on Github and PyPI.Comment: 7 pages, 6 figure

A guide to time-resolved and parameter-free measures of spike train synchrony

Measures of spike train synchrony have proven a valuable tool in both experimental and computational neuroscience. Particularly useful are time-resolved methods such as the ISI- and the SPIKE-distance, which have already been applied in various bivariate and multivariate contexts. Recently, SPIKE-Synchronization was proposed as another time-resolved synchronization measure. It is based on Event-Synchronization and has a very intuitive interpretation. Here, we present a detailed analysis of the mathematical properties of these three synchronization measures. For example, we were able to obtain analytic expressions for the expectation values of the ISI-distance and SPIKE-Synchronization for Poisson spike trains. For the SPIKE-distance we present an empirical formula deduced from numerical evaluations. These expectation values are crucial for interpreting the synchronization of spike trains measured in experiments or numerical simulations, as they represent the point of reference for fully randomized spike trains.Comment: 8 pages, 4 figure

Using spike train distances to identify the most discriminative neuronal subpopulation

Background: Spike trains of multiple neurons can be analyzed following the summed population (SP) or the labeled line (LL) hypothesis. Responses to external stimuli are generated by a neuronal population as a whole or the individual neurons have encoding capacities of their own. The SPIKE-distance estimated either for a single, pooled spike train over a population or for each neuron separately can serve to quantify these responses. New Method: For the SP case we compare three algorithms that search for the most discriminative subpopulation over all stimulus pairs. For the LL case we introduce a new algorithm that combines neurons that individually separate different pairs of stimuli best. Results: The best approach for SP is a brute force search over all possible subpopulations. However, it is only feasible for small populations. For more realistic settings, simulated annealing clearly outperforms gradient algorithms with only a limited increase in computational load. Our novel LL approach can handle very involved coding scenarios despite its computational ease. Comparison with Existing Methods: Spike train distances have been extended to the analysis of neural populations interpolating between SP and LL coding. This includes parametrizing the importance of distinguishing spikes being fired in different neurons. Yet, these approaches only consider the population as a whole. The explicit focus on subpopulations render our algorithms complimentary. Conclusions: The spectrum of encoding possibilities in neural populations is broad. The SP and LL cases are two extremes for which our algorithms provide correct identification results.Comment: 14 pages, 9 Figure

Risk of angioedema following invasive or surgical procedures in HAE type I and II : the natural history

Background: Hereditary angioedema (HAE), caused by deficiency in C1-inhibitor (C1-INH), leads to unpredictable edema of subcutaneous tissues with potentially fatal complications. As surgery can be a trigger for edema episodes, current guidelines recommend preoperative prophylaxis with C1-INH or attenuated androgens in patients with HAE undergoing surgery. However, the risk of an HAE attack in patients without prophylaxis has not been quantified. Objectives: This analysis examined rates of perioperative edema in patients with HAE not receiving prophylaxis. Methods: This was a retrospective analysis of records of randomly selected patients with HAE type I or II treated at the Frankfurt Comprehensive Care Centre. These were examined for information about surgical procedures and the presence of perioperative angioedema. Results: A total of 331 patients were included; 247 underwent 700 invasive procedures. Of these procedures, 335 were conducted in 144 patients who had not received prophylaxis at the time of surgery. Categories representing significant numbers of procedures were abdominal (n = 113), ENT (n = 71), and gynecological (n = 58) procedures. The rate of documented angioedema without prophylaxis across all procedures was 5.7%; in 24.8% of procedures, the presence of perioperative angioedema could not be excluded, leading to a maximum potential risk of 30.5%. Predictors of perioperative angioedema could not be identified. Conclusion: The risk of perioperative angioedema in patients with HAE type I or II without prophylaxis undergoing surgical procedures ranged from 5.7% to 30.5% (CI 3.5–35.7%). The unpredictability of HAE episodes supports current international treatment recommendations to consider short-term prophylaxis for all HAE patients undergoing surgery