Measures of multiple spike train synchrony are essential in order to study issues such as spike timing reliability, network synchronization, and neuronal coding. These measures can broadly be divided in multivariate measures and averages over bivariate measures. One of the most recent bivariate approaches, the ISI-distance, employs the ratio of instantaneous interspike intervals (ISIs). In this...

Although spike trains are the principal channel of communication between neurons, a single stimulus will elicit different spike trains from trial to trial. This variability, in both spike timings and spike number can obscure the temporal structure of spike trains and often means that computations need to be run on numerous spike trains in order to extract features common across all the response...

1Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal 2Group for Neural Theory, INSERM U960, Département d’Etudes Cognitives, Ecole Normale Supérieure, Paris, France 3Werner Reichardt Centre for Integrative Neuroscience, University of Tübingen, Germany ∗These authors contributed equally †To whom correspondence should be addressed; E-mail: [email protected] or christ...

Estimating the population activity patterns between two or more spike trains is a fundamental problem in studying neural coding in computational neuroscience. In recent years, there are many different methods proposed to build a framework to deal with these problems by using spike train metric. Here we suggest a kernel method for multichannel spike trains that can provide an opportunity to meas...

The retina is divided into parallel and mostly independent ON and OFF pathways, but the ON pathway "cross" inhibits the OFF pathway. Cross inhibition was thought to improve signal processing by the OFF pathway, but its effect on contrast encoding had not been tested experimentally. To quantify the effect of cross inhibition on the encoding of contrast, we presented a dark flash to an in vitro p...

The relationship between a neuron's complex inputs and its spiking output defines the neuron's coding strategy. This is frequently and effectively modeled phenomenologically by one or more linear filters that extract the components of the stimulus that are relevant for triggering spikes and a nonlinear function that relates stimulus to firing probability. In many sensory systems, these two comp...

The Victor-Purpura spike train metric has recently been extended to a family of multineuron metrics and used to analyze spike trains recorded simultaneously from pairs of proximate neurons. The metric is one of the two metrics commonly used for quantifying the distance between two spike trains; the other is the van Rossum metric. Here, we suggest an extension of the van Rossum metric to a multi...

The stock market is a popular topic in Twitter. The number of tweets concerning a stock varies over days, and sometimes exhibits a significant spike. In this paper, we investigate the relationship between Twitter volume spikes and stock options pricing. We start with the underlying assumption of the Black–Scholes model, the most widely used model for stock options pricing, and investigate when ...

Stimulus properties, attention, and behavioral context influence correlations between the spike times produced by a pair of neurons. However, the biophysical mechanisms that modulate these correlations are poorly understood. With a combined theoretical and experimental approach, we show that the rate of balanced excitatory and inhibitory synaptic input modulates the magnitude and timescale of p...

The spike-triggered average voltage (STV) is an experimentally measurable quantity that is determined by both the membrane response properties and the statistics of the synaptic drive. Here, the form of the STV is modelled for neurons with three distinct types of subthreshold dynamics; passive decay, h-current sag, and damped oscillations. Analytical expressions for the STV are first obtained i...