Measuring spike train synchrony

Estimating the degree of synchrony or reliability between two or more spike trains is a frequent task in both experimental and computational neuroscience. In recent years, many different methods have been proposed that typically compare the timing of spikes on a certain time scale to be fixed beforehand. Here, we propose the ISI-distance, a simple complementary approach that extracts information from the interspike intervals by evaluating the ratio of the instantaneous frequencies. The method is parameter free, time scale independent and easy to visualize as illustrated by an application to real neuronal spike trains obtained in vitro from rat slices. In a comparison with existing approaches on spike trains extracted from a simulated Hindemarsh-Rose network, the ISI-distance performs as well as the best time-scale-optimized measure based on spike timing.Comment: 11 pages, 13 figures; v2: minor modifications; v3: minor modifications, added link to webpage that includes the Matlab Source Code for the method (http://inls.ucsd.edu/~kreuz/Source-Code/Spike-Sync.html

An Analysis Pipeline for Genome-wide Association Studies

We developed an efficient pipeline to analyze genome-wide association study single nucleotide polymorphism scan results. Purl scripts were used to convert genotypes called using the BRLMM algorithm into a modified PB format. We computed summary statistics characteristic of our case and control populations including allele counts, missing values, heterozygosity, measures of compliance with Hardy-Weinberg equilibrium, and several population difference statistics. In addition, we computed association tests, including exact tests of association for genotypes, alleles, the Cochran-Armitage linear trend test, and dominant, recessive, and overdominant models at every single nucleotide polymorphism (SNP). In addition, pairwise linkage disequilbrium statistics were elaborated, using the command line version of HaploView, which was possible by writing a reformatting script. Additional Perl scripts permit loading the results into a MySQL database conjoined with a Generic Genome Browser (gbrowse) for comprehensive visualization. This browser incorporates a download feature that provides actual case and control genotypes to users in associated genomic regions. Thus, re-analysis “on the fly” is possible for casual browser users from anywhere on the Internet

Gamma Oscillations of Spiking Neural Populations Enhance Signal Discrimination

Selective attention is an important filter for complex environments where distractions compete with signals. Attention increases both the gamma-band power of cortical local field potentials and the spike-field coherence within the receptive field of an attended object. However, the mechanisms by which gamma-band activity enhances, if at all, the encoding of input signals are not well understood. We propose that gamma oscillations induce binomial-like spike-count statistics across noisy neural populations. Using simplified models of spiking neurons, we show how the discrimination of static signals based on the population spike-count response is improved with gamma induced binomial statistics. These results give an important mechanistic link between the neural correlates of attention and the discrimination tasks where attention is known to enhance performance. Further, they show how a rhythmicity of spike responses can enhance coding schemes that are not temporally sensitive

Extraction and Characterization of Essential Discharge Patterns from Multisite Recordings of Spiking Ongoing Activity

Conditional sampling, in comparison with the classical constant time-bin sampling, enables to reject, at least in most cases, the common mode modulation of the spiking frequency across different spiking sources. Here we consider a simple but significant example while a more general analysis is currently in preparation: Consider two spiking neurons and let n1, n2 the number of spikes emitted in a time period T. They both follow a Poisson process with parameters λcλ1T and λcλ2T respectively, being λc a common modulation term, λ1 and λ2 the independent component of their activity. Let n1 + n2 = k and Pn1,n2 = Pn1,k−n1 the probability of observing n1 and k − n1 spikes (respectively from the first and the second neuron) in a period T. Then Pn1,k−n1 = e−λcT (λ1+λ2) (T λc) k λn 1 1 λk−n 1 2 n1!(k−n1)! Now consider the conditional probability of observing n1 and k − n1 spikes i

カーネル法による時系列データの解析

Thesis (Master of Information Science)--University of Tsukuba, no. 34311, 2015.3.25201

The information theoretic approach to signal anomaly detection for cognitive radio

Efficient utilisation and sharing of limited spectrum resources in an autonomous fashion is one of the primary goals of cognitive radio. However, decentralised spectrum sharing can lead to interference scenarios that must be detected and characterised to help achieve the other goal of cognitive radio—reliable service for the end user. Interference events can be treated as unusual and therefore anomaly detection algorithms can be applied for their detection. Two complementary algorithms based on information theoretic measures of statistical distribution divergence and information content are proposed. The first method is applicable to signals with periodic structures and is based on the analysis of Kullback-Leibler divergence. The second utilises information content analysis to detect unusual events. Results from software and hardware implementations show that the proposed algorithms are effective, simple, and capable of processing high-speed signals in real time. Additionally, neither of the algorithms require demodulation of the signal

Distributed Fading Memory for Stimulus Properties in the Primary Visual Cortex

The brain has a one-back memory for visual stimuli. Neural responses to an image contain as much information about the current image as it does about another image presented immediately before