Biomaterial Database

Bootstrap significance test of synchronous spike events--a case study of oscillatory spike trains. 2007

Hiroyuki Ito

Faculty of Engineering, Kyoto Sangyo University, Kyoto 603-8555, Japan. hiro@ics.kyoto-su.ac.jp

The purpose of this monograph is two folds. Firstly, we introduce challenging spike data to the statistical analysis. The data of two neurons recorded from the cat visual pathway show various non-stationary characteristics not fitted by the Poisson spike train. Spike firings of both neurons are strongly periodic and tightly synchronized. Our second purpose is a case study of applications of various statistical methods for the significance test of the time-varying spike synchrony. We provide various general remarks to the statistical analysis of the synchronous spike activities. At first, we apply the unitary event analysis. The significance limit for the coincident spike events by the Poisson distribution is compared with the limit given by the non-parametric test based on the bootstrap samplings. The bootstrap test performs superior to the Poisson test in two respects: (1) avoids false positives due to the sudden change of spike density; and (2) takes into account the non-stationary change of the spiking pattern at different sampling windows. When the spike trains are highly periodic, the histogram of the number of accidental coincident spike events over the bootstrap samples has a systematically larger variance than the Poisson distribution. We find that a large variance originates from the correlation between the successive coincident spike events in the structured spike trains. The significance of the time-varying synchrony is tested by another statistical method by Ventura et al., which is based on the adaptive smoothing method and the bootstrap significance test. .

UI	MeSH Term	Description	Entries
D007564	Japan	A country in eastern Asia, island chain between the North Pacific Ocean and the Sea of Japan, east of the Korean Peninsula. The capital is Tokyo.	Bonin Islands
D002415	Cats	The domestic cat, Felis catus, of the carnivore family FELIDAE, comprising over 30 different breeds. The domestic cat is descended primarily from the wild cat of Africa and extreme southwestern Asia. Though probably present in towns in Palestine as long ago as 7000 years, actual domestication occurred in Egypt about 4000 years ago. (From Walker's Mammals of the World, 6th ed, p801)	Felis catus,Felis domesticus,Domestic Cats,Felis domestica,Felis sylvestris catus,Cat,Cat, Domestic,Cats, Domestic,Domestic Cat
D004569	Electroencephalography	Recording of electric currents developed in the brain by means of electrodes applied to the scalp, to the surface of the brain, or placed within the substance of the brain.	EEG,Electroencephalogram,Electroencephalograms
D000200	Action Potentials	Abrupt changes in the membrane potential that sweep along the CELL MEMBRANE of excitable cells in response to excitation stimuli.	Spike Potentials,Nerve Impulses,Action Potential,Impulse, Nerve,Impulses, Nerve,Nerve Impulse,Potential, Action,Potential, Spike,Potentials, Action,Potentials, Spike,Spike Potential
D000704	Analysis of Variance	A statistical technique that isolates and assesses the contributions of categorical independent variables to variation in the mean of a continuous dependent variable.	ANOVA,Analysis, Variance,Variance Analysis,Analyses, Variance,Variance Analyses
D000818	Animals	Unicellular or multicellular, heterotrophic organisms, that have sensation and the power of voluntary movement. Under the older five kingdom paradigm, Animalia was one of the kingdoms. Under the modern three domain model, Animalia represents one of the many groups in the domain EUKARYOTA.	Animal,Metazoa,Animalia
D001699	Biometry	The use of statistical and mathematical methods to analyze biological observations and phenomena.	Biometric Analysis,Biometrics,Analyses, Biometric,Analysis, Biometric,Biometric Analyses
D015233	Models, Statistical	Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.	Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D016012	Poisson Distribution	A distribution function used to describe the occurrence of rare events or to describe the sampling distribution of isolated counts in a continuum of time or space.	Distribution, Poisson