Neural Comput - Applying the multivariate time-rescaling theorem to neural population models.

Tópicos

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Resumo

Statistical models of neural activity are integral to modern neuroscience. Recently interest has grown in modeling the spiking activity of populations of simultaneously recorded neurons to study the effects of correlations and functional connectivity on neural information processing. However, any statistical model must be validated by an appropriate goodness-of-fit test. Kolmogorov-Smirnov tests based on the time-rescaling theorem have proven to be useful for evaluating point-process-based statistical models of single-neuron spike trains. Here we discuss the extension of the time-rescaling theorem to the multivariate (neural population) case. We show that even in the presence of strong correlations between spike trains, models that neglect couplings between neurons can be erroneously passed by the univariate time-rescaling test. We present the multivariate version of the time-rescaling theorem and provide a practical step-by-step procedure for applying it to testing the sufficiency of neural population models. Using several simple analytically tractable models and more complex simulated and real data sets, we demonstrate that important features of the population activity can be detected only using the multivariate extension of the test.

Resumo Limpo

statist model neural activ integr modern neurosci recent interest grown model spike activ popul simultan record neuron studi effect correl function connect neural inform process howev statist model must valid appropri goodnessoffit test kolmogorovsmirnov test base timeresc theorem proven use evalu pointprocessbas statist model singleneuron spike train discuss extens timeresc theorem multivari neural popul case show even presenc strong correl spike train model neglect coupl neuron can erron pass univari timeresc test present multivari version timeresc theorem provid practic stepbystep procedur appli test suffici neural popul model use sever simpl analyt tractabl model complex simul real data set demonstr import featur popul activ can detect use multivari extens test

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