Some theoretical results on neural spike train probability models

DOI10.1214/009053607000000280zbMath1129.62101arXivmath/0703829OpenAlexW2012911002MaRDI QIDQ2473079

Hock Peng Chan, Wei-Liem Loh

Publication date: 26 February 2008

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/math/0703829

zbMATH Keywords

importance samplingPoisson processtemplate matchingcounting processscan statisticsconditional intensityboundary crossing probabilitysieve maximum likelihood estimationneural spike train

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Neural biology (92C20) Signal detection and filtering (aspects of stochastic processes) (60G35) Inference from stochastic processes (62M99)

Related Items (4)

On a spike train probability model with interacting neural units ⋮ Modeling some properties of circadian rhythms ⋮ Some theoretical results on neural spike train probability models ⋮ Discussion on “Change-Points: From Sequential Detection to Biology and Back” by David Siegmund

Cites Work

• Unnamed Item
• Unnamed Item
• Sequential analysis. Tests and confidence intervals
• A lower bound on the error in nonparametric regression type problems
• A central limit theorem under metric entropy with \(L_ 2\) bracketing
• Importance sampling in the Monte Carlo study of sequential tests
• Convergence rate of sieve estimates
• Upper bounds and importance sampling of \(p\)-values of DNA and protein sequence alignments
• Large deviations for template matching between point processes
• Probability inequalities for likelihood ratios and convergence rates of sieve MLEs
• Some theoretical results on neural spike train probability models
• A Spike-Train Probability Model
• Unitary Events in Multiple Single-Neuron Spiking Activity: I. Detection and Significance
• Algorithms for removing recovery-related distortion from auditory-nerve discharge patterns
• Uniform Central Limit Theorems
• Pattern Filtering for Detection of Neural Activity, with Examples from HVc Activity During Sleep in Zebra Finches
• Efficient recursive algorithms for detection of abrupt changes in signals and control systems
• [https://portal.mardi4nfdi.de/wiki/Publication:4743580 Approximation dans les espaces m�triques et th�orie de l'estimation]
• An Introduction to the Theory of Point Processes
• A Local Limit Theorem for Nonlattice Multi-Dimensional Distribution Functions
• Statistical analysis of temporal evolution in single-neuron firing rates
• Comments on: A general science-based framework for dynamical spatio-temporal models

This page was built for publication: Some theoretical results on neural spike train probability models