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A Simple Probabilistic and Point-process Response Model for Predicting Every Spike in Optogenetics
optogenetics point processes generalized linear models response functions neuronal data generalized additive models prediction.
2012/9/19
Optogenetics is a new tool to stimulate genetically targeted neuronal circuits us-ing light flashes that can be delivered at high frequencies. It has shown promise for studying neural circuits that ar...
Grouped Variable Selection via Nested Spike and Slab Priors
Log-sum approximation Majorization-minimization algorithms
2011/7/6
In this paper we study grouped variable selection problems by proposing a specified prior, called the nested spike and slab prior, to model collective behavior of regression coefficients.
Fast Inference of Interactions in Assemblies of Stochastic Integrate-and-Fire Neurons from Spike Recordings
Bayesian procedures noise variance activity of the salamander
2011/3/24
We present two Bayesian procedures to infer the interactions and external currents in an assembly of stochastic integrate-and-fire neurons from the recording of their spiking activity. The first proce...
Some theoretical results on neural spike train probability models
Boundary crossing probability change of measure conditional intensity countingprocess importance sampling metric entropy
2010/4/27
This article contains two main theoretical results on neural spike train models.
The first assumes that the spike train is modeled as a counting or point process
on the real line where the condition...