A neuron with a large dendritic structure is considered. The number of synapses located on
the dendrites is substantially higher than on the soma. The synaptic input effect on the …

In this paper, two degradation models are developed in terms of degradation signals of
systems with some Wiener diffusion processes under pre-specified periodical calibrations …

Spike trains from neurons are often used to make inferences about the underlying processes
that generate the spikes. Random walks or diffusions are commonly used to model these …

Nonparametric Bayesian methods for one-dimensional diffusion models - ScienceDirect Skip
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Abstract For the Ornstein-Uhlenbeck neuronal model a quantitative method is proposed for
the estimation of the two parameters characterizing the unkown input process, namely the …

In terms of a single neuron's long-distance communication, interpulse intervals (IPIs) are an
attractive alternative to rate and binary codes. As a proxy for an IPI, a neuron's time-to-spike …

Abstract Micro-Tissue Engineered Neural Networks (Micro-TENNs) are living three-
dimensional constructs designed to replicate the neuroanatomy of white matter pathways in …

In stochastic neuronal models, an interspike interval corresponds to the time interval during
which the process imitating the membrane potential reaches a threshold from an initial …

Stochastic models of neural activity are a well developed application in biology. Diffusion
models hold a prominent place because of the many synaptic inputs to a neuron, and …

This paper examines a one dimensional stochastic differential equation model for the
membrane potential in a neuron with synaptic reversal potentials and random postsynaptic …