Input Identification in the Ornstein-Uhlenbeck Neuronal Model with Signal Dependent Noise
نویسندگان
چکیده
The stochastic leaky integrate-and-fire (LIF) continuous model is studied under the condition that the amplitude of noise is a function of the input signal. The coefficient of variation (CV) of interspike intervals (ISIs) is investigated for different types of dependencies between the noise and the signal. Finally, we present the CV and the ISI density resulting from the special choice of parameters of the input that gave rise to a contra-intuitive behavior of the transfer function in Lánský and Sacerdote [Phys. Lett. A 285 (2001) 132].
منابع مشابه
Convergence of Passive Scalars in Ornstein-uhlenbeck Flows to Kraichnan’s Model
We prove that the passive scalar field in the Ornstein-Uhlenbeck velocity field with wave-number dependent correlation times converges, in the white-noise limit, to that of Kraichnan’s model with higher spatial regularity.
متن کاملSignal Selection Based on Stochastic Resonance
Noise aids the encoding of continuous signals into pulse sequences by way of stochastic resonance and endows the encoding device with a preferred frequency. We study encoding by a threshold device based on the Ornstein-Uhlenbeck process, equivalent to the leaky integrate-and-fire neuron model. Preferred frequency, optimum noise intensity, and optimum signal-to-noise ratio are shown to be linear...
متن کاملOn Filtering with Ornstein-Uhlenbeck Process as Noise
We consider the nonlinear filtering model with Ornstein-Uhlenbeck process as noise and obtain an analogue of the Bayes’ formula for the filter. For this we need to consider a modified model, where the instaneteneous effect h(Xt) of the signal in the usual model is replaced by ξ t = α ∫ t (t− 1 α )∨0 h(Xu) du, (where α is a large parameter). This means that there is a lingering effect of the sig...
متن کاملOn some computational results for single neurons' activity modeling.
The classical Ornstein-Uhlenbeck diffusion neuronal model is generalized by inclusion of a time-dependent input whose strength exponentially decreases in time. The behavior of the membrane potential is consequently seen to be modeled by a process whose mean and covariance classify, it as Gaussian-Markov. The effect of the input on the neuron's firing characteristics is investigated by comparing...
متن کاملSpatial neuron model with two-parameter Ornstein–Uhlenbeck input current
We consider a new and extended spatial neuron model in which the neuronal electrical depolarization from resting level satisfies a cable partial differential equation. The synaptic input current is also a function of space and time and satisfies a first order linear partial differential equation driven by a two-parameter random process. A natural choice for these random input processes is to ma...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Bio Systems
دوره 67 1-3 شماره
صفحات -
تاریخ انتشار 2002