5 research outputs found
Spiking Activity of a LIF Neuron in Distributed Delay Framework
Evolution of membrane potential and spiking
activity for a single leaky integrate-and-fire (LIF) neuron in
distributed delay framework (DDF) is investigated. DDF provides
a mechanism to incorporate memory element in terms of delay
(kernel) function into a single neuron models. This investigation
includes LIF neuron model with two different kinds of delay kernel
functions, namely, gamma distributed delay kernel function and
hypo-exponential distributed delay kernel function. Evolution
of membrane potential for considered models is studied in terms
of stationary state probability distribution (SPD). Stationary
state probability distribution of membrane potential (SPDV)
for considered neuron models are found asymptotically similar
which is Gaussian distributed. In order to investigate the effect
of membrane potential delay, rate code scheme for neuronal
information processing is applied. Firing rate and Fano-factor
for considered neuron models are calculated and standard LIF
model is used for comparative study. It is noticed that distributed
delay increases the spiking activity of a neuron. Increase in
spiking activity of neuron in DDF is larger for hypo-exponential
distributed delay function than gamma distributed delay function.
Moreover, in case of hypo-exponential delay function, a LIF neuron
generates spikes with Fano-factor less than 1
Temporal Information Processing and Stability Analysis of the MHSN Neuron Model in DDF
Implementation of a neuron like information processing structure at hardware level is a burning research problem. In this article, we analyze the modified hybrid spiking neuron model (the MHSN model) in distributed delay framework (DDF) for hardware level implementation point of view. We investigate its temporal information processing capability in term of inter-spike-interval (ISI) distribution. We also perform the stability analysis of the MHSN model, in which, we compute nullclines, steady state solution, eigenvalues corresponding the MHSN model. During phase plane analysis, we notice that the MHSN model generates limit cycle oscillations which is an important phenomenon in many biological processes. Qualitative behavior of these limit cycle does not changes due to the variation in applied input stimulus, however, delay effect the spiking activity and duration of cycle get altered
Spiking Activity of a LIF Neuron in Distributed Delay Framework
Evolution of membrane potential and spiking activity for a single leaky integrate-and-fire (LIF) neuron in distributed delay framework (DDF) is investigated. DDF provides a mechanism to incorporate memory element in terms of delay (kernel) function into a single neuron models. This investigation includes LIF neuron model with two different kinds of delay kernel functions, namely, gamma distributed delay kernel function and hypo-exponential distributed delay kernel function. Evolution of membrane potential for considered models is studied in terms of stationary state probability distribution (SPD). Stationary state probability distribution of membrane potential (SPDV) for considered neuron models are found asymptotically similar which is Gaussian distributed. In order to investigate the effect of membrane potential delay, rate code scheme for neuronal information processing is applied. Firing rate and Fano-factor for considered neuron models are calculated and standard LIF model is used for comparative study. It is noticed that distributed delay increases the spiking activity of a neuron. Increase in spiking activity of neuron in DDF is larger for hypo-exponential distributed delay function than gamma distributed delay function. Moreover, in case of hypo-exponential delay function, a LIF neuron generates spikes with Fano-factor less than 1
Spiking Activity of a LIF Neuron in Distributed Delay Framework
Evolution of membrane potential and spiking activity for a single leaky integrate-and-fire (LIF) neuron in distributed delay framework (DDF) is investigated. DDF provides a mechanism to incorporate memory element in terms of delay (kernel) function into a single neuron models. This investigation includes LIF neuron model with two different kinds of delay kernel functions, namely, gamma distributed delay kernel function and hypo-exponential distributed delay kernel function. Evolution of membrane potential for considered models is studied in terms of stationary state probability distribution (SPD). Stationary state probability distribution of membrane potential (SPDV) for considered neuron models are found asymptotically similar which is Gaussian distributed. In order to investigate the effect of membrane potential delay, rate code scheme for neuronal information processing is applied. Firing rate and Fano-factor for considered neuron models are calculated and standard LIF model is used for comparative study. It is noticed that distributed delay increases the spiking activity of a neuron. Increase in spiking activity of neuron in DDF is larger for hypo-exponential distributed delay function than gamma distributed delay function. Moreover, in case of hypo-exponential delay function, a LIF neuron generates spikes with Fano-factor less than 1