Simulating leaky integrate and fire neuron with integers
The leaky integrate and fire (LIF) neuron represents standard neuronal model used for numerical simulations. The leakage is implemented in the model as exponential decay of trans-membrane voltage towards its resting value. This makes inevitable the usage of machine floating point numbers in the course of simulation. It is known that machine floating point arithmetic is subjected to small inaccuracies, which prevent from exact comparison of floating point quantities. In particular, it is incorrect to decide whether two separate in time states of a simulated system composed of LIF neurons are exactly identical. However, decision of this type is necessary, e.g. to figure periodic dynamical regimes in a reverberating network. Here we offer a simulation paradigm of a LIF neuron, in which neuronal states are described by whole numbers. Within this paradigm, the LIF neuron behaves exactly the same way as does the standard floating point simulated LIF, although exact comparison of states becomes correctly defined.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Output stream of leaky integrate and fire neuron
Probability density function of output interspike intervals is found in exact form for leaky integrate and fire neuron stimulated with Poisson stream. The diffusion approximation is not exploited.
FormLeaky Integrate-and-Fire Neuron under Poisson Stimulation
We consider a single Leaky integrate-and-fire neuron stimulated with Poisson process. We develop a method, which allows one to obtain the first passage time probability density function without any additional approximati…
Hardware design of LIF with Latency neuron model with memristive STDP synapses
In this paper, the hardware implementation of a neuromorphic system is presented. This system is composed of a Leaky Integrate-and-Fire with Latency (LIFL) neuron and a Spike-Timing Dependent Plasticity (STDP) synapse. L…
Firing rate of the leaky integrate-and-fire neuron with stochastic conductance-based synaptic inputs with short decay times
We compute the firing rate of a leaky integrate-and-fire (LIF) neuron with stochastic conductance-based inputs in the limit when synaptic decay times are much shorter than the membrane time constant. A comparison of our …
A synchronization-capturing multi-scale solver to the noisy integrate-and-fire neuron networks
The noisy leaky integrate-and-fire (NLIF) model describes the voltage configurations of neuron networks with an interacting many-particles system at a microscopic level. When simulating neuron networks of large sizes, co…