The Leaky Integrate and Fire Neuron Model
The Leaky Integrate-and-Fire Neuron Model
... )] (2) It is easy to understand the behavior of this solution. The asymptotic value of the membrane potential is RI. If this value is less than the spiking threshold, v th , no spike can be generated. If, however, RI > v ...
6
Effects caused on Leaky integrate and fire model
... Keywords— leaky integrate and fire model, t stop, computational neuroscience, spiking patterns, variations in ...the neuron state in integrate and fire neuron ...
7
Bistability in a Leaky Integrate-and-Fire Neuron with a Passive Dendrite
... ball-and-stick model when considering dependence of the firing dynamics on ...LIF neuron that explicitly includes a spike. We model the dendrite as either a passive cable using the cable equation (a ...
33
The Performance (and Limits) of Simple Neuron Models: Generalizations of the Leaky Integrate-and-Fire Model
... fixed point which is sitting at the intersection between te V - and the w-nullcline. Af- ter the step, the stable fixed point has disappeared and this results in repetitive firing. The distinction between an initially ...
31
A Semi-Markov Leaky Integrate-and-Fire model
... The model we study in this paper is a modification of the one introduced in [10] and face the two issues ...our model with the popular Unit 240-1, studied for instance in ...
24
Rate dynamics of leaky integrate-and-fire neurons with strong synapses
... of leaky integrate-and-fire neurons receiving input spikes through excitatory synapses with alpha-function shaped postsynaptic currents for strong synaptic ...linear–nonlinear model accurately ...
13
Collective irregular dynamics in balanced networks of leaky integrate-and-fire neurons
... sending neuron j is excitatory, it may happen that the post-synaptic potentials triggers several threshold passings events at exactly the same ...the model with a rule to handle perfectly synchronous ...
20
Responses of Leaky Integrate-and-Fire Neurons to a Plurality of Stimuli in Their Receptive Fields
... probability-mixing model, and another data set consisting of 10 spike trains following the response-averaging ...probability-mixing model and the response-averaging model on both data sets, resulting ...
33
Detectability of Excitatory versus Inhibitory Drive in an Integrate-and-Fire-or-Burst Thalamocortical Relay Neuron Model
... A number of criteria to distinguish drivers from modulators for thalamic relays have been suggested; for example, cross- correlograms from driver inputs are likely to be sharply peaked compared with those from modulatory ...
9
Associative memory of phase-coded spatiotemporal patterns in leaky Integrate and Fire networks
... a Leaky Integrate and Fire network in which precise relative phase relationship of spikes among neurons are stored, as attractors of the dynamics, and selectively replayed at different time ...
18
Fokker–Planck and Fortet Equation-Based Parameter Estimation for a Leaky Integrate-and-Fire Model with Sinusoidal and Stochastic Forcing
... In this paper, we thus describe and discuss two methods to estimate parameters of LIF models with the added complexity of a time-varying input current. We assume that the time-varying current is a sinusoidal wave, but we ...
30
Analysis of nonlinear noisy integrate & fire neuron models: blow-up and steady states
... the model since the firing rate diverges for a fixed time creating possibly a strong par- tial synchronization, that is, a part of the network firing at the same ...simple model encodes complicated ...
33
An integrate-and-fire model to generate spike trains with long-range dependence
... a model yields stationary spike trains, multiple simulations can be ...same model and a boxplot of the p-values was ...a model which produces stationary ISIs, p-values must be uni- formly distributed ...
18
Equivalence of phase-oscillator and integrate-and-fire models
... Kuramoto-Sakaguchi model [11] (sine coupling with a phase shift) but only for a particular value of the phase shift, when it is marginally ...This model can be obtained as a phase approximation of ...
11
First passage times in integrate and fire neurons with stochastic thresholds
... ‘renewal’ model in which the threshold is reset to a con- stant value after firing, but an alternative procedure is to set it to a value selected from the statistical distri- bution of the ...
8
Fundamental Limits of Forced Asynchronous Spiking with Integrate and Fire Dynamics
... Clearly, our results here are of theoretical nature. Although the control-theoretic features revealed are themselves interesting from a mathematical standpoint, they serve the broader purpose of establishing fundamental ...
37
A Simple Mechanism for Beyond-Pairwise Correlations in Integrate-and-Fire Neurons
... of integrate-and-fire ...stochastic model of neural spiking, the linear–nonlinear ...by integrate- and-fire and dichotomous Gaussian models, and show that the latter is a surprisingly ...
13
Spike trains statistics in integrate and fire models: exact results.
... source at http://enas.gforge.inria.fr. 9 Discussion In this paper we have addressed the question of character- izing the spike trains statistics of a network of LIF neurons with noise, in the stationary case, with two ...
7
The chronotron: a neuron that learns to fire temporally-precise spike patterns
... train integrate-and-fire neu- ...to fire spikes at the desired timings, with sub-millisecond ...can model neurons in oscillatory networks that encode information in the phases of spikes ...
58
Linearization of the Morris-Lecar Neuron Model
... linearized model failed to capture the non-linear aspects of the action potential, it may accurately characterize membrane dynamics in all times preceeding an action potential and following the membrane’s minima ...
12