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Tutorial objectives # estimated timing of tutorial It's leaky because of leak conductance gl = 1 dissipates the rm membrane potential over time. 1 hour, 10 min this is tutorial 1 of a series on implementing realistic neuron models
Leaky integrate and fire model
In particular, we are going to write a few lines of code to It integrates because the membrane voltage sums (integrates) over input currents Simulate the lif neuron model drive the lif neuron.
Learn the fundamentals of the lif neuron model, a simple spiking neuron model that integrates input over time with a leakage
Use snntorch to implement a first order lif neuron and explore its dynamics and applications. Learn how to model the membrane potential of a neuron as a function of input current using a simple rc circuit The essence of the model is to divide the voltage changes of the neuron into two parts Below threshold, it is assumed that the membrane behaves passively (i.e
I closely follow chapter 4.1 of gerstner and kistler (2002) I consider three different stimulation conditions below and show how each condition can be implemented in the brian spiking neural network simulator for python (goodman & brette, 2008). The basic idea of lif neuron was proposed in 1907 by louis édouard lapicque, long before we understood the electrophysiology of a neuron [see a translation of lapicque's paper link text]. Now add a 'fire' by hand when vmreaches a threshold, vththen reset to vresetand wait a short refractory time, τrefbefore further integration
Vreset vth vm t i app what is the firing rate, f(i)
