I’m running the tutorial 2 of W1D1 and I’ve got some technical problems over the LIF neuron model.

In the tutorial, we first only implemented the excitation part of the LIF neuron model which causes a central distribution like Gaussian distribution, but I am confused why it causes such a distribution rather than an exponential one? What’s the intuition?

Another question is about the leaky part and the inhibition part of the LIF neuron model. Whether the former or the latter changes the central distribution into a distribution similar to exponential distribution?

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For your first question, I think it is not a Guassian distribution but a Poisson ditribution whose lambda equals 1/(alpha* rate). In fact you might observe the asymmetry of the distribution after tuning alpha to 0.04.

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