Reduction of the Number of Synapses
Posted: Fri Jan 16, 2015 7:57 am
I built a model of a neuron and want to stimulate it with synapses. Usually one neuron in the brain is stimulated with thousands of synapses. I was trying to think of a way to reduce this number in my simulations in order to reduce computation time. My idea was the following:
1. Compute spike trains for every synapse.
2. Compute the conductance of each time step per synapse (before simulation). Using e.g. G = weight * factor * (exp(-t/tau2) - exp(-t/tau1))
3. Adding the conductances.
4. Calculate the current during the simulation using a point process with the formula: i = G * (v - e).
My questions are:
Firstly whether there are better approaches to reduce the number of synapses. (For instance one could also use less synapses and increase the frequency, but this leads to saturation which is not there when several synapses are used.)
Secondly if my proposal is reasonable and how step 4 could be implemented in Neuron (maybe making a point process which receives the conductances via netcon in the net receive block.)
1. Compute spike trains for every synapse.
2. Compute the conductance of each time step per synapse (before simulation). Using e.g. G = weight * factor * (exp(-t/tau2) - exp(-t/tau1))
3. Adding the conductances.
4. Calculate the current during the simulation using a point process with the formula: i = G * (v - e).
My questions are:
Firstly whether there are better approaches to reduce the number of synapses. (For instance one could also use less synapses and increase the frequency, but this leads to saturation which is not there when several synapses are used.)
Secondly if my proposal is reasonable and how step 4 could be implemented in Neuron (maybe making a point process which receives the conductances via netcon in the net receive block.)