SPNet++: Variable Time Step

The first modification to make to implement the new model using existing SPNet++ code was to enable variable timestep, as the existing code only supported one time step (1ms) and the new model required 0.1ms time step for fast spiking (FS) neurons.

After I finished making changes and run the code for the first time the firing rate (number of spikes per neuron per second) dropped from ~7 to almost zero. After spending few minutes looking at the data I realized that by changing the time step from 1ms to 0.1ms I effectively reduced the time that input current influences the neuron and it was not enough to excite it. After a brief search on the Internet I found a paper that describes duration of spikes for excitatory and inhibitory neurons. Based on the data provided in the paper I made the input current to decay; and after applying this logic to synaptic and random thalamic input I almost got the numbers I expected.

Almost, but not quite. I ended up changing the logic that handles synaptic delays as it expected to work with delays expressed in ms and I needed delays to vary depending on the time step.

I also modified the generator of random integers from (rand()%(int)(max1)) to (int(((double)rand())/((double)(RAND_MAX)+1)*(max1))). According to the author of this page this can make a difference, depending on the type of the random number generator used.

Here is the current version of the source code and here is the diagram of the spikes it produces. It shows all spikes during the 50th second of the simulation for 1000 neurons (the top part of the picture shows inhibitory neurons):

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