I am trying to model a poisson process. When I histogram the inter-event times, the distribution is exponential. I want to prove that the simulation is Poissonian. How can I calculate the Fano-factor?I have a list of waiting times and spiketimes.

while duration <= Total_time

randNumbers = rand(1,1); IVI = -log(randNumbers)/rate;

SpikeTime = duration + IVI;

duration = duration + IVI; SpikeTimes = [SpikeTimes; SpikeTime];

counter = counter + 1;

IVI_hist(counter,1) = IVI;

end

figure(1) hist(IVI_hist, sqrt(length(IVI_hist)))

Answer 1

[Aditya]

Hi Phil,

I understand that you are trying to calculate the fano factor .

The following script might help you doing the same :

% Assuming SpikeTimes is your list of spike times
Total_time = max(SpikeTimes);  % Use the maximum spike time as total time
binWidth = 1;  % Define the width of each bin (e.g., 1 second)
edges = 0:binWidth:Total_time;  % Define the edges of the bins

% Calculate the number of spikes in each bin
spikeCounts = histcounts(SpikeTimes, edges);

% Calculate the mean and variance of spike counts
meanSpikeCounts = mean(spikeCounts);
varianceSpikeCounts = var(spikeCounts);

% Calculate the Fano factor
FanoFactor = varianceSpikeCounts / meanSpikeCounts;

% Display the Fano factor
fprintf('Fano Factor: %.2f\n', FanoFactor);