function [cnt, pd] = poisscnt(mrate,interval,maxcount)
% poisscnt: function which returns the probability density for the
% distribution of the spike count of a Poisson process in a fixed time
% interval. If called without output arguments, the probability
% distribution is plotted.
%
% [cnt, pd] = poisscnt(mrate,interval,maxcount)
%
% where
% mrate = mean rate of the Poisson process [Hz]
% interval = the length of the interval (in msec)
% maxcount = maximal count taken into account
%
% The return parameters are:
% cnt = vector of spike counts.
% pd = corresponding probability distribution.
%
% For an I&F neuron with exponentially distributed threshold under
% constant current injection, the mean rate is given by I/CVthres.
%
%
if ( nargin ~= 3 )
disp(‘ ‘);
disp(‘usage: poisscnt(mrate,interval,maxcount) ‘);
disp(‘ for more information type “help poisscnt” in the main’);
disp(‘ matlab window’);
disp(‘ ‘);
return;
end;
%initializes the various variables
lambda = mrate*interval*1e-3;
cnt = (0:1:maxcount)’;
pd = zeros(maxcount+1,1);
pd(1) = exp(-lambda);
for k = 2:maxcount+1
pd(k) = lambda/cnt(k)*pd(k-1);
end;
if ( nargout == 0 )
%looks for the figure ‘countprob’, otherwise creates it
%and sets it to current
fig_name = ‘countprob’;
Figures = get(0,’Chil’);
new_fig = 1;
for i=1:length(Figures)
if strcmp(get(Figures(i),’Type’),’figure’)
if strcmp(get(Figures(i),’Name’),fig_name)
new_fig = 0;
h_fig = Figures(i);
set(0,’CurrentFigure’,h_fig);
end;
end;
end;
if (new_fig == 1)
h_fig = figure(‘Name’,fig_name);
end;
%sets decorations and plots the isi distribution
plot(cnt,pd,’g–‘);
titt = sprintf(‘Spike count distribution for an interval of %g
[msec]’,…
interval);
title(titt);
xlabel(‘spike count’);
ylabel(‘probability’);
clear cnt, pd;
end;