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scientificComputing/pointprocesses/code/lifinputdiscriminationtime.m
2014-11-12 18:39:02 +01:00

52 lines
1.3 KiB
Matlab

input = 65.0; % lifadapt 100Hz
%input = 8.0; % lifadapt 10Hz
%input = 15.7; % lif 100Hz
%input = 8.3; % lif 10Hz
trials = 10;
tmax = 50.0;
Dnoise = 0.1;
Dounoise = 5e1;
outau = 10.0;
adapttau = 0.2;
adaptincr = 0.5;
windows = 0.05:0.05:1.0;
pmax = zeros( size( windows ) );
for j = 1:length( windows )
w = windows( j );
spikes = lifadaptspikes( trials, input, tmax, Dnoise, adapttau, adaptincr );
%spikes = lifouspikes( trials, input, tmax, Dounoise, outau);
[ n1, bins1 ] = counthist( spikes, w );
spikes = lifadaptspikes( trials, input+10.0, tmax, Dnoise, adapttau, adaptincr );
%spikes = lifouspikes( trials, input+10.0, tmax, Dounoise, outau );
[ n2, bins2 ] = counthist( spikes, w );
subplot( 2, 1, 1 );
bar( bins1, n1, 'b' );
hold on;
bar( bins2, n2, 'r' );
hold off;
subplot( 2, 1, 2 );
bmax = max( [ length( bins1 ), length( bins2 ) ] );
decision1 = zeros( bmax, 1 );
decision2 = zeros( bmax, 1 );
cs1 = ones( bmax, 1 );
cs1(1:length(n1)) = cumsum( n1 );
cs2 = ones( bmax, 1 );
cs2(1:length(n2)) = cumsum( n2 );
cbins = 0:1:bmax-1;
plot( cbins, cs1, 'b' );
hold on;
plot( cbins, cs2, 'r' );
plot( cbins, cs1-cs2, 'g' );
hold off;
pause( 0.1 );
pmax(j) = max( cs1-cs2 );
end
clf;
subplot( 1, 1, 1 );
plot( windows, pmax );