diff --git a/projects/instructions.tex b/projects/instructions.tex index 1c06bc4..597c844 100644 --- a/projects/instructions.tex +++ b/projects/instructions.tex @@ -1,5 +1,5 @@ \setlength{\fboxsep}{2ex} -\fbox{\parbox{1\linewidth}{ \small +\fbox{\parbox{1\linewidth}{\small {\bf Evaluation criteria:} @@ -48,7 +48,9 @@ and discussing your results, and (iii) explain how you solved the problem algorithmically (don't show your entire code). All data-related figures you show in the presentation should be - produced by your program. It is always a good idea to illustrate - the problem with basic plots of the raw-data. Make sure the axis - labels are large enough! - }} + produced by your program --- no editing or labeling by + PowerPoint or other software. It is always a good idea to + illustrate the problem with basic plots of the raw-data. Make + sure the axis labels are large enough! + +}} diff --git a/projects/project_fano_slope/lifboltzmannspikes.m b/projects/project_fano_slope/lifboltzmannspikes.m index 85ea63e..6da50d8 100644 --- a/projects/project_fano_slope/lifboltzmannspikes.m +++ b/projects/project_fano_slope/lifboltzmannspikes.m @@ -20,7 +20,7 @@ function spikes = lifboltzmannspikes(trials, input, tmax, gain) for k=1:trials times = []; j = 1; - v = vreset; + v = vreset + (vthresh - vreset) * rand(); noise = sqrt(2.0*D)*randn(n, 1)/sqrt(dt); for i=1:n v = v + (- v + noise(i) + inb)*dt/tau; diff --git a/projects/project_fano_slope/solution/fanoslope.m b/projects/project_fano_slope/solution/fanoslope.m index d2bd643..cd0d27d 100644 --- a/projects/project_fano_slope/solution/fanoslope.m +++ b/projects/project_fano_slope/solution/fanoslope.m @@ -76,7 +76,8 @@ plot(false2s, true1s); T = 0.1; gains = 0.01:0.01:1.0; cmax = 100; -ds = zeros(length(gains), 1); +dstt = zeros(length(gains), 1); +dsff = zeros(length(gains), 1); for k = 1:length(gains) gain = gains(k); spikes1 = lifboltzmannspikes(trials, I1, tmax, gain); @@ -84,9 +85,11 @@ for k = 1:length(gains) [c1, b1] = counthist(spikes1, 0.0, tmax, T, cmax); [c2, b2] = counthist(spikes2, 0.0, tmax, T, cmax); [d, thresholds, true1s, false1s, true2s, false2s, pratio] = discriminability(spikes1, spikes2, tmax, T, cmax); - ds(k) = d; + dstt(k) = d; + dsff(k) = min(false1s + false2s); end figure() -plot(gains, ds) - - +plot(gains, dstt); +hold on; +plot(gains, dsff); +hold off; diff --git a/projects/project_fano_slope/solution/lifboltzmannspikes.m b/projects/project_fano_slope/solution/lifboltzmannspikes.m index 85ea63e..6da50d8 100644 --- a/projects/project_fano_slope/solution/lifboltzmannspikes.m +++ b/projects/project_fano_slope/solution/lifboltzmannspikes.m @@ -20,7 +20,7 @@ function spikes = lifboltzmannspikes(trials, input, tmax, gain) for k=1:trials times = []; j = 1; - v = vreset; + v = vreset + (vthresh - vreset) * rand(); noise = sqrt(2.0*D)*randn(n, 1)/sqrt(dt); for i=1:n v = v + (- v + noise(i) + inb)*dt/tau; diff --git a/projects/project_fano_time/lifspikes.m b/projects/project_fano_time/lifspikes.m index c1bec46..c079742 100644 --- a/projects/project_fano_time/lifspikes.m +++ b/projects/project_fano_time/lifspikes.m @@ -19,7 +19,7 @@ function spikes = lifspikes(trials, input, tmax) for k=1:trials times = []; j = 1; - v = vreset + (vthresh-vreset)*rand(1); + v = vreset + (vthresh-vreset)*rand(); noise = sqrt(2.0*D)*randn(n, 1)/sqrt(dt); for i=1:length(noise) v = v + (- v + noise(i) + input)*dt/tau; diff --git a/projects/project_fano_time/solution/lifspikes.m b/projects/project_fano_time/solution/lifspikes.m index c1bec46..c079742 100644 --- a/projects/project_fano_time/solution/lifspikes.m +++ b/projects/project_fano_time/solution/lifspikes.m @@ -19,7 +19,7 @@ function spikes = lifspikes(trials, input, tmax) for k=1:trials times = []; j = 1; - v = vreset + (vthresh-vreset)*rand(1); + v = vreset + (vthresh-vreset)*rand(); noise = sqrt(2.0*D)*randn(n, 1)/sqrt(dt); for i=1:length(noise) v = v + (- v + noise(i) + input)*dt/tau; diff --git a/projects/project_isicorrelations/lifadaptspikes.m b/projects/project_isicorrelations/lifadaptspikes.m index 2ef1874..e2de8fc 100644 --- a/projects/project_isicorrelations/lifadaptspikes.m +++ b/projects/project_isicorrelations/lifadaptspikes.m @@ -32,7 +32,7 @@ function spikes = lifadaptspikes( trials, input, tmaxdt, D, tauadapt, adaptincr for k=1:trials times = []; j = 1; - v = vreset; + v = vreset + (vthresh-vreset)*rand(); a = 0.0; noise = sqrt(2.0*D)*randn( length( input ), 1 )/sqrt(dt); for i=1:length( noise ) diff --git a/projects/project_isipdffit/lifouspikes.m b/projects/project_isipdffit/lifouspikes.m index fc1f5d5..3bff0d0 100644 --- a/projects/project_isipdffit/lifouspikes.m +++ b/projects/project_isipdffit/lifouspikes.m @@ -28,7 +28,7 @@ function spikes = lifouspikes( trials, input, tmaxdt, D, outau ) times = []; j = 1; n = 0.0; - v = vreset; + v = vreset + (vthresh-vreset)*rand(); noise = sqrt(2.0*D)*randn( length( input ), 1 )/sqrt(dt); for i=1:length( noise ) n = n + ( - n + noise(i))*dt/outau; diff --git a/projects/project_isipdffit/pifouspikes.m b/projects/project_isipdffit/pifouspikes.m index b6516cc..f85cfae 100644 --- a/projects/project_isipdffit/pifouspikes.m +++ b/projects/project_isipdffit/pifouspikes.m @@ -28,7 +28,7 @@ function spikes = pifouspikes( trials, input, tmaxdt, D, outau ) times = []; j = 1; n = 0.0; - v = vreset; + v = vreset + (vthresh-vreset)*rand(); noise = sqrt(2.0*D)*randn( length( input ), 1 )/sqrt(dt); for i=1:length( noise ) n = n + ( - n + noise(i))*dt/outau; diff --git a/projects/project_noiseficurves/lifspikes.m b/projects/project_noiseficurves/lifspikes.m index 5c06505..313397f 100644 --- a/projects/project_noiseficurves/lifspikes.m +++ b/projects/project_noiseficurves/lifspikes.m @@ -18,7 +18,7 @@ function spikes = lifspikes(trials, input, tmax, D) for k=1:trials times = []; j = 1; - v = vreset; + v = vreset + (vthresh-vreset)*rand(); noise = sqrt(2.0*D)*randn(n, 1)/sqrt(dt); for i=1:n v = v + (- v + noise(i) + input)*dt/tau; diff --git a/projects/project_noiseficurves/solution/lifspikes.m b/projects/project_noiseficurves/solution/lifspikes.m index 5c06505..313397f 100644 --- a/projects/project_noiseficurves/solution/lifspikes.m +++ b/projects/project_noiseficurves/solution/lifspikes.m @@ -18,7 +18,7 @@ function spikes = lifspikes(trials, input, tmax, D) for k=1:trials times = []; j = 1; - v = vreset; + v = vreset + (vthresh-vreset)*rand(); noise = sqrt(2.0*D)*randn(n, 1)/sqrt(dt); for i=1:n v = v + (- v + noise(i) + input)*dt/tau;