[pointprocesses] finished solution of first exercise

pointprocesses/exercises/fanoplots.m

@@ -1,9 +1,9 @@
 spikes{1} = poissonspikes;
 spikes{2} = pifouspikes;
 spikes{3} = lifadaptspikes;
-idents = {'poisson', 'pifou', 'lifadapt'};
+titles = {'poisson', 'pifou', 'lifadapt'};
 for k = 1:3
     figure(k)
     fanoplot(spikes{k}, titles{k});
-    savefigpdf(gcf, sprintf('fanoplots%s.pdf', idents{k}), 20, 7);
+    savefigpdf(gcf, sprintf('fanoplots%s.pdf', titles{k}), 20, 7);
 end

pointprocesses/exercises/plotisihs.m

@@ -1,19 +1,20 @@
 maxisi = 300.0;
 subplot(1, 3, 1);
+dt = 0.005;    % bin width for ISIH in seconds
 poissonisis = isis(poissonspikes);
-plotisihist(poissonisis, 0.001);
+plotisihist(poissonisis, dt);
 xlim([0, maxisi])
 title('Poisson');
 
 subplot(1, 3, 2);
 pifouisis = isis(pifouspikes);
-plotisihist(pifouisis, 0.001);
+plotisihist(pifouisis, dt);
 xlim([0, maxisi])
 title('PIF OU');
 
 subplot(1, 3, 3);
 lifadaptisis = isis(lifadaptspikes);
-plotisihist(lifadaptisis, 0.001);
+plotisihist(lifadaptisis, dt);
 xlim([0, maxisi])
 title('LIF adapt');
 savefigpdf(gcf, 'isihist.pdf', 20, 7);

pointprocesses/exercises/plotpoissonisih.m

@@ -1,12 +1,13 @@
 maxisi = 300.0;
+dt = 0.005;
 poissonisis = isis(poissonspikes);
 rate = 1.0/mean(poissonisis);
-plotisihist(poissonisis, 0.001);
+plotisihist(poissonisis, dt);
 tt = linspace(0.0, 0.001*maxisi, 200);
 pexp = rate*exp(-tt*rate);
 hold on;
-plot(1000.0*tt, pexp, 'r')
+plot(1000.0*tt, pexp, 'r', 'linewidth', 4)
 hold off;
 xlim([0, maxisi])
 title('Poisson');
-savefigpdf(gcf, 'poissonisihist.pdf', 10, 7);
+savefigpdf(gcf, 'poissonisihist.pdf', 10, 6);

pointprocesses/exercises/plotspikeraster.m

@@ -1,3 +1,11 @@
+x = load('poisson.mat');
+poissonspikes = x.spikes;
+x = load('pifou.mat');
+pifouspikes = x.spikes;
+x = load('lifadapt.mat');
+lifadaptspikes = x.spikes;
+clear x;
+
 subplot(1, 3, 1);
 rasterplot(poissonspikes, 1.0);
 title('Poisson');

pointprocesses/exercises/pointprocesses-1.tex

@@ -35,8 +35,8 @@
     How do you access single spike times?
     \begin{solution}
       \begin{lstlisting}
-        clear all
         % not so good:
+        clear all
         load poisson.mat
         whos
         poissonspikes = spikes;
@@ -55,6 +55,15 @@
         lifadaptspikes = x.spikes;
         clear x;
       \end{lstlisting}
+      The files contain cell arrays with 20 trials of spike
+      trains. Each spike train is a vector containing the times of
+      spikes.
+      \begin{lstlisting}
+        % access first trial:
+        trial = poissonspikes{1};
+        % access second spike of first trial:
+        trial(2);
+      \end{lstlisting}
     \end{solution}
 
     \newsolutionpage    
@@ -112,11 +121,11 @@
     of the mean interspike interval.
     \begin{solution}
       \lstinputlisting{plotpoissonisih.m}
-      %\mbox{}\\[-3ex]
-      %\colorbox{white}{\includegraphics[width=1\textwidth]{poissonisihist}}
+      \mbox{}\\[-3ex]
+      \colorbox{white}{\includegraphics{poissonisihist}}
     \end{solution}
-  
-  \continuepage
+    
+    \continue
     % XXX Add return map!!! XXX
     \part Write a function that computes the serial correlations of
     interspike intervals for lags up to \code{maxlag}. The serial

pointprocesses/exercises/rasterplot.m

@@ -6,7 +6,7 @@ function rasterplot(spikes, tmax)
 % Arguments:
 %   spikes: a cell array of vectors of spike times in seconds
 %   tmax: plot spike raster up to tmax seconds
-    in_msecs = tmax < 1.5
+    in_msecs = tmax < 1.5;
     spiketimes = [];
     trials = [];
     ntrials = length(spikes);