fixed exercise 01 of point processes

pointprocesses/code/isiserialcorr.m

@@ -26,7 +26,7 @@ function isicorr = isiserialcorr(isivec, maxlag)
         % plot:
         plot(lags, isicorr, '-b');
         hold on;
-        scatter(lags, isicorr, 100.0, 'b', 'filled');
+        scatter(lags, isicorr, 10.0, 'b', 'filled');
         hold off;
         xlabel('Lag k')
         ylabel('\rho_k')

pointprocesses/code/plotisihist.m

@@ -1,7 +1,7 @@
-function plotISIHist(isis, binwidth)
+function plotisihist(isis, binwidth)
 % Plot and annotate histogram of interspike intervals.
 %
-% plotISIHist(isis, binwidth)
+% plotisihist(isis, binwidth)
 %
 % Arguments:
 %   isis: vector of interspike intervals in seconds
@@ -9,9 +9,9 @@ function plotISIHist(isis, binwidth)
 
     % compute normalized histogram:
     if nargin < 2
-        [pdf, centers] = isiHist(isis);
+        [pdf, centers] = isihist(isis);
     else
-        [pdf, centers] = isiHist(isis, binwidth);
+        [pdf, centers] = isihist(isis, binwidth);
     end
 
     % plot:
@@ -21,14 +21,11 @@ function plotISIHist(isis, binwidth)
     % annotation:
     misi = mean(isis);
     sdisi = std(isis);
-    disi = sdisi^2.0/2.0/misi^3;
     text(0.95, 0.8, sprintf('mean=%.1f ms', 1000.0*misi), ...
          'Units', 'normalized', 'HorizontalAlignment', 'right')
     text(0.95, 0.7, sprintf('std=%.1f ms', 1000.0*sdisi), ...
          'Units', 'normalized', 'HorizontalAlignment', 'right')
     text(0.95, 0.6, sprintf('CV=%.2f', sdisi/misi), ...
          'Units', 'normalized', 'HorizontalAlignment', 'right')
-    %text(0.95, 0.5, sprintf('D=%.1f Hz', disi), ...
-    %    'Units', 'normalized', 'HorizontalAlignment', 'right')
 end
 

pointprocesses/code/plotisihs.m

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

pointprocesses/exercises/instructions.tex

@@ -1,11 +1,6 @@
-\vspace*{-6.5ex}
+\vspace*{-7.8ex}
 \begin{center}
-\textbf{\Large Einf\"uhrung in die wissenschaftliche Datenverarbeitung}\\[1ex]
+\textbf{\Large Introduction to Scientific Computing}\\[2.3ex]
 {\large Jan Grewe, Jan Benda}\\[-3ex]
-Abteilung Neuroethologie \hfill --- \hfill Institut f\"ur Neurobiologie \hfill --- \hfill \includegraphics[width=0.28\textwidth]{UT_WBMW_Black_RGB} \\
+Neuroethology Lab \hfill --- \hfill Institute for Neurobiology \hfill --- \hfill \includegraphics[width=0.28\textwidth]{UT_WBMW_Black_RGB} \\
 \end{center}
-
-\ifprintanswers%
-\else
-
-\fi

pointprocesses/exercises/pointprocesses01-de.tex

@@ -0,0 +1,198 @@
+\documentclass[12pt,a4paper,pdftex]{exam}
+
+\usepackage[german]{babel}
+\usepackage{pslatex}
+\usepackage[mediumspace,mediumqspace,Gray]{SIunits}      % \ohm, \micro
+\usepackage{xcolor}
+\usepackage{graphicx}
+\usepackage[breaklinks=true,bookmarks=true,bookmarksopen=true,pdfpagemode=UseNone,pdfstartview=FitH,colorlinks=true,citecolor=blue]{hyperref}
+
+%%%%% layout %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+\usepackage[left=20mm,right=20mm,top=25mm,bottom=25mm]{geometry}
+\pagestyle{headandfoot}
+\ifprintanswers
+\newcommand{\stitle}{L\"osungen}
+\else
+\newcommand{\stitle}{\"Ubung}
+\fi
+\header{{\bfseries\large \stitle}}{{\bfseries\large Punktprozesse}}{{\bfseries\large 27. Oktober, 2015}}
+\firstpagefooter{Prof. Dr. Jan Benda}{Phone: 29 74573}{Email:
+jan.benda@uni-tuebingen.de}
+\runningfooter{}{\thepage}{}
+
+\setlength{\baselineskip}{15pt}
+\setlength{\parindent}{0.0cm}
+\setlength{\parskip}{0.3cm}
+\renewcommand{\baselinestretch}{1.15}
+
+%%%%% listings %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+\usepackage{listings}
+\lstset{
+  language=Matlab,
+  basicstyle=\ttfamily\footnotesize,
+  numbers=left,
+  numberstyle=\tiny,
+  title=\lstname,
+  showstringspaces=false,
+  commentstyle=\itshape\color{darkgray},
+  breaklines=true,
+  breakautoindent=true,
+  columns=flexible,
+  frame=single,
+  xleftmargin=1em,
+  xrightmargin=1em,
+  aboveskip=10pt
+}
+
+%%%%% math stuff: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+\usepackage{amsmath}
+\usepackage{amssymb}
+\usepackage{bm} 
+\usepackage{dsfont}
+\newcommand{\naZ}{\mathds{N}}
+\newcommand{\gaZ}{\mathds{Z}}
+\newcommand{\raZ}{\mathds{Q}}
+\newcommand{\reZ}{\mathds{R}}
+\newcommand{\reZp}{\mathds{R^+}}
+\newcommand{\reZpN}{\mathds{R^+_0}}
+\newcommand{\koZ}{\mathds{C}}
+
+%%%%% page breaks %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+\newcommand{\continue}{\ifprintanswers%
+\else
+\vfill\hspace*{\fill}$\rightarrow$\newpage%
+\fi}
+\newcommand{\continuepage}{\ifprintanswers%
+\newpage
+\else
+\vfill\hspace*{\fill}$\rightarrow$\newpage%
+\fi}
+\newcommand{\newsolutionpage}{\ifprintanswers%
+\newpage%
+\else
+\fi}
+
+%%%%% new commands %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+\newcommand{\qt}[1]{\textbf{#1}\\}
+\newcommand{\pref}[1]{(\ref{#1})}
+\newcommand{\extra}{--- Zusatzaufgabe ---\ \mbox{}}
+\newcommand{\code}[1]{\texttt{#1}}
+
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+\begin{document}
+
+\input{instructions}
+
+
+\begin{questions}
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+  \question \qt{Statistik von Spiketrains}
+  In Ilias findet ihr die Dateien \code{poisson.mat},
+  \code{pifou.mat}, und \code{lifadapt.mat}.  Jede dieser Dateien
+  enth\"alt mehrere Trials von Spiketrains von einer bestimmten Art
+  von Neuron. Die Spikezeiten sind in Sekunden gemessen.
+
+  Mit den folgenden Aufgaben wollen wir die Statistik der Spiketrains
+  der drei Neurone miteinander vergleichen.
+  \begin{parts}
+    \part Lade die Spiketrains aus den drei Dateien. Achte darauf,
+    dass sie verschiedene Variablen\-namen bekommen.
+    \begin{solution}
+      \begin{lstlisting}
+        clear all
+        % not so good:
+        load poisson.mat
+        whos
+        poissonspikes = spikes;
+        load pifou.mat;
+        pifouspikes = spikes;
+        load lifadapt.mat;
+        lifadaptspikes = spikes;
+        clear spikes;
+        % better:
+        clear all
+        x = load( 'poisson.mat' );
+        poissonspikes = x.spikes;
+        x = load( pifou.mat' );
+        pifouspikes = x.spikes;
+        x = load( 'lifadapt.mat' );
+        lifadaptspikes = x.spikes;
+      \end{lstlisting}
+    \end{solution}
+    
+    \part Schreibe eine Funktion, die die Spikezeiten der ersten
+    $t_{max}$ Sekunden in einem Rasterplot visualisiert.  In jeder
+    Zeile des Rasterplots wird ein Spiketrain dargestellt. Jeder
+    einzelne Spike wird als senkrechte Linie zu der Zeit des
+    Auftretens des Spikes geplottet. Benutze die Funktion, um die
+    Spikeraster der ersten 1\,s der drei Neurone nebeneinander zu plotten.
+    \begin{solution}
+      \lstinputlisting{../code/spikeraster.m}
+      \lstinputlisting{../code/plotspikeraster.m}
+      \mbox{}\\[-3ex]
+      \colorbox{white}{\includegraphics[width=1\textwidth]{spikeraster}}
+    \end{solution}
+  
+    \part Schreibe eine Funktion, die einen einzigen Vektor mit den
+    Interspikeintervallen aller Trials von Spikezeiten zur\"uckgibt.
+    \begin{solution}
+      \lstinputlisting{../code/isis.m}
+    \end{solution}
+    
+    \part Schreibe eine Funktion, die ein normiertes Histogramm aus
+    einem Vektor von Interspikeintervallen, gegeben in Sekunden,
+    berechnet und dieses mit richtiger Achsenbeschriftung plottet.
+    Die Interspikeintervalle sollen dabei in Millisekunden angegeben
+    werden. Die Funktion soll zus\"atzlich den Mittelwert, die
+    Standardabweichung, und den Variationskoeffizienten der
+    Interspikeintervalle berechnen und diese im Plot mit angeben.
+    
+    Benutze die vorherige und diese Funktion, um die
+    Interspikeintervall Verteilung der drei Neurone zu vergleichen.
+    \begin{solution}
+      \lstinputlisting{../code/isihist.m}
+      \lstinputlisting{../code/plotisih.m}
+      \mbox{}\\[-3ex]
+      \colorbox{white}{\includegraphics[width=1\textwidth]{isihist}}
+    \end{solution}
+  
+    \part Schreibe eine Funktion, die die seriellen Korrelationen der
+    Interspikeintervalle f\"ur Lags bis zu \code{maxlag} berechnet und
+    plottet.  Die Seriellen Korrelationen $\rho_k$ f\"ur Lag $k$ der
+    Interspikeintervalle $T_i$ sind die Korrelationskoeffizienten
+    zwischen den Interspikeintervallen $T_i$ und den um das Lag $k$
+    verschobenen Intervallen $T_{i+k}$:
+    \[ \rho_k = \frac{\langle (T_{i+k} - \langle T \rangle)(T_i -
+      \langle T \rangle) \rangle}{\langle (T_i - \langle T
+      \rangle)^2\rangle} = \frac{{\rm cov}(T_{i+k}, T_i)}{{\rm
+        var}(T_i)} = {\rm corr}(T_{i+k}, T_i) \] 
+
+    Benutze diese Funktion, um die Interspikeintervall-Korrelationen
+    der drei Neurone zu vergleichen.
+    \begin{solution}
+      \lstinputlisting{../code/isiserialcorr.m}
+      \lstinputlisting{../code/plotserialcorr.m}
+      \colorbox{white}{\includegraphics[width=1\textwidth]{serialcorr}}
+    \end{solution}
+  
+    \part Schreibe eine Funktion, die aus Spikezeiten
+    Histogramme aus der Anzahl von Spikes, die in Fenstern gegebener L\"ange $W$
+    gez\"ahlt werden, erzeugt und plottet.
+
+    Wende diese Funktion auf die drei
+    Datens\"atze an. Probiere verschiedene Fenstergr\"o{\ss}en $W$ aus.
+    \begin{solution}
+      \lstinputlisting{../code/counthist.m}
+      \lstinputlisting{../code/plotcounthist.m}
+      \colorbox{white}{\includegraphics[width=1\textwidth]{counthist}}
+    \end{solution}
+
+    
+  \end{parts}
+  
+\end{questions}
+
+\end{document}

pointprocesses/exercises/pointprocesses01.tex

@@ -11,11 +11,11 @@
 \usepackage[left=20mm,right=20mm,top=25mm,bottom=25mm]{geometry}
 \pagestyle{headandfoot}
 \ifprintanswers
-\newcommand{\stitle}{L\"osungen}
+\newcommand{\stitle}{: Solutions}
 \else
-\newcommand{\stitle}{\"Ubung}
+\newcommand{\stitle}{}
 \fi
-\header{{\bfseries\large \stitle}}{{\bfseries\large Punktprozesse}}{{\bfseries\large 27. Oktober, 2015}}
+\header{{\bfseries\large Exercise 8\stitle}}{{\bfseries\large Point processes}}{{\bfseries\large November 27th, 2017}}
 \firstpagefooter{Prof. Dr. Jan Benda}{Phone: 29 74573}{Email:
 jan.benda@uni-tuebingen.de}
 \runningfooter{}{\thepage}{}
@@ -89,17 +89,20 @@ jan.benda@uni-tuebingen.de}
 \begin{questions}
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-  \question \qt{Statistik von Spiketrains}
+  \question \qt{Statistics of interspike intervals}
-  In Ilias findet ihr die Dateien \code{poisson.mat},
+  Download the files \code{poisson.mat},
-  \code{pifou.mat}, und \code{lifadapt.mat}.  Jede dieser Dateien
+  \code{pifou.mat}, and \code{lifadapt.mat} from Ilias.  
-  enth\"alt mehrere Trials von Spiketrains von einer bestimmten Art
+  Each of these files contains several trials of spike trains
-  von Neuron. Die Spikezeiten sind in Sekunden gemessen.
+  of a specific type of neuron. The spike times are measured in seconds.
-
+
-  Mit den folgenden Aufgaben wollen wir die Statistik der Spiketrains
+  We want to compare the statistics of the interspike intervals of the
-  der drei Neurone miteinander vergleichen.
+  three neurons.
   \begin{parts}
-    \part Lade die Spiketrains aus den drei Dateien. Achte darauf,
+    \part Load the spike trains from the three files.
-    dass sie verschiedene Variablen\-namen bekommen.
+    Make sure that the data are assigned to different variables. 
+
+    What is the type of the data? How can you access individual spike trains?
+    How do you access single spike times?
     \begin{solution}
       \begin{lstlisting}
         clear all
@@ -116,19 +119,22 @@ jan.benda@uni-tuebingen.de}
         clear all
         x = load('poisson.mat');
         poissonspikes = x.spikes;
-        x = load( pifou.mat' );
+        x = load('pifou.mat');
         pifouspikes = x.spikes;
         x = load('lifadapt.mat');
         lifadaptspikes = x.spikes;
       \end{lstlisting}
     \end{solution}
 
-    \part Schreibe eine Funktion, die die Spikezeiten der ersten
+    \newsolutionpage    
-    $t_{max}$ Sekunden in einem Rasterplot visualisiert.  In jeder
+    \part Write a function that illustrated the spike times of the
-    Zeile des Rasterplots wird ein Spiketrain dargestellt. Jeder
+    first $t_{max}$ seconds in a raster plot. Each spike train is one
-    einzelne Spike wird als senkrechte Linie zu der Zeit des
+    row in the raster plot. Each spike is a vertical line at the time
-    Auftretens des Spikes geplottet. Benutze die Funktion, um die
+    of the spike. When appropriate, the function should use milliseconds 
-    Spikeraster der ersten 1\,s der drei Neurone nebeneinander zu plotten.
+    for the time axis instead of seconds.
+
+    Use this function to plot the first second of the
+    spike rasters of the three neurons.
     \begin{solution}
       \lstinputlisting{../code/spikeraster.m}
       \lstinputlisting{../code/plotspikeraster.m}
@@ -136,61 +142,55 @@ jan.benda@uni-tuebingen.de}
       \colorbox{white}{\includegraphics[width=1\textwidth]{spikeraster}}
     \end{solution}
   
-    \part Schreibe eine Funktion, die einen einzigen Vektor mit den
+    \part Write a function that returns a single vector containing the
-    Interspikeintervallen aller Trials von Spikezeiten zur\"uckgibt.
+    interspike intervals of all trials of spike times.
     \begin{solution}
       \lstinputlisting{../code/isis.m}
     \end{solution}
     
-    \part Schreibe eine Funktion, die ein normiertes Histogramm aus
+    \part Write a function that computes an estimate of the
-    einem Vektor von Interspikeintervallen, gegeben in Sekunden,
+    probability density of interspike intervals from a vector of
-    berechnet und dieses mit richtiger Achsenbeschriftung plottet.
+    interspike intervals. The function should automatically choose a
-    Die Interspikeintervalle sollen dabei in Millisekunden angegeben
+    good bin width for the histogram.  
-    werden. Die Funktion soll zus\"atzlich den Mittelwert, die
+
-    Standardabweichung, und den Variationskoeffizienten der
+    Write another function that plots the probability density of
-    Interspikeintervalle berechnen und diese im Plot mit angeben.
+    interspike intervals given a vector of interspike intervals as
-    
+    argument. The function should use the first function for computing
-    Benutze die vorherige und diese Funktion, um die
+    the probability density. The interspike intervals are given in
-    Interspikeintervall Verteilung der drei Neurone zu vergleichen.
+    seconds, but the plot should mark the interspike intervals in
+    milliseconds. In addition, the function should compute the mean,
+    the standard deviation and the coefficient of variation and
+    display them in the plot as well.
+
+    Use this and the previous functions to compare the 
+    interspike interval statistics of the three neurons.
     \begin{solution}
       \lstinputlisting{../code/isihist.m}
-      \lstinputlisting{../code/plotisih.m}
+      \lstinputlisting{../code/plotisihist.m}
+      \lstinputlisting{../code/plotisihs.m}
       \mbox{}\\[-3ex]
       \colorbox{white}{\includegraphics[width=1\textwidth]{isihist}}
     \end{solution}
   
-    \part Schreibe eine Funktion, die die seriellen Korrelationen der
+    \part Write a function that computes and plots the serial
-    Interspikeintervalle f\"ur Lags bis zu \code{maxlag} berechnet und
+    correlations of interspike intervals for lags upto
-    plottet.  Die Seriellen Korrelationen $\rho_k$ f\"ur Lag $k$ der
+    \code{maxlag}. The serial correlations $\rho_k$ for lag $k$ of the
-    Interspikeintervalle $T_i$ sind die Korrelationskoeffizienten
+    interspike intervals $T_i$ are the correlation coefficients
-    zwischen den Interspikeintervallen $T_i$ und den um das Lag $k$
+    between interspike intervals $T_i$ and the intervals $T_{i+k}$
-    verschobenen Intervallen $T_{i+k}$:
+    that are shifted by lag $k$:
     \[ \rho_k = \frac{\langle (T_{i+k} - \langle T \rangle)(T_i -
       \langle T \rangle) \rangle}{\langle (T_i - \langle T
       \rangle)^2\rangle} = \frac{{\rm cov}(T_{i+k}, T_i)}{{\rm
         var}(T_i)} = {\rm corr}(T_{i+k}, T_i) \] 
 
-    Benutze diese Funktion, um die Interspikeintervall-Korrelationen
+    Use this function to compare the serial correlations of the
-    der drei Neurone zu vergleichen.
+    interspike intervals of the three neurons.
     \begin{solution}
       \lstinputlisting{../code/isiserialcorr.m}
       \lstinputlisting{../code/plotserialcorr.m}
       \colorbox{white}{\includegraphics[width=1\textwidth]{serialcorr}}
     \end{solution}
 
-    \part Schreibe eine Funktion, die aus Spikezeiten
-    Histogramme aus der Anzahl von Spikes, die in Fenstern gegebener L\"ange $W$
-    gez\"ahlt werden, erzeugt und plottet.
-
-    Wende diese Funktion auf die drei
-    Datens\"atze an. Probiere verschiedene Fenstergr\"o{\ss}en $W$ aus.
-    \begin{solution}
-      \lstinputlisting{../code/counthist.m}
-      \lstinputlisting{../code/plotcounthist.m}
-      \colorbox{white}{\includegraphics[width=1\textwidth]{counthist}}
-    \end{solution}
-
-    
   \end{parts}
   
 \end{questions}

pointprocesses/lecture/pointprocessscetchA.eps

@@ -1,7 +1,7 @@
 %!PS-Adobe-2.0 EPSF-2.0
 %%Title: pointprocessscetchA.tex
 %%Creator: gnuplot 4.6 patchlevel 4
-%%CreationDate: Sat Nov 25 18:46:51 2017
+%%CreationDate: Mon Nov 27 21:08:10 2017
 %%DocumentFonts: 
 %%BoundingBox: 50 50 373 135
 %%EndComments
@@ -433,7 +433,7 @@ SDict begin [
   /Author (jan)
 %  /Producer (gnuplot)
 %  /Keywords ()
-  /CreationDate (Sat Nov 25 18:46:51 2017)
+  /CreationDate (Mon Nov 27 21:08:10 2017)
   /DOCINFO pdfmark
 end
 } ifelse

pointprocesses/lecture/pointprocessscetchB.eps

@@ -1,7 +1,7 @@
 %!PS-Adobe-2.0 EPSF-2.0
 %%Title: pointprocessscetchB.tex
 %%Creator: gnuplot 4.6 patchlevel 4
-%%CreationDate: Sat Nov 25 18:46:51 2017
+%%CreationDate: Mon Nov 27 21:08:10 2017
 %%DocumentFonts: 
 %%BoundingBox: 50 50 373 237
 %%EndComments
@@ -433,7 +433,7 @@ SDict begin [
   /Author (jan)
 %  /Producer (gnuplot)
 %  /Keywords ()
-  /CreationDate (Sat Nov 25 18:46:51 2017)
+  /CreationDate (Mon Nov 27 21:08:10 2017)
   /DOCINFO pdfmark
 end
 } ifelse

statistics/exercises/exercises02.tex

@@ -11,11 +11,11 @@
 \usepackage[left=20mm,right=20mm,top=25mm,bottom=25mm]{geometry}
 \pagestyle{headandfoot}
 \ifprintanswers
-\newcommand{\stitle}{: L\"osungen}
+\newcommand{\stitle}{: Solutions}
 \else
 \newcommand{\stitle}{}
 \fi
-\header{{\bfseries\large Exercise 7\stitle}}{{\bfseries\large Statistics}}{{\bfseries\large 21. November, 2017}}
+\header{{\bfseries\large Exercise 7\stitle}}{{\bfseries\large Statistics}}{{\bfseries\large November 21st, 2017}}
 \firstpagefooter{Prof. Dr. Jan Benda}{Phone: 29 74573}{Email:
 jan.benda@uni-tuebingen.de}
 \runningfooter{}{\thepage}{}
@@ -78,8 +78,6 @@ jan.benda@uni-tuebingen.de}
 \newcommand{\extra}{--- bonus question ---\ \mbox{}}
 \newcommand{\code}[1]{\texttt{#1}}
 
-\graphicspath{{../../pointprocesses/exercises/}}
-
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 \begin{document}
@@ -182,81 +180,6 @@ With the following questions we want to illustrate the central limit theorem.
   \includegraphics[width=0.5\textwidth]{centrallimit-samples}
 \end{solution}
 
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-  \question \qt{Statistics of interspike intervals}
-  Download the files \code{poisson.mat},
-  \code{pifou.mat}, and \code{lifadapt.mat} from Ilias.  
-  Each of these files contains several trials of spike trains
-  of a specific type of neuron. The spike times are measured in seconds.
-
-  We want to compare the statistics of the interspike intervals of the
-  three neurons.
-  \begin{parts}
-    \part Load the spike trains from the three files.
-    Make sure that data are assigned to different variables. 
-
-    What is the type of the data? How can you access individual spike trains?
-    How do you access single spike times?
-    \begin{solution}
-      \begin{lstlisting}
-        clear all
-        % not so good:
-        load poisson.mat
-        whos
-        poissonspikes = spikes;
-        load pifou.mat;
-        pifouspikes = spikes;
-        load lifadapt.mat;
-        lifadaptspikes = spikes;
-        clear spikes;
-        % better:
-        clear all
-        x = load('poisson.mat');
-        poissonspikes = x.spikes;
-        x = load('pifou.mat');
-        pifouspikes = x.spikes;
-        x = load('lifadapt.mat');
-        lifadaptspikes = x.spikes;
-      \end{lstlisting}
-    \end{solution}
-    
-    \part Write a function that illustrated the spike times of the
-    first $t_{max}$ seconds in a raster plot. Each spike train is one
-    row in the raster plot. Each spike is a vertical line at the time
-    of the spike. Use this function to plot the first second of the
-    spike rasters of the three neurons.
-    \begin{solution}
-      \lstinputlisting{../../pointprocesses/code/spikeraster.m}
-      \lstinputlisting{../../pointprocesses/code/plotspikeraster.m}
-      \mbox{}\\[-3ex]
-      \colorbox{white}{\includegraphics[width=1\textwidth]{spikeraster}}
-    \end{solution}
-  
-    \part Write a function that returns a single vector containing the
-    interspike intervals of aall trials of spike times.
-    \begin{solution}
-      \lstinputlisting{../../pointprocesses/code/isis.m}
-    \end{solution}
-    
-    \part Write a function that computes and plots an estimate of the
-    probability density of interspike intervals from a vector of
-    interspike intervals. The interspike intervals are given in
-    seconds, but the plot should mark the interspike intervals in
-    milliseconds. In addition, the function should compute the mean,
-    the standard deviation and the coefficient of variation
-    and display them in the plot as well.
-
-    Use this and the previous functions to compare the 
-    interspike interval statistics of the three neurons.
-    \begin{solution}
-      \lstinputlisting{../../pointprocesses/code/isihist.m}
-      \lstinputlisting{../../pointprocesses/code/plotisih.m}
-      \mbox{}\\[-3ex]
-      \colorbox{white}{\includegraphics[width=1\textwidth]{isihist}}
-    \end{solution}
-  \end{parts}
-
 \end{questions}
 
 \end{document}

statistics/exercises/instructions.tex

@@ -1,6 +1,6 @@
-\vspace*{-6.5ex}
+\vspace*{-7.8ex}
 \begin{center}
-\textbf{\Large Introduction to scientific computing}\\[1ex]
+\textbf{\Large Introduction to Scientific Computing}\\[2.3ex]
 {\large Jan Grewe, Jan Benda}\\[-3ex]
-Neuroethology lab \hfill --- \hfill Institute for Neurobiology \hfill --- \hfill \includegraphics[width=0.28\textwidth]{UT_WBMW_Black_RGB} \\
+Neuroethology Lab \hfill --- \hfill Institute for Neurobiology \hfill --- \hfill \includegraphics[width=0.28\textwidth]{UT_WBMW_Black_RGB} \\
 \end{center}