fixed exercise 01 of point processes
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@ -26,7 +26,7 @@ function isicorr = isiserialcorr(isivec, maxlag)
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% plot:
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plot(lags, isicorr, '-b');
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hold on;
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scatter(lags, isicorr, 100.0, 'b', 'filled');
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scatter(lags, isicorr, 10.0, 'b', 'filled');
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hold off;
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xlabel('Lag k')
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ylabel('\rho_k')
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@ -1,7 +1,7 @@
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function plotISIHist(isis, binwidth)
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function plotisihist(isis, binwidth)
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% Plot and annotate histogram of interspike intervals.
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%
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% plotISIHist(isis, binwidth)
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% plotisihist(isis, binwidth)
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%
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% Arguments:
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% isis: vector of interspike intervals in seconds
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@ -9,9 +9,9 @@ function plotISIHist(isis, binwidth)
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% compute normalized histogram:
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if nargin < 2
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[pdf, centers] = isiHist(isis);
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[pdf, centers] = isihist(isis);
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else
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[pdf, centers] = isiHist(isis, binwidth);
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[pdf, centers] = isihist(isis, binwidth);
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end
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% plot:
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@ -21,14 +21,11 @@ function plotISIHist(isis, binwidth)
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% annotation:
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misi = mean(isis);
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sdisi = std(isis);
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disi = sdisi^2.0/2.0/misi^3;
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text(0.95, 0.8, sprintf('mean=%.1f ms', 1000.0*misi), ...
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'Units', 'normalized', 'HorizontalAlignment', 'right')
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text(0.95, 0.7, sprintf('std=%.1f ms', 1000.0*sdisi), ...
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'Units', 'normalized', 'HorizontalAlignment', 'right')
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text(0.95, 0.6, sprintf('CV=%.2f', sdisi/misi), ...
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'Units', 'normalized', 'HorizontalAlignment', 'right')
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%text(0.95, 0.5, sprintf('D=%.1f Hz', disi), ...
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% 'Units', 'normalized', 'HorizontalAlignment', 'right')
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end
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@ -1,19 +1,19 @@
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maxisi = 300.0;
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subplot(1, 3, 1);
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poissonisis = isis(poissonspikes);
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isihist(poissonisis, 0.001);
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plotisihist(poissonisis, 0.001);
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xlim([0, maxisi])
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title('Poisson');
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subplot(1, 3, 2);
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pifouisis = isis(pifouspikes);
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isihist(pifouisis, 0.001);
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plotisihist(pifouisis, 0.001);
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xlim([0, maxisi])
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title('PIF OU');
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subplot(1, 3, 3);
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lifadaptisis = isis(lifadaptspikes);
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isihist(lifadaptisis, 0.001);
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plotisihist(lifadaptisis, 0.001);
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xlim([0, maxisi])
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title('LIF adapt');
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savefigpdf(gcf, 'isihist.pdf', 20, 7);
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savefigpdf(gcf, 'isihist.pdf', 20, 7);
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@ -1,11 +1,6 @@
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\vspace*{-6.5ex}
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\vspace*{-7.8ex}
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\begin{center}
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\textbf{\Large Einf\"uhrung in die wissenschaftliche Datenverarbeitung}\\[1ex]
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\textbf{\Large Introduction to Scientific Computing}\\[2.3ex]
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{\large Jan Grewe, Jan Benda}\\[-3ex]
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Abteilung Neuroethologie \hfill --- \hfill Institut f\"ur Neurobiologie \hfill --- \hfill \includegraphics[width=0.28\textwidth]{UT_WBMW_Black_RGB} \\
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Neuroethology Lab \hfill --- \hfill Institute for Neurobiology \hfill --- \hfill \includegraphics[width=0.28\textwidth]{UT_WBMW_Black_RGB} \\
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\end{center}
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\ifprintanswers%
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\else
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\fi
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198
pointprocesses/exercises/pointprocesses01-de.tex
Normal file
198
pointprocesses/exercises/pointprocesses01-de.tex
Normal file
@ -0,0 +1,198 @@
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\documentclass[12pt,a4paper,pdftex]{exam}
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\usepackage[german]{babel}
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\usepackage{pslatex}
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\usepackage[mediumspace,mediumqspace,Gray]{SIunits} % \ohm, \micro
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\usepackage{xcolor}
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\usepackage{graphicx}
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\usepackage[breaklinks=true,bookmarks=true,bookmarksopen=true,pdfpagemode=UseNone,pdfstartview=FitH,colorlinks=true,citecolor=blue]{hyperref}
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%%%%% layout %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\usepackage[left=20mm,right=20mm,top=25mm,bottom=25mm]{geometry}
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\pagestyle{headandfoot}
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\ifprintanswers
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\newcommand{\stitle}{L\"osungen}
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\else
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\newcommand{\stitle}{\"Ubung}
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\fi
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\header{{\bfseries\large \stitle}}{{\bfseries\large Punktprozesse}}{{\bfseries\large 27. Oktober, 2015}}
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\firstpagefooter{Prof. Dr. Jan Benda}{Phone: 29 74573}{Email:
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jan.benda@uni-tuebingen.de}
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\runningfooter{}{\thepage}{}
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\setlength{\baselineskip}{15pt}
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\setlength{\parindent}{0.0cm}
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\setlength{\parskip}{0.3cm}
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\renewcommand{\baselinestretch}{1.15}
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%%%%% listings %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\usepackage{listings}
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\lstset{
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language=Matlab,
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basicstyle=\ttfamily\footnotesize,
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numbers=left,
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numberstyle=\tiny,
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title=\lstname,
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showstringspaces=false,
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commentstyle=\itshape\color{darkgray},
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breaklines=true,
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breakautoindent=true,
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columns=flexible,
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frame=single,
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xleftmargin=1em,
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xrightmargin=1em,
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aboveskip=10pt
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}
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%%%%% math stuff: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\usepackage{amsmath}
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\usepackage{amssymb}
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\usepackage{bm}
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\usepackage{dsfont}
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\newcommand{\naZ}{\mathds{N}}
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\newcommand{\gaZ}{\mathds{Z}}
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\newcommand{\raZ}{\mathds{Q}}
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\newcommand{\reZ}{\mathds{R}}
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\newcommand{\reZp}{\mathds{R^+}}
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\newcommand{\reZpN}{\mathds{R^+_0}}
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\newcommand{\koZ}{\mathds{C}}
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%%%%% page breaks %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\newcommand{\continue}{\ifprintanswers%
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\else
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\vfill\hspace*{\fill}$\rightarrow$\newpage%
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\fi}
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\newcommand{\continuepage}{\ifprintanswers%
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\newpage
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\else
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\vfill\hspace*{\fill}$\rightarrow$\newpage%
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\fi}
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\newcommand{\newsolutionpage}{\ifprintanswers%
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\newpage%
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\else
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\fi}
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%%%%% new commands %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\newcommand{\qt}[1]{\textbf{#1}\\}
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\newcommand{\pref}[1]{(\ref{#1})}
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\newcommand{\extra}{--- Zusatzaufgabe ---\ \mbox{}}
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\newcommand{\code}[1]{\texttt{#1}}
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\begin{document}
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\input{instructions}
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\begin{questions}
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\question \qt{Statistik von Spiketrains}
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In Ilias findet ihr die Dateien \code{poisson.mat},
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\code{pifou.mat}, und \code{lifadapt.mat}. Jede dieser Dateien
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enth\"alt mehrere Trials von Spiketrains von einer bestimmten Art
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von Neuron. Die Spikezeiten sind in Sekunden gemessen.
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Mit den folgenden Aufgaben wollen wir die Statistik der Spiketrains
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der drei Neurone miteinander vergleichen.
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\begin{parts}
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\part Lade die Spiketrains aus den drei Dateien. Achte darauf,
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dass sie verschiedene Variablen\-namen bekommen.
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\begin{solution}
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\begin{lstlisting}
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clear all
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% not so good:
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load poisson.mat
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whos
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poissonspikes = spikes;
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load pifou.mat;
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pifouspikes = spikes;
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load lifadapt.mat;
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lifadaptspikes = spikes;
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clear spikes;
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% better:
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clear all
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x = load( 'poisson.mat' );
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poissonspikes = x.spikes;
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x = load( pifou.mat' );
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pifouspikes = x.spikes;
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x = load( 'lifadapt.mat' );
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lifadaptspikes = x.spikes;
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\end{lstlisting}
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\end{solution}
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\part Schreibe eine Funktion, die die Spikezeiten der ersten
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$t_{max}$ Sekunden in einem Rasterplot visualisiert. In jeder
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Zeile des Rasterplots wird ein Spiketrain dargestellt. Jeder
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einzelne Spike wird als senkrechte Linie zu der Zeit des
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Auftretens des Spikes geplottet. Benutze die Funktion, um die
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Spikeraster der ersten 1\,s der drei Neurone nebeneinander zu plotten.
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\begin{solution}
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\lstinputlisting{../code/spikeraster.m}
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\lstinputlisting{../code/plotspikeraster.m}
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\mbox{}\\[-3ex]
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\colorbox{white}{\includegraphics[width=1\textwidth]{spikeraster}}
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\end{solution}
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\part Schreibe eine Funktion, die einen einzigen Vektor mit den
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Interspikeintervallen aller Trials von Spikezeiten zur\"uckgibt.
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\begin{solution}
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\lstinputlisting{../code/isis.m}
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\end{solution}
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\part Schreibe eine Funktion, die ein normiertes Histogramm aus
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einem Vektor von Interspikeintervallen, gegeben in Sekunden,
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berechnet und dieses mit richtiger Achsenbeschriftung plottet.
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Die Interspikeintervalle sollen dabei in Millisekunden angegeben
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werden. Die Funktion soll zus\"atzlich den Mittelwert, die
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Standardabweichung, und den Variationskoeffizienten der
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Interspikeintervalle berechnen und diese im Plot mit angeben.
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Benutze die vorherige und diese Funktion, um die
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Interspikeintervall Verteilung der drei Neurone zu vergleichen.
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\begin{solution}
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\lstinputlisting{../code/isihist.m}
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\lstinputlisting{../code/plotisih.m}
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\mbox{}\\[-3ex]
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\colorbox{white}{\includegraphics[width=1\textwidth]{isihist}}
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\end{solution}
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\part Schreibe eine Funktion, die die seriellen Korrelationen der
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Interspikeintervalle f\"ur Lags bis zu \code{maxlag} berechnet und
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plottet. Die Seriellen Korrelationen $\rho_k$ f\"ur Lag $k$ der
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Interspikeintervalle $T_i$ sind die Korrelationskoeffizienten
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zwischen den Interspikeintervallen $T_i$ und den um das Lag $k$
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verschobenen Intervallen $T_{i+k}$:
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\[ \rho_k = \frac{\langle (T_{i+k} - \langle T \rangle)(T_i -
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\langle T \rangle) \rangle}{\langle (T_i - \langle T
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\rangle)^2\rangle} = \frac{{\rm cov}(T_{i+k}, T_i)}{{\rm
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var}(T_i)} = {\rm corr}(T_{i+k}, T_i) \]
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Benutze diese Funktion, um die Interspikeintervall-Korrelationen
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der drei Neurone zu vergleichen.
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\begin{solution}
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\lstinputlisting{../code/isiserialcorr.m}
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\lstinputlisting{../code/plotserialcorr.m}
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\colorbox{white}{\includegraphics[width=1\textwidth]{serialcorr}}
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\end{solution}
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\part Schreibe eine Funktion, die aus Spikezeiten
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Histogramme aus der Anzahl von Spikes, die in Fenstern gegebener L\"ange $W$
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gez\"ahlt werden, erzeugt und plottet.
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Wende diese Funktion auf die drei
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Datens\"atze an. Probiere verschiedene Fenstergr\"o{\ss}en $W$ aus.
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\begin{solution}
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\lstinputlisting{../code/counthist.m}
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\lstinputlisting{../code/plotcounthist.m}
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\colorbox{white}{\includegraphics[width=1\textwidth]{counthist}}
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\end{solution}
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\end{parts}
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\end{questions}
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\end{document}
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@ -11,11 +11,11 @@
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\usepackage[left=20mm,right=20mm,top=25mm,bottom=25mm]{geometry}
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\pagestyle{headandfoot}
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\ifprintanswers
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\newcommand{\stitle}{L\"osungen}
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\newcommand{\stitle}{: Solutions}
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\else
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\newcommand{\stitle}{\"Ubung}
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\newcommand{\stitle}{}
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\fi
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\header{{\bfseries\large \stitle}}{{\bfseries\large Punktprozesse}}{{\bfseries\large 27. Oktober, 2015}}
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\header{{\bfseries\large Exercise 8\stitle}}{{\bfseries\large Point processes}}{{\bfseries\large November 27th, 2017}}
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\firstpagefooter{Prof. Dr. Jan Benda}{Phone: 29 74573}{Email:
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jan.benda@uni-tuebingen.de}
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\runningfooter{}{\thepage}{}
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@ -89,17 +89,20 @@ jan.benda@uni-tuebingen.de}
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\begin{questions}
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\question \qt{Statistik von Spiketrains}
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In Ilias findet ihr die Dateien \code{poisson.mat},
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\code{pifou.mat}, und \code{lifadapt.mat}. Jede dieser Dateien
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enth\"alt mehrere Trials von Spiketrains von einer bestimmten Art
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von Neuron. Die Spikezeiten sind in Sekunden gemessen.
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Mit den folgenden Aufgaben wollen wir die Statistik der Spiketrains
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der drei Neurone miteinander vergleichen.
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\question \qt{Statistics of interspike intervals}
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Download the files \code{poisson.mat},
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\code{pifou.mat}, and \code{lifadapt.mat} from Ilias.
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Each of these files contains several trials of spike trains
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of a specific type of neuron. The spike times are measured in seconds.
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We want to compare the statistics of the interspike intervals of the
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three neurons.
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\begin{parts}
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\part Lade die Spiketrains aus den drei Dateien. Achte darauf,
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dass sie verschiedene Variablen\-namen bekommen.
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\part Load the spike trains from the three files.
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Make sure that the data are assigned to different variables.
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What is the type of the data? How can you access individual spike trains?
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How do you access single spike times?
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\begin{solution}
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\begin{lstlisting}
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clear all
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@ -114,21 +117,24 @@ jan.benda@uni-tuebingen.de}
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clear spikes;
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% better:
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clear all
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x = load( 'poisson.mat' );
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x = load('poisson.mat');
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poissonspikes = x.spikes;
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x = load( pifou.mat' );
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x = load('pifou.mat');
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pifouspikes = x.spikes;
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x = load( 'lifadapt.mat' );
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x = load('lifadapt.mat');
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lifadaptspikes = x.spikes;
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\end{lstlisting}
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\end{solution}
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\part Schreibe eine Funktion, die die Spikezeiten der ersten
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$t_{max}$ Sekunden in einem Rasterplot visualisiert. In jeder
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Zeile des Rasterplots wird ein Spiketrain dargestellt. Jeder
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einzelne Spike wird als senkrechte Linie zu der Zeit des
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Auftretens des Spikes geplottet. Benutze die Funktion, um die
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Spikeraster der ersten 1\,s der drei Neurone nebeneinander zu plotten.
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\newsolutionpage
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\part Write a function that illustrated the spike times of the
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first $t_{max}$ seconds in a raster plot. Each spike train is one
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row in the raster plot. Each spike is a vertical line at the time
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of the spike. When appropriate, the function should use milliseconds
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for the time axis instead of seconds.
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Use this function to plot the first second of the
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spike rasters of the three neurons.
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\begin{solution}
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\lstinputlisting{../code/spikeraster.m}
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\lstinputlisting{../code/plotspikeraster.m}
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@ -136,61 +142,55 @@ jan.benda@uni-tuebingen.de}
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\colorbox{white}{\includegraphics[width=1\textwidth]{spikeraster}}
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\end{solution}
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\part Schreibe eine Funktion, die einen einzigen Vektor mit den
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Interspikeintervallen aller Trials von Spikezeiten zur\"uckgibt.
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\part Write a function that returns a single vector containing the
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interspike intervals of all trials of spike times.
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\begin{solution}
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\lstinputlisting{../code/isis.m}
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\end{solution}
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\part Schreibe eine Funktion, die ein normiertes Histogramm aus
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einem Vektor von Interspikeintervallen, gegeben in Sekunden,
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berechnet und dieses mit richtiger Achsenbeschriftung plottet.
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Die Interspikeintervalle sollen dabei in Millisekunden angegeben
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werden. Die Funktion soll zus\"atzlich den Mittelwert, die
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Standardabweichung, und den Variationskoeffizienten der
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Interspikeintervalle berechnen und diese im Plot mit angeben.
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Benutze die vorherige und diese Funktion, um die
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Interspikeintervall Verteilung der drei Neurone zu vergleichen.
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\part Write a function that computes an estimate of the
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probability density of interspike intervals from a vector of
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interspike intervals. The function should automatically choose a
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good bin width for the histogram.
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Write another function that plots the probability density of
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interspike intervals given a vector of interspike intervals as
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argument. The function should use the first function for computing
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the probability density. The interspike intervals are given in
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seconds, but the plot should mark the interspike intervals in
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milliseconds. In addition, the function should compute the mean,
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the standard deviation and the coefficient of variation and
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display them in the plot as well.
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Use this and the previous functions to compare the
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interspike interval statistics of the three neurons.
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\begin{solution}
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\lstinputlisting{../code/isihist.m}
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\lstinputlisting{../code/plotisih.m}
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\lstinputlisting{../code/plotisihist.m}
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\lstinputlisting{../code/plotisihs.m}
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\mbox{}\\[-3ex]
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\colorbox{white}{\includegraphics[width=1\textwidth]{isihist}}
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\end{solution}
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|
||||
\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 $T_{i+k}$:
|
||||
\part Write a function that computes and plots the serial
|
||||
correlations of interspike intervals for lags upto
|
||||
\code{maxlag}. The serial correlations $\rho_k$ for lag $k$ of the
|
||||
interspike intervals $T_i$ are the correlation coefficients
|
||||
between interspike intervals $T_i$ and the intervals $T_{i+k}$
|
||||
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
|
||||
der drei Neurone zu vergleichen.
|
||||
Use this function to compare the serial correlations of the
|
||||
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}
|
||||
|
||||
@ -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
|
||||
|
||||
Binary file not shown.
@ -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
|
||||
|
||||
Binary file not shown.
@ -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}
|
||||
|
||||
@ -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}
|
||||
|
||||
Reference in New Issue
Block a user