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Fabian Sinz 2014-11-01 13:29:30 +01:00
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62
programming/lectures/sta_stc.tex
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@ -99,14 +99,6 @@ Cross-Correlation, Spike--Triggered--Average and Reverse Reconstruction}
\end{frame}
\begin{frame}[plain]
\frametitle{Rekapitulation}
\begin{enumerate}
\item PSTH\pause
\end{enumerate}
\end{frame}
\begin{frame}
\frametitle{Introduction to scientific computing}
\frametitle{Menue}
@ -119,7 +111,7 @@ Cross-Correlation, Spike--Triggered--Average and Reverse Reconstruction}
\begin{frame}[plain]
\huge{1. Recapitulation: PSTH}
\huge{1. Recapitulation: Plotting neuronal activity as a function of time.}
\end{frame}
@ -142,6 +134,17 @@ Cross-Correlation, Spike--Triggered--Average and Reverse Reconstruction}
\end{frame}
\begin{frame}
\frametitle{Relating stimulus and response}
\framesubtitle{Displaying the neuronal response over time - PSTH}
\begin{itemize}
\item What does this tell us? \pause
\item Wouldn't it be more interesting to relate the response to the stimulus?!
\end{itemize}
\end{frame}
\begin{frame}[plain]
\huge{2. Relating stimulus and response}
\end{frame}
@ -152,7 +155,7 @@ Cross-Correlation, Spike--Triggered--Average and Reverse Reconstruction}
\framesubtitle{How can we relate the response to the stimulus?}
\begin{figure}
\centering
\includegraphics[height=0.9\textheight]{images/conv_stim}
\includegraphics[height=0.75\textheight]{images/conv_stim}
\end{figure}
\end{frame}
@ -201,20 +204,34 @@ ylabel('correlation')
\frametitle{Relating stimulus and response}
\framesubtitle{Cross--correlation - Exercises}
\begin{enumerate}
\item calculate the cross-correlation between two vectors of random
\item Calculate the cross-correlation between two vectors of random
numbers.
\item Calculate the cross-correlation between one of these vectors
and itself (auto-correlation).
\item Calculate the cross-correlation between one vector and a
time-shifted version of itself (use \verb+circshift+ to do this).
\item Generate two vectors of random numbers, one having a (slight)
correlation with the other.
\item Calculate the correlation coefficient (\verb+corrcoef+).
\item Calculate the cross-correlation.
\item Calculate the the correlation coefficient between the one
vector and a \verb+circshif+ted version of the other.
\item Calculate the cross-correlation of these.
\item Find out the maximum correlation and its position.
\end{enumerate}
\textbf{Note:} Select max\_lag to be less than 10\% of the length of
your vectors!
\end{frame}
\begin{frame}[fagile]
\frametitle{Relating stimulus and response}
\framesubtitle{Cross--correlation - Exercises}
\begin{enumerate}
\item Create the cross correlation of the p-unit data and stimulus.
\item \textbf{Note:} you have to convert the spike\_times to a PSTH!
\item Find out the position of the correlation peak.
\item What does this tell you?
\item What does it tell you?
\end{enumerate}
\end{frame}
@ -273,8 +290,8 @@ ylabel('correlation')
\begin{enumerate}
\item Write a function \verb+sta(x, y, count, sample_rate)+ that
takes the stimulus (x), the response (y, as spike times), the
number (count) of sampling points it should cut out from the
stimulus and the sampling\_rate to convert from times to
number (count) of sample points it should cut out from the
stimulus and the sample\_rate to convert from times to
indices.
\item \textbf{Beware:} sometimes the spike\_time may be too close
to the beginning or the end of the stimulus to cut out enough
@ -284,23 +301,6 @@ ylabel('correlation')
\end{frame}
\begin{frame}[fragile]
\frametitle{Relating stimulus and response}
\framesubtitle{Spike--Triggered--Average -- STA}
What does the \textbf{STA} tell us?
\begin{figure}
\centering
\includegraphics[width=0.25\columnwidth]{images/sta}
\end{figure}
\begin{enumerate}
\item Is there a relation between stimulus and response?\pause
\item Is there a lag between them and how large is it?\pause
\item How far in the past does a neuron encode?\pause
\item Can it see into the future?
\end{enumerate}
\end{frame}
\begin{frame}[plain]
\huge{3. Reverse reconstruction using the \textbf{STA}}
\end{frame}

36
projects/disclaimer.tex
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@ -8,30 +8,34 @@
\vspace{.5cm}
The {\bf code} and the {\bf presentation} should be uploaded to
ILIAS before the presentations start on Thursday. Everything
should be bundeled into a {\em single} zip-file. The
presentation should be handed in as pdf.
ILIAS at latest on Thursday, November 6th, 12:00h.
The presentations start on Thursday 13:00h. Please hand in
your presentation as a pdf file. Bundle everything into a
{\em single} zip-file.
\vspace{.5cm}
The {\bf code} should be exectuable without any further
adjustments from us. This means that you should include all
adjustments from us. This means that you need to include all
additional functions you wrote and the data into the
zip-file. The {\em main script} should produce the same {\em
figures} that you use in your slides. The figures should follow
the guidelines for proper plotting as discussed in the first
statistics lecture. The code should be properly commented and
comprehensible by third persons (use proper and consistent
zip-file. A single {\em main script} should produce the same
{\em figures} that you use in your slides. The figures should
follow the guidelines for proper plotting as discussed in the
first statistics lecture. The code should be properly commented
and comprehensible by third persons (use proper and consistent
variable names).
\vspace{.5cm} \textbf{Please write your name and matriculation
number as a comment at the top of a script called \texttt{main.m}!}
The \texttt{main.m} script then should call all your scripts.
\vspace{.5cm}
The {\bf slides} should be handed in along with the code and in
pdf format. We will store them all on one computer to allow fast
transitions between talks. The {\bf presentation} itself should
be {\em at most} 10min long and be held in English. In the
presentation you should (i) briefly describe the problem, (ii)
explain how you solved it algorithmically (don't show your
entire code), and (iii) present figures showing your results.
The {\bf presentation} should be {\em at most} 10min long and be
held in English. In the presentation you should (i) briefly
describe the problem, (ii) explain how you solved it
algorithmically (don't show your entire code), and (iii) present
figures showing your results. We will store all presentations on
one computer to allow fast transitions between talks.
}}