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adaptation of the assignments to the modern times

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22
projects/disclaimer.tex
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@ -8,26 +8,28 @@
\vspace{1ex}
The {\bf code} and the {\bf presentation} should be uploaded to
ILIAS at latest on Thursday, November 6th, 10:00h.
The presentations start on Thursday 11:00h. Please hand in
your presentation as a pdf file. Bundle everything into a
{\em single} zip-file.
ILIAS at latest on Thursday, November 5th, 13:00h. The
presentations start on Thursday 13:00h. Please hand in your
presentation as a pdf file. Bundle everything (the pdf and the
code) into a {\em single} zip-file.
\vspace{1ex}
The {\bf code} should be exectuable without any further
adjustments from us. This means that you need to include all
adjustments from our side. This means that you need to include all
additional functions you wrote and the data into the
zip-file. A single {\em main script} should produce the same
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
course. The code should be properly commented
and comprehensible by third persons (use proper and consistent
variable names).
variable and function names).
\vspace{1ex} \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.
number as a comment at the top of a script called
\texttt{main.m}.} The \texttt{main.m} script then should
coordinate the execution of your analysis by e.g. calling
sub-scripts and functions with appropriate parameters.
\vspace{1ex}

23
projects/project_adaptation_fit/adaptation_fit.tex
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@ -6,8 +6,8 @@
\pagestyle{headandfoot}
\runningheadrule
\firstpageheadrule
\firstpageheader{Scientific Computing}{Project Assignment}{11/05/2014
-- 11/06/2014}
\firstpageheader{Scientific Computing}{Project Assignment}{11/02/2015
-- 11/05/2015}
%\runningheader{Homework 01}{Page \thepage\ of \numpages}{23. October 2014}
\firstpagefooter{}{}{{\bf Supervisor:} Jan Grewe}
\runningfooter{}{}{}
@ -44,15 +44,14 @@ electroreceptors of the weakly electric fish \textit{Apteronotus
certain intensity, i.e. the \textit{contrast} which is also stored
in the file.
\begin{parts}
\part Estimate for each stimulus intensity the
PSTH and plot it. You will see that there are three parts. (i)
The first 200 ms is the baseline (no stimulus) activity. (ii)
During the next 1000 ms the stimulus was switched on. (iii) After
stimulus offset the neuronal activity was recorded for further 825
ms.
\part Estimate the adaptation time-constant of the adaptation for
both the stimulus on- and offset. To do this fit an exponential
function to the data. For the decay use:
\part Estimate for each stimulus intensity the PSTH and plot
it. You will see that there are three parts. (i) The first
200\,ms is the baseline (no stimulus) activity. (ii) During the
next 1000\,ms the stimulus was switched on. (iii) After stimulus
offset the neuronal activity was recorded for further 825\,ms.
\part Estimate the adaptation time-constant for both the stimulus
on- and offset. To do this fit an exponential function to the
data. For the decay use:
\begin{equation}
f_{A,\tau,y_0}(t) = y_0 + A \cdot e^{-\frac{t}{\tau}},
\end{equation}
@ -62,7 +61,7 @@ electroreceptors of the weakly electric fish \textit{Apteronotus
\begin{equation}
f_{A,\tau, y_0}(t) = y_0 + A \cdot \left(1 - e^{-\frac{t}{\tau}}\right ),
\end{equation}
\part Plot the decays into the data.
\part Plot the best fits into the data.
\part Plot the estimated time-constants as a function of stimulus intensity.
\end{parts}
\end{questions}

11
projects/project_eod/eod.tex
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@ -6,10 +6,10 @@
\pagestyle{headandfoot}
\runningheadrule
\firstpageheadrule
\firstpageheader{Scientific Computing}{Project Assignment}{11/05/2014
-- 11/06/2014}
\firstpageheader{Scientific Computing}{Project Assignment}{11/02/2015
-- 11/05/2015}
%\runningheader{Homework 01}{Page \thepage\ of \numpages}{23. October 2014}
\firstpagefooter{}{}{{\bf Supervisor:} Fabian Sinz}
\firstpagefooter{}{}{{\bf Supervisor:} Jan Grewe}
\runningfooter{}{}{}
\pointsinmargin
\bracketedpoints
@ -38,8 +38,9 @@
\begin{parts}
\part Load and plot the data in an appropriate way. Time is in
seconds and the voltage is in mV/cm.
\part Fit the following curve to the eod (select a smaller time
window for fitting, not the entire trace) using least squares:
\part Fit the following curve to the eod (select a small time
window, a few tens of milliseconds, for fitting, not the entire
trace) using least squares:
$$f_{\omega_0,b_0,\varphi_1, ...,\varphi_n}(t) = b_0 +
\sum_{j=1}^n \sin(2\pi j\omega_0\cdot t + \varphi_j ).$$
$\omega_0$ is called {\em fundamental frequency}. The single terms

18
projects/project_numbers/numbers.tex
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@ -6,10 +6,10 @@
\pagestyle{headandfoot}
\runningheadrule
\firstpageheadrule
\firstpageheader{Scientific Computing}{Project Assignment}{11/05/2014
-- 11/06/2014}
\firstpageheader{Scientific Computing}{Project Assignment}{11/02/2015
-- 11/05/2015}
%\runningheader{Homework 01}{Page \thepage\ of \numpages}{23. October 2014}
\firstpagefooter{}{}{{\bf Supervisor:} Fabian Sinz}
\firstpagefooter{}{}{{\bf Supervisor:} Jan Grewe}
\runningfooter{}{}{}
\pointsinmargin
\bracketedpoints
@ -37,24 +37,20 @@
macaque prefrontal cortex (data courtesy of Prof. Nieder). The task
of the monkey was to discriminate point-sets with 1 to 4 points. The
first column contains the number of points shown plus one. The
remaining columns contain the spike response across 1300ms. During
the first 500ms the monkey was fixating a target. The next 800ms the
stimulus was shown. This was followed by 1000ms delay time before
remaining columns contain the spike response across 1300\,ms. During
the first 500\,ms the monkey was fixating a target. The next 800\,ms the
stimulus was shown. This was followed by 1000\,ms delay time before
the monkey was allowed to respond.
\begin{parts}
\part Plot the data in an appropriate way.
\part Sort the trials according to the stimulus presented and
compute the firing rate (in Hz) in the time interval
500-1300ms. Plot the firing rate in an appropriate way.
500-1300\,ms. Plot the firing rate in an appropriate way.
\part Use an appropriate test to determine whether the firing rate
in that interval is significantly different for 1 vs. 4 points
shown.
\end{parts}
\end{questions}
\end{document}

24
projects/project_onset_fi/onset_fi.tex
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@ -6,8 +6,8 @@
\pagestyle{headandfoot}
\runningheadrule
\firstpageheadrule
\firstpageheader{Scientific Computing}{Project Assignment}{11/05/2014
-- 11/06/2014}
\firstpageheader{Scientific Computing}{Project Assignment}{11/02/2015
-- 11/05/2015}
%\runningheader{Homework 01}{Page \thepage\ of \numpages}{23. October 2014}
\firstpagefooter{}{}{{\bf Supervisor:} Jan Grewe}
\runningfooter{}{}{}
@ -37,19 +37,19 @@ of the stimulus \textbf{I}ntensity.
\begin{questions}
\question In the accompanying datasets you find the
\textit{spike\_times} of an P-unit electrorecptor of the weakly
\textit{spike\_times} of an P-unit electroreceptor of the weakly
electric fish \textit{Apteronotus leptorhynchus} to a stimulus of a
certain intensity, i.e. the \textit{contrast}.
\begin{parts}
\part For each stimulus intensity estimate the average response
(PSTH) and plot it. You will see that there are three parts. (i)
The first 200 ms is the baseline (no stimulus) activity. (ii)
During the next 1000 ms the stimulus was switched on. (iii) After
stimulus offset the neuronal activity was recorded for further 825
ms.
\part Extract the neuron's activity in the first 50 ms after stimulus onset
and plot it against the stimulus intensity, respectively the
contrast, in an appropriate way.
The first 200\,ms is the baseline (no stimulus) activity. (ii)
During the next 1000\,ms the stimulus was switched on. (iii) After
stimulus offset the neuronal activity was recorded for further
825\,ms.
\part Extract the neuron's activity in the first 50\,ms after
stimulus onset and plot it against the stimulus intensity,
respectively the contrast, in an appropriate way.
\part Fit a Boltzmann function to the FI-curve. The Boltzmann function
is defined as:
\begin{equation}
@ -62,8 +62,4 @@ of the stimulus \textbf{I}ntensity.
\end{parts}
\end{questions}
\end{document}

14
projects/project_stimulus_reconstruction/stimulus_reconstruction.tex
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@ -6,8 +6,8 @@
\pagestyle{headandfoot}
\runningheadrule
\firstpageheadrule
\firstpageheader{Scientific Computing}{Project Assignment}{11/05/2014
-- 11/06/2014}
\firstpageheader{Scientific Computing}{Project Assignment}{11/02/2015
-- 11/05/2015}
%\runningheader{Homework 01}{Page \thepage\ of \numpages}{23. October 2014}
\firstpagefooter{}{}{{\bf Supervisor:} Jan Grewe}
\runningfooter{}{}{}
@ -31,8 +31,16 @@
%%%%%%%%%%%%%% Questions %%%%%%%%%%%%%%%%%%%%%%%%%
\section*{Reverse reconstruction of the stimulus evoking neuronal responses.}
During the course we have used the Spike-Triggered-Average to
To analyse encoding properties of a neuron one often calculates the
Spike-Triggered-Average (STA).
\[ STA(\tau) = \frac{1}{\langle n \rangle} \left\langle
\displaystyle\sum_{i=1}^{n}{s(t_i - \tau)} \right\rangle \]
The STA is the average stimulus that led to a spike in the neuron and
can calculated by cutting out snippets form the stimulus centered on
the respective spike time. The Spike-Triggered-Average can be used to
reconstruct the stimulus a neuron has been stimulated with.
\begin{questions}
\question In the accompanying files you find the spike responses of
P-units and pyramidal neurons of the weakly electric fish

8
projects/project_vector_strength/vector_strength.tex
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@ -6,8 +6,8 @@
\pagestyle{headandfoot}
\runningheadrule
\firstpageheadrule
\firstpageheader{Scientific Computing}{Project Assignment}{11/05/2014
-- 11/06/2014}
\firstpageheader{Scientific Computing}{Project Assignment}{11/02/2015
-- 11/05/2015}
%\runningheader{Homework 01}{Page \thepage\ of \numpages}{23. October 2014}
\firstpagefooter{}{}{{\bf Supervisor:} Jan Grewe}
\runningfooter{}{}{}
@ -31,7 +31,7 @@
%%%%%%%%%%%%%% Questions %%%%%%%%%%%%%%%%%%%%%%%%%
\section*{Quantifying the coupling of action potentials to the EOD.}
P-unit electrorecptors are driven by the fish's self-generated field,
P-unit electroreceptors are driven by the fish's self-generated field,
the EOD. In this project you have to quantify the strength of this
coulpling using the \textbf{vector strength}:
\begin{equation}
@ -46,7 +46,7 @@ locking, respectively.
\begin{questions}
\question In the accompanying datasets you find recrordings of the
``baseline'' activity of P-unit electrorecptors of different weakly
``baseline'' activity of P-unit electroreceptors of different weakly
electric fish of the species \textit{Apteronotus leptorhynchus}.
The files further contain respective recordings of the \textit{eod},
i.e. the fish's field.