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scientificComputing/projects/project_adaptation_fit/adaptation_fit.tex

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\documentclass[addpoints,11pt]{exam}
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\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}
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\begin{document}
%%%%%%%%%%%%%%%%%%%%% Submission instructions %%%%%%%%%%%%%%%%%%%%%%%%%
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\input{../disclaimer.tex}
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%%%%%%%%%%%%%% Questions %%%%%%%%%%%%%%%%%%%%%%%%%
\section*{Estimating the adaptation time-constant.}
Stimulating a neuron with a constant stimulus for an extended period of time
often leads to a strong initial response that relaxes over time. This
process is called adaptation and is ubiquitous. Your task here is to
estimate the time-constant of the firing-rate adaptation in P-unit
electroreceptors of the weakly electric fish \textit{Apteronotus
leptorhynchus}.
\begin{questions}
\question In the accompanying datasets you find the
\textit{spike\_times} of an P-unit electroreceptor to a stimulus of
a certain intensity, i.e. the \textit{contrast} which is also stored
in the file. The contrast of the stimulus is a measure relative to
the amplitude of fish's field, it has no unit. The data is sampled
with 20\,kHz sampling frequency and spike times are given in
milliseconds relative to the stimulus onset.
\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 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}
where $y_0$ the offset, $A$ the amplitude, $t$ the time, $\tau$
the time-constant.
For the increasing phases use an exponential of the form:
\begin{equation}
f_{A,\tau, y_0}(t) = y_0 + A \cdot \left(1 - e^{-\frac{t}{\tau}}\right ),
\end{equation}
\part Plot the best fits into the data.
\part Plot the estimated time-constants as a function of stimulus intensity.
\end{parts}
\end{questions}
\end{document}