This repository has been archived on 2021-05-17. You can view files and clone it, but cannot push or open issues or pull requests.
scientificComputing/projects/project_adaptation_fit/adaptation_fit.tex

66 lines
2.6 KiB
TeX

\documentclass[a4paper,12pt,pdftex]{exam}
\newcommand{\ptitle}{Adaptation time-constant}
\input{../header.tex}
\firstpagefooter{Supervisor: Lukas Sonnenberg}{phone:}%
{email: lukas.sonnenberg@uni-tuebingen.de}
\begin{document}
\input{../instructions.tex}
Stimulating a neuron with a constant stimulus for an extended period
of time often results in a decay of an initially strong response. This
process is called adaptation. 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 and is given in percent. The data is sampled
with 20\,kHz sampling frequency and spike times are given in
milliseconds (not seconds!) relative to stimulus onset.
\begin{parts}
\part Plot spike rasters of the data.
\part Estimate for each stimulus intensity the PSTH. 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. Find an appropriate bin-width
for the PSTH.
\part Estimate the adaptation time-constant for both the stimulus
on- and offset. To do this, fit an exponential function
$f_{A,\tau,y_0}(t)$ to appropriate regions of the data:
\begin{equation}
f_{A,\tau,y_0}(t) = A \cdot e^{-\frac{t}{\tau}} + y_0,
\end{equation}
where $t$ is time, $A$ the (positive or negative) amplitude of the
exponential decay, $\tau$ the adaptation time-constant, and $y_0$
an offset.
Before you do the fitting, familiarize yourself with the three
parameter of the exponential function. What is the value of
$f_{A,\tau,y_0}(t)$ at $t=0$? What is the value for large times? How does
$f_{A,\tau,y_0}(t)$ change if you change either of the parameter?
Which of the parameter could you directly estimate from the data
(without fitting)?
How could you get good estimates for the other parameter?
Do the fit and show the resulting exponential function together
with the data.
\part Do the estimated time-constants depend on stimulus intensity?
Use an appropriate statistical test to support your observation.
\end{parts}
\end{questions}
\end{document}