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scientificComputing/projects/project_stimulus_reconstruction/stimulus_reconstruction.tex

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\documentclass[a4paper,12pt,pdftex]{exam}
\newcommand{\ptitle}{Reverse reconstruction}
\input{../header.tex}
\firstpagefooter{Supervisor: Jan Grewe}{phone: 29 74588}%
{email: jan.grewe@uni-tuebingen.de}
\begin{document}
\input{../instructions.tex}
%%%%%%%%%%%%%% Questions %%%%%%%%%%%%%%%%%%%%%%%%%
\section*{Reverse reconstruction of the stimulus that evoked a neuronal response.}
To analyse encoding properties of a neuron one often calculates the
Spike-Triggered-Average (STA). The STA is the average stimulus that
led to a spike in the neuron and is calculated by cutting out snippets
form the stimulus centered on the respective spike time:
\[ STA(\tau) = \frac{1}{n} \displaystyle\sum_{i=1}^{n}{s(t_i - \tau)} \],
where $n$ is the number of trials and $t_i$ is the time of the
$i_{th}$ spike. The Spike-Triggered-Average can be used to reconstruct
the stimulus from the neuronal response. The reconstructed stimulus
can then be compared to the original stimulus.
\begin{questions}
\question In the accompanying files you find the spike responses of
a p-type electroreceptor afferent (P-unit) and a pyramidal neurons
recorded in the hindbrain of the weakly electric fish
\textit{Apteronotus leptorhynchus}. The respective stimuli are
stored in separate files. The data is sampled with 20\,kHz temporal
resolution and spike times are given in seconds. Start with the
P-unit and, in the end, apply the same analyzes/functions to the
pyramidal data.
\begin{parts}
\part Estimate the STA and plot it.
\part Implement a function that does the reverse reconstruction and uses the STA to recopnstruct the stimulus.
\part Implement a function that estimates the reconstruction
error using the mean-square-error and express it relative to the
variance of the original stimulus.
\begin{equation}
err = \frac{1}{N} \cdot \displaystyle\sum^{N}_{i=1}(x_i - \bar{x})^2,
\end{equation}
with $N$ the number of data points, $x_i$ the current value and
$\bar{x}$, the average of all $x$.
\part Analyze the robustness of the reconstruction: Estimate
the STA with less and less data and estimate the reconstruction
error.
\part Plot the reconstruction error as a function of the amount of data
used to estimate the STA.
\part Repeat the above steps for the pyramidal neuron, what do you
observe?
\end{parts}
\end{questions}
\end{document}