diff --git a/projects/project_stimulus_reconstruction/Makefile b/projects/project_stimulus_reconstruction/Makefile
new file mode 100644
index 0000000..dad25ce
--- /dev/null
+++ b/projects/project_stimulus_reconstruction/Makefile
@@ -0,0 +1,10 @@
+latex:
+	pdflatex *.tex > /dev/null
+	pdflatex *.tex > /dev/null
+
+clean:
+	rm -rf *.log *.aux *.zip *.out auto
+	rm -f `basename *.tex .tex`.pdf
+
+zip: latex
+	zip `basename *.tex .tex`.zip *.pdf *.dat *.mat
diff --git a/projects/project_stimulus_reconstruction/stimulus_reconstruction.tex b/projects/project_stimulus_reconstruction/stimulus_reconstruction.tex
new file mode 100755
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+++ b/projects/project_stimulus_reconstruction/stimulus_reconstruction.tex
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+\documentclass[addpoints,11pt]{exam}
+\usepackage{url}
+\usepackage{color}
+\usepackage{hyperref}
+
+\pagestyle{headandfoot}
+\runningheadrule
+\firstpageheadrule
+\firstpageheader{Scientific Computing}{Project Assignment}{11/05/2014
+  -- 11/06/2014}
+%\runningheader{Homework 01}{Page \thepage\ of \numpages}{23. October 2014}
+\firstpagefooter{}{}{}
+\runningfooter{}{}{}
+\pointsinmargin
+\bracketedpoints
+
+%\printanswers
+%\shadedsolutions
+
+
+\begin{document}
+%%%%%%%%%%%%%%%%%%%%% Submission instructions %%%%%%%%%%%%%%%%%%%%%%%%%
+\sffamily
+% \begin{flushright}
+% \gradetable[h][questions]
+% \end{flushright}
+
+\begin{center}
+  \input{../disclaimer.tex}
+\end{center}
+
+%%%%%%%%%%%%%% Questions %%%%%%%%%%%%%%%%%%%%%%%%%
+\section*{Reverse reconstruction of the stimulus evoking neuronal responses.}
+During the course we have used the Spike-Triggered-Average to
+reconstruct the stimulus
+\begin{questions}
+  \question .
+  \begin{parts}
+    \part Estimate the STA and plot it for each of the cells.
+    \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}),
+    \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 data 
+    amount used to estimate the STA.
+    \part Apply the STA estimated for one neuron to reconstruct 
+    the stimulus another neuron has seen.
+  \end{parts}
+\end{questions}
+
+\end{document}