\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}