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diff --git a/projects/project_onset_fi/data/p_unit_2012-03-30-aa_fi_curve_-14.mat b/projects/project_ficurves/data/p_unit_2012-03-30-aa_fi_curve_-14.mat
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diff --git a/projects/project_onset_fi/data/p_unit_2012-03-30-aa_fi_curve_-18.mat b/projects/project_ficurves/data/p_unit_2012-03-30-aa_fi_curve_-18.mat
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diff --git a/projects/project_onset_fi/data/p_unit_2012-03-30-aa_fi_curve_-2.mat b/projects/project_ficurves/data/p_unit_2012-03-30-aa_fi_curve_-2.mat
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diff --git a/projects/project_onset_fi/data/p_unit_2012-03-30-aa_fi_curve_-6.mat b/projects/project_ficurves/data/p_unit_2012-03-30-aa_fi_curve_-6.mat
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diff --git a/projects/project_onset_fi/data/p_unit_2012-03-30-aa_fi_curve_-9.mat b/projects/project_ficurves/data/p_unit_2012-03-30-aa_fi_curve_-9.mat
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diff --git a/projects/project_onset_fi/data/p_unit_2012-03-30-aa_fi_curve_12.mat b/projects/project_ficurves/data/p_unit_2012-03-30-aa_fi_curve_12.mat
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diff --git a/projects/project_onset_fi/data/p_unit_2012-03-30-aa_fi_curve_15.mat b/projects/project_ficurves/data/p_unit_2012-03-30-aa_fi_curve_15.mat
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diff --git a/projects/project_onset_fi/data/p_unit_2012-03-30-aa_fi_curve_5.mat b/projects/project_ficurves/data/p_unit_2012-03-30-aa_fi_curve_5.mat
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diff --git a/projects/project_onset_fi/data/p_unit_2012-03-30-aa_fi_curve_9.mat b/projects/project_ficurves/data/p_unit_2012-03-30-aa_fi_curve_9.mat
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diff --git a/projects/project_ficurves/ficurves.tex b/projects/project_ficurves/ficurves.tex
new file mode 100644
index 0000000..7bfba31
--- /dev/null
+++ b/projects/project_ficurves/ficurves.tex
@@ -0,0 +1,73 @@
+\documentclass[a4paper,12pt,pdftex]{exam}
+
+\newcommand{\ptitle}{F-I curves}
+\input{../header.tex}
+\firstpagefooter{Supervisor: Jan Grewe}{phone: 29 74588}%
+{email: jan.grewe@uni-tuebingen.de}
+
+\begin{document}
+
+\input{../instructions.tex}
+
+
+%%%%%%%%%%%%%% Questions %%%%%%%%%%%%%%%%%%%%%%%%%
+\section{Quantifying the responsiveness of a neuron by its F-I curves}
+The responsiveness of a neuron is often quantified using an F-I
+curve. The F-I curve plots the \textbf{F}iring rate of the neuron as a
+function of the stimulus \textbf{I}ntensity.
+
+\begin{questions}
+ \question In the accompanying datasets you find the
+ \textit{spike\_times} of an P-unit electroreceptor of the weakly
+ electric fish \textit{Apteronotus leptorhynchus} to a stimulus of a
+ certain intensity, i.e. the \textit{contrast}. The spike times are
+ given in milliseconds relative to the stimulus onset.
+ \begin{parts}
+ \part For each stimulus intensity estimate the average response
+ (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 Extract the neuron's activity for every 50\,ms after
+ stimulus onset and for one 50\,ms slice before stimulus onset.
+
+ For each time slice plot the resulting F-I curve by plotting the
+ computed firing rates against the corresponding stimulus
+ intensity, respectively the contrast.
+
+ \part Fit a Boltzmann function to each of the F-I-curves. The
+ Boltzmann function is a sigmoidal function and is defined as
+ \begin{equation}
+ f(x) = \frac{\alpha-\beta}{1+e^{-k(x-x_0)}}+\beta \; .
+ \end{equation}
+ $x$ is the stimulus intensity, $\alpha$ is the starting
+ firing rate, $\beta$ the saturation firing rate, $x_0$ defines the
+ position of the sigmoid, and $k$ (together with $\alpha-\beta$)
+ sets the slope.
+
+ Before you do the fitting, familiarize yourself with the four
+ parameter of the Boltzmann function. What is its value for very
+ large or very small stimulus intensities? How does the Boltzmann
+ function change if you change either of the parameter?
+
+ How could you get good initial estimates for the parameter?
+
+ Do the fits and show the resulting Boltzmann functions together
+ with the corresponding data.
+
+ \part Illustrate how the F-I curves change in time also by means
+ of the parameter you obtained from the fits with the Boltzmann
+ function.
+
+ Which parameter stay the same, which ones change with time?
+
+ Support your conclusion with appropriate statistical tests.
+
+ \part Discuss you results with respect to encoding of different
+ stimulus intensities.
+ \end{parts}
+\end{questions}
+
+\end{document}
diff --git a/projects/project_onset_fi/solution/boltzmannFit.m b/projects/project_ficurves/solution/boltzmannFit.m
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diff --git a/projects/project_onset_fi/solution/getFICurve.m b/projects/project_ficurves/solution/getFICurve.m
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diff --git a/projects/project_onset_fi/solution/main.m b/projects/project_ficurves/solution/main.m
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diff --git a/projects/project_onset_fi/solution/plotAverageResponse.m b/projects/project_ficurves/solution/plotAverageResponse.m
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diff --git a/projects/project_onset_fi/onset_fi.tex b/projects/project_onset_fi/onset_fi.tex
deleted file mode 100644
index 94be9b5..0000000
--- a/projects/project_onset_fi/onset_fi.tex
+++ /dev/null
@@ -1,47 +0,0 @@
-\documentclass[a4paper,12pt,pdftex]{exam}
-
-\newcommand{\ptitle}{Onset f-I curve}
-\input{../header.tex}
-\firstpagefooter{Supervisor: Jan Grewe}{phone: 29 74588}%
-{email: jan.grewe@uni-tuebingen.de}
-
-\begin{document}
-
-\input{../instructions.tex}
-
-
-%%%%%%%%%%%%%% Questions %%%%%%%%%%%%%%%%%%%%%%%%%
-\section{Quantifying the responsiveness of a neuron by its F-I curve}
-The responsiveness of a neuron is often quantified using an F-I
-curve. The F-I curve plots the \textbf{F}iring rate of the neuron as a
-function of the stimulus \textbf{I}ntensity.
-
-\begin{questions}
- \question In the accompanying datasets you find the
- \textit{spike\_times} of an P-unit electroreceptor of the weakly
- electric fish \textit{Apteronotus leptorhynchus} to a stimulus of a
- certain intensity, i.e. the \textit{contrast}. The spike times are
- given in milliseconds relative to the stimulus onset.
- \begin{parts}
- \part For each stimulus intensity estimate the average response
- (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 Extract the neuron's activity in the first 50\,ms after
- stimulus onset and plot it against the stimulus intensity,
- respectively the contrast, in an appropriate way.
- \part Fit a Boltzmann function to the FI-curve. The Boltzmann function
- is defined as:
- \begin{equation}
- y=\frac{\alpha-\beta}{1+e^{(x-x_0)/\Delta x}}+\beta,
- \end{equation}
- where $\alpha$ is the starting firing rate, $\beta$ the saturation
- firing rate, $x$ the current stimulus intensity, $x_0$ starting
- stimulus intensity, and $\Delta x$ a measure of the slope.
- \part Plot the fit into the data.
- \end{parts}
-\end{questions}
-
-\end{document}
diff --git a/projects/project_steady_state_fi/Makefile b/projects/project_steady_state_fi/Makefile
deleted file mode 100644
index a7b3726..0000000
--- a/projects/project_steady_state_fi/Makefile
+++ /dev/null
@@ -1,3 +0,0 @@
-ZIPFILES=
-
-include ../project.mk
diff --git a/projects/project_steady_state_fi/data/p_unit_2012-03-30-aa_fi_curve_-14.mat b/projects/project_steady_state_fi/data/p_unit_2012-03-30-aa_fi_curve_-14.mat
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diff --git a/projects/project_steady_state_fi/steady_state_fi.tex b/projects/project_steady_state_fi/steady_state_fi.tex
deleted file mode 100644
index abba436..0000000
--- a/projects/project_steady_state_fi/steady_state_fi.tex
+++ /dev/null
@@ -1,45 +0,0 @@
-\documentclass[a4paper,12pt,pdftex]{exam}
-
-\newcommand{\ptitle}{Steady-state f-I curve}
-\input{../header.tex}
-\firstpagefooter{Supervisor: Jan Grewe}{phone: 29 74588}%
-{email: jan.grewe@uni-tuebingen.de}
-
-\begin{document}
-
-\input{../instructions.tex}
-
-
-%%%%%%%%%%%%%% Questions %%%%%%%%%%%%%%%%%%%%%%%%%
-\section*{Quantifying the responsiveness of a neuron using the F-I curve.}
-The responsiveness of a neuron is often quantified using an F-I
-curve. The F-I curve plots the \textbf{F}iring rate of the neuron as a function
-of the stimulus \textbf{I}ntensity.
-
-\begin{questions}
- \question In the accompanying datasets you find the
- \textit{spike\_times} of an P-unit electrorecptor of the weakly
- electric fish \textit{Apteronotus leptorhynchus} to a stimulus of a
- certain intensity, i.e. the \textit{contrast}. The contrast is also
- part of the file name itself.
- \begin{parts}
- \part Estimate for each stimulus intensity the average response
- (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 Extract the neuron's activity in the last 200 ms before
- stimulus offset and plot it against the stimulus intensity or the
- contrast, respectively.
- \part Fit a Boltzmann function to the FI-curve. The Boltzmann function
- is defined as:
- \begin{equation}
- y=\frac{\alpha-\beta}{1+e^{(x-x_0)/\Delta x}}+\beta,
- \end{equation}
- where $\alpha$ is the starting firing rate, $\beta$ the saturation
- firing rate, $x$ the current stimulus intensity, $x_0$ starting
- stimulus intensity, and $\Delta x$ a measure of the slope.
- \end{parts}
-\end{questions}
-
-\end{document}