[projects] minor fixes, change supervisor for some projects

projects/project_adaptation_fit/adaptation_fit.tex

@@ -2,8 +2,8 @@
 
 \newcommand{\ptitle}{Adaptation time-constant}
 \input{../header.tex}
-\firstpagefooter{Supervisor: Jan Grewe}{phone: 29 74588}%
-{email: jan.grewe@uni-tuebingen.de}
+\firstpagefooter{Supervisor: Lukas Sonnenberg}{phone:}%
+{email: lukas.sonnenberg@uni-tuebingen.de}
 
 \begin{document}
 

projects/project_eod/eod.tex

@@ -56,8 +56,4 @@ multiples of the fundamental frequency).
   \end{parts}
 \end{questions}
 
-
-
-
-
 \end{document}

projects/project_eyetracker/eyetracker.tex

@@ -24,7 +24,7 @@ The eyetracker recorded ey positions with 60\,Hz. The fixation point was shown a
 \begin{questions}
   \question Familiarize yourself with the data.
   \begin{parts}
-    \part Cut the data in chunks belonging to the same period (fixation and free eye-movements).
+    \part Cut the data into chunks belonging to the same period (fixation and free eye-movements).
     \part Detect problems in the data (e.g. the eye was not found) and correct the eye traces. Interpolate linearily in these sections. 
   \end{parts}
 
@@ -35,7 +35,7 @@ The eyetracker recorded ey positions with 60\,Hz. The fixation point was shown a
     \part Detect fixation points in the "free movement" part of the data.
   \end{parts}
 
-  \question Compare the subject's behaviour when viewing the different scenes.
+  \question Compare the subject's behavior when viewing the different scenes.
 \end{questions}
 
 \end{document}

projects/project_ficurves/ficurves.tex

@@ -2,8 +2,8 @@
 
 \newcommand{\ptitle}{f-I curves}
 \input{../header.tex}
-\firstpagefooter{Supervisor: Jan Benda}{phone: 29 74573}%
-{email: jan.benda@uni-tuebingen.de}
+\firstpagefooter{Supervisor: Jan Grewe}{phone: 29 74588}%
+{email: jan.grewe@uni-tuebingen.de}
 
 \begin{document}
 

projects/project_photoreceptor/photoreceptor.tex

@@ -12,16 +12,15 @@
 
 %%%%%%%%%%%%%% Questions %%%%%%%%%%%%%%%%%%%%%%%%%
 \section*{Light responses of an insect photoreceptor.}
-In this project you will analyze data from intracellular recordings of
-a fly R\,1--6 photoreceptor. These cells show graded membrane
-potential changes in response to a light stimulus. The membrane
-potential of the photoreceptor was recorded while the cell was
-stimulated with a light stimulus.
+Fly R\,1--6 photoreceptors respond to light-on stimuli with graded membrane
+potential changes. In the acompanying datasets you find the membrane
+potential of a single R\,1-6 photoreceptor that was recorded while the receptor was
+stimulated with a light stimulus of different amplitudes.
 
 \begin{questions}
   \question{} The accompanying dataset (photoreceptor\_data.zip)
   contains seven mat files. Each of these holds the data from one
-  stimulus intensity and contains therr variables.  (i)
+  stimulus intensity and contains three variables. (i)
   \textit{voltage} a matrix with the recorded membrane potential from
   10 consecutive trials, (ii) \textit{time} a matrix with the
   time-axis for each trial, and (iii) \textit{trace\_meta} a structure
@@ -36,8 +35,8 @@ stimulated with a light stimulus.
     the individual responses as a function of time.
 
     \part Intracellular recordings often suffer from drifts in the resting
-    potential. This leads to a large variability in the responses which is technical and not a cellular
-    property. To compensate for such drifts trials are aligned to the
+    potential. This leads to a large variability in the responses which has technical reasons and is not a cellular
+    property. To compensate for such drifts trials usually are aligned to the
     resting potential before stimulus onset.
     Replot the data but with the compensation for the drifts.
     
@@ -46,9 +45,9 @@ stimulated with a light stimulus.
     
     \part You will notice that the responses have three main parts, (i) a
     pre-stimulus phase, (ii) the phase in which the light was on, and (iii)
-    a post-stimulus phase. Create an characteristic curve that
+    a post-stimulus phase. The light-on phase can further be devided into two parts, the onset, and the "steady state" response part. Create an characteristic curve that
     plots the response strength as a function of the stimulus
-    intensity for the ``onset'' and the ``steady state''
+    intensity for ``onset'' and ``steady state''
     phases of the light response.
 
     \part The light switches on at time zero. Estimate the delay

projects/project_random_walk/random_walk.tex

@@ -2,8 +2,8 @@
 
 \newcommand{\ptitle}{Random walk}
 \input{../header.tex}
-\firstpagefooter{Supervisor: Jan Grewe}{phone: 29 74588}%
-{email: jan.grewe@uni-tuebingen.de}
+\firstpagefooter{Supervisor: Lukas Sonnenberg}{phone:}%
+{email: lukas.sonnenberg@uni-tuebingen.de}
 
 \begin{document}
 
@@ -51,4 +51,4 @@ a random walk and changes directions randomly.
   \end{parts}
 \end{questions}
 
-\end{document}
+\end{document}

projects/project_stimulus_reconstruction/stimulus_reconstruction.tex

@@ -11,27 +11,29 @@
 
 %%%%%%%%%%%%%% Questions %%%%%%%%%%%%%%%%%%%%%%%%%
 \section*{Reverse reconstruction of the stimulus that evoked a neuronal response.}
-To analyse the encoding properties of a neuron one often calculates the
-Spike-Triggered-Average (STA). The STA is the average stimulus that
+When analyzing neuronal responses we want to figure out which aspects of the stimulus are actually encoded in the neuronal response.
+One way to do this is to calculate the
+Spike-Triggered-Average (STA) and use it to reversely estimate which aspects of the stimulus are encoded in the resopnse.
+
+The STA is the average stimulus that
 led to a spike in the neuron:
 \[ STA(\tau) = \frac{1}{n} \displaystyle\sum_{i=1}^{n}{s(t_i - \tau)} \]
 where $n$ is the number of spikes and $t_i$ is the time of the
 $i_{th}$ spike. $\tau$ is a temporal shift relative to the spike
-time. For the beginning let $\tau$ assume values in the range
-$\pm50$\,ms. The STA can be estimated by cutting out snippets from the
+time. 
+
+Another approach to understand the equation is to cut out snippets from the
 stimulus that are centered on the respective spike time and by
-subsequently averaging these stimulus snippets. The STA can be used to
-reconstruct the stimulus from the neuronal response (reverse
-reconstruction). The reconstructed stimulus can then be compared to
-the original stimulus and provides a good impression about the
-features that are encoded in the neuronal response.
+subsequently averaging these stimulus snippets.
+
+
 
 \begin{questions}
   \question In the accompanying data files you find the spike
   responses of a p-type electroreceptor afferent (P-unit) and a
   pyramidal neuron recorded in the hindbrain of the weakly electric
   fish \textit{Apteronotus leptorhynchus}. The respective stimuli are
-  stored in separate files. The neron is stimulated with an amplitude
+  stored in separate files. The neuron is stimulated with an amplitude
   modulation of the fish's own electric field. The stored stimulus
   trace is the modulator that is applied to the field and is
   dimensionless, i.e. it has no unit. The data is sampled with
@@ -39,7 +41,15 @@ features that are encoded in the neuronal response.
   seconds. Start with the P-unit and, in the end, apply the same
   analyzes/functions to the pyramidal cell.
   \begin{parts}
-    \part Estimate the STA and plot it. What does it tell?
+    \part Familiarize yourself with the cellular responses and the stimulus. 
+    \part Estimate the STA and plot it. For the beginning let $\tau$ assume values in the range 
+    $\pm50$\,ms. What does it tell? 
+  \end{parts}
+  \question The STA can be used to reconstruct the stimulus from the neuronal response (reverse
+  reconstruction) by convolution of the spiking response with the STA. The reconstructed stimulus can then be compared to
+  the original stimulus and provides a good impression about the
+  features that are encoded in the neuronal response.
+  \begin{parts}
     \part Implement a function that does the reverse reconstruction and uses the STA to reconstruct the stimulus.
     \part Implement a function that estimates the reconstruction quality.
     \part Test the robustness of the reconstruction: Estimate