diff --git a/projects/project_face_selectivity/face_selectivity.tex b/projects/project_face_selectivity/face_selectivity.tex
index 6e5f7ae..512c5aa 100644
--- a/projects/project_face_selectivity/face_selectivity.tex
+++ b/projects/project_face_selectivity/face_selectivity.tex
@@ -16,20 +16,21 @@
 
 In the temporal lobe of primates you can find neurons that respond
 selectively to a certain type of object category. You may have heard
-stories about the famous grandmother neurons which are supposed to
-respond exclusively when the subject perceives a particular
-person. Even though the existence of a grandmother neuron in the
+about the famous grandmother neuron which is supposed to respond
+exclusively when the subject sees a particular person, i.e. the
+grandmother. Even though the existence of a grandmother neuron in the
 strict sense is implausible, the concept exemplifies the observation
 that sensory neurons within the ventral visual stream are tuned to
-certain stimuli types. One of the most important and first visual
-stimulus the newborn typically perceives is the mother's face. It is
+certain stimulus types. One of the most important and first visual
+stimulus the newborn typically sees is the mother's face. It is
 believed that the early ubiquity of faces and their importance for
 social interactions triggers the development of the so called
-face-patch system within the temporal lobe of primates.\par
-Your task here will be to estimate the \textit{selectivity index}
-($SI$) of neurons that were recorded in the superior temporal sulcus
-of a rhesus monkey during the visual presentation of objects of different
-categories.
+face-patch system within the temporal lobe of primates.\par Your task
+here will be to estimate the \textit{face selectivity index} ($FSI$)
+of neurons that were recorded in the superior temporal sulcus of a
+rhesus monkey during the visual presentation of objects of different
+categories (data courtesy of the Sensorymotor-Lab, Hertie
+Institute).
 
 
 \begin{questions}
@@ -66,8 +67,8 @@ categories.
     this individually for each trial and average afterwards in order
     to obtain the standard deviation of the firing rates. Plot the
     firing rates and their standard deviations on top of the raster
-    plots. Which of the methods appears to be a better representation
-    of the spike rasters?
+    plots. Which of the methods appears best to represent
+    the spiking activity seen in the raster plots?
 
   \part
     Generate figures that show for each neuron the firing rates
@@ -79,17 +80,17 @@ categories.
     modulations.
     % First, normalize each response to baseline activity
     % (first 400 ms). Why is the normalization useful?
-    % \par
-    Now, determine the periods within which the neurons activity
-    deviates from the baseline activity at least by $2*\sigma$. Do
-    this for each object category and mark the periods in the plots in
-    an appropriate way. Are there also neurons that do not repond to
-    the visual stimulation or exhibit inhibitory responses? \par
+    % \par Now, determine the periods within which the neurons
+    activity deviates from the baseline activity at least by
+    $2*\sigma$. Do this for each object category and mark the periods
+    in the plots in an appropriate way. Are there neurons that do not
+    repond to the visual stimulation or exhibit inhibitory responses?
+    \par
     
 
   \part
-    The $SI$ gives an estimate of how strong a neuron is tuned to the
-    chosen object categories. It is given by the neurons response
+    The $FSI$ gives an estimate of how strongly a neuron is tuned to
+    the chosen object categories. It is given by the neuron's response
     during the presentation of the one category compared to the other
     category.
     \begin{equation}
@@ -97,33 +98,34 @@ categories.
             to category B}} } { \mu_{\text{Response to category A}} + \mu_{ \text{Response
             to category B} } }
     \end{equation}
-    $SI$ can take values between -1 and 1 which indicates tuning to
+    $FSI$ can take values between -1 and 1 which indicates tuning to
     the one or to the other category. There are different
     possibilities of how it can be estimated. The easiest way would be
     to average the spike count during the whole time of stimulus
     presentation. However, if responses are phasic you will
-    underestimate the $SI$. Therefor, you should limit the estimate to
-    periods of significant modulations. Use the periods determined in
-    (d). Store all obtained $SI$s within one variable. We are mainly
-    interested to identify face-selective neurons but feel free to
-    test the neurons for selectivity to other categories, as well.
+    underestimate the $FSI$. Therefore, you should limit the estimate
+    to periods of significant modulations. Use the periods determined
+    in (d). Store all obtained $FSI$s within a single variable. We are
+    mainly interested in identifying face-selective neurons but feel
+    free to test the neurons for selectivity to other categories, as
+    well.
     
   \part
-    Plot the distribution of $SI$ values and describe it
+    Plot the distribution of $FSI$ values and describe it
     qualitatively. Does it indicate a continuum or a distinct
-    population of face-selective neurons. \par
-    Think about a statistical test that tells you whether a given
-    neuron is significantly modulated by one or the other category
-    (try different combinations of categories). List cells that show
-    significant modulation to faces and non-faces. Which is the
-    minimum SI that reaches significance when choosing
-    $\alpha = 0.05$? Is it an all or nothing selectivity?
+    population of face-selective neurons. \par Think about a
+    statistical test that tells you whether a given neuron is
+    significantly modulated by one or the other category (try
+    different combinations of categories). List cells that show
+    significant modulations to faces and non-faces. Which is the
+    minimum $FSI$ that reaches significance when choosing $\alpha =
+    0.05$? Is it an all or nothing selectivity?
     
   \part 
     Take a look at the time resolved firing rates of the identified
     face-selective neurons and examine their response properties. What
-    is their response-latency (choose an appropriate visualisation),
-    is their response phasic or tonic.
+    are their response-latencies (choose an appropriate
+    visualisation), are their responses phasic or tonic.
 
   \end{parts}
 \end{questions}
diff --git a/projects/project_pca_natural_images/pca_natural_images.tex b/projects/project_pca_natural_images/pca_natural_images.tex
index c82c625..75207e5 100644
--- a/projects/project_pca_natural_images/pca_natural_images.tex
+++ b/projects/project_pca_natural_images/pca_natural_images.tex
@@ -27,6 +27,9 @@ In you zip file you find a natural image called {\tt natimg.jpg}.
   \question What could be the biological significance of that (\cite{BG} can
   give you a clue)?
 
+  \question How could you transform the picture to match the true
+  representation in the retina (S-, M-, L- cones)?
+
 \end{questions}
 
 \begin{thebibliography}{1}