[projects] imrpoved population vector

projects/project_populationvector/populationvector.tex

@@ -47,19 +47,19 @@
     200\,ms. The resulting curves are the tuning curves $r(\varphi)$
     of the neurons.
 
-    \part Fit the function \[ r(\varphi) =
-    g(1+\cos(2(\varphi-\varphi_0)))/2 \] to the measured tuning curves in
-    order to estimated the orientation angle at which the neurons
-    respond strongest. In this function $\varphi_0$ is the position of
-    the peak and $g$ is a gain factor that sets the maximum firing
-    rate.
+    \part Fit the function \[ r(\varphi) = g \cdot
+    (1+\cos(2(\varphi-\varphi_0)))/2 + a \] to the measured tuning
+    curves in order to estimated the orientation angle at which the
+    neurons respond strongest. In this function $\varphi_0$ is the
+    position of the peak, $g$ is a gain factor that sets the
+    modulation depth of the firing rate, and $a$ is an offset.
 
     \part How can the orientation angle of the presented bar be read
     out from one trial of the population activity of the 6 neurons?
-    One is the so called ``population vector'' where unit vectors
-    pointing into the direction of the maximum response of each neuron
-    are weighted by their firing rate. The stimulus orientation is
-    then the direction of the averaged vectors.  
+    One possible method is the so called ``population vector'' where
+    unit vectors pointing into the direction of the maximum response
+    of each neuron are weighted by their firing rate. The stimulus
+    orientation is then the direction of the averaged vectors.
 
     %Think of another (simpler) method how the orientation of the bar
     %may be approximately read out from the population.