From 10f71d5661696996564d9300da0f8a2a8c9b9761 Mon Sep 17 00:00:00 2001
From: Jan Benda <jan.benda@uni-tuebingen.de>
Date: Sat, 9 Jan 2021 19:55:54 +0100
Subject: [PATCH] [likelihood] updated exercise

---
 likelihood/exercises/likelihood-1.tex |  3 +++
 likelihood/lecture/likelihood.tex     | 22 +++++++++++-----------
 2 files changed, 14 insertions(+), 11 deletions(-)

diff --git a/likelihood/exercises/likelihood-1.tex b/likelihood/exercises/likelihood-1.tex
index 28b3946..c0b7f3d 100644
--- a/likelihood/exercises/likelihood-1.tex
+++ b/likelihood/exercises/likelihood-1.tex
@@ -15,6 +15,9 @@
 
 \begin{questions}
 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 
+\question \qt{Read chapter 9 on ``Maximum likelihood estimation''!}\vspace{-3ex}
+
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 \question \qt{Maximum likelihood of the standard deviation}
 Let's compute the likelihood and the log-likelihood for the estimation
diff --git a/likelihood/lecture/likelihood.tex b/likelihood/lecture/likelihood.tex
index ea0cfd4..255ddd5 100644
--- a/likelihood/lecture/likelihood.tex
+++ b/likelihood/lecture/likelihood.tex
@@ -411,17 +411,6 @@ analysis. Neural systems face the very same problem. They also need to
 estimate parameters of the internal and external environment based on
 the activity of neurons.
 
-In sensory systems certain aspects of the environment are encoded in
-the neuronal activity of populations of neurons. One example of such a
-population code is the tuning of neurons in the primary visual cortex
-(V1) to the orientation of a bar in the visual stimulus. Different
-neurons respond best to different bar orientations. Traditionally,
-such a tuning is measured by analyzing the neuronal response strength
-(e.g. the firing rate) as a function of the orientation of a black bar
-and is illustrated and summarized with the so called
-\enterm{tuning-curve} (\determ{Abstimmkurve},
-figure~\ref{mlecodingfig}, top).
-
 \begin{figure}[tp]
   \includegraphics[width=1\textwidth]{mlecoding}
   \titlecaption{\label{mlecodingfig} Maximum likelihood estimation of
@@ -440,6 +429,17 @@ figure~\ref{mlecodingfig}, top).
     orientation.}
 \end{figure}
 
+In sensory systems certain aspects of the environment are encoded in
+the neuronal activity of populations of neurons. One example of such a
+population code is the tuning of neurons in the primary visual cortex
+(V1) to the orientation of a bar in the visual stimulus. Different
+neurons respond best to different bar orientations. Traditionally,
+such a tuning is measured by analyzing the neuronal response strength
+(e.g. the firing rate) as a function of the orientation of a black bar
+and is illustrated and summarized with the so called
+\enterm{tuning-curve} (\determ{Abstimmkurve},
+figure~\ref{mlecodingfig}, top).
+
 The brain, however, is confronted with the inverse problem: given a
 certain activity pattern in the neuronal population, what is the
 stimulus? In our example, what is the orientation of the bar? In the