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main.tex
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\documentclass[a4paper, 12pt]{article}
\usepackage{amsmath}
\usepackage{amssymb}
\usepackage{cases}
\usepackage{color}
\usepackage{empheq}
\usepackage[english]{babel}
\usepackage{enumerate}
\usepackage{enumitem}
\usepackage{epstopdf}
\usepackage{fancyhdr}
\usepackage{float}
\usepackage{gensymb}
\usepackage{graphicx}
\usepackage{hyperref}
\usepackage{ifthen}
\usepackage{listings}
\usepackage[miktex]{gnuplottex}
\usepackage{subcaption}
\usepackage{subfiles}
\usepackage{textcomp}
\usepackage{tikz}
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\usepackage[utf8]{inputenc}
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\graphicspath{{./images/}}
\title{\textbf{Introduction to Neuroinformatics} \\Summary of the lectures
2019\\\normalsize Version 5.0 \\
for internal use by students attending the lecture only}
\author{
\texttt{Initial Version 2012}\\
Benjamin Ellenberger
\and
\texttt{Revision 2013}\\
Joachim Ott\\Dora Sumislawska
\and
\texttt{Revision 2014}\\
Fabian Tschopp
\and
\texttt{Revision 2018 and 2019}\\
Vanessa Leite
\and
\texttt{Revision 2020}\\
Karla Burelo\\ Nicoletta Risi\\ Vanessa Leite}
\date{}
\begin{document}
\maketitle
\newpage
\tableofcontents
\newpage
\newpage
\subfile{01-introduction.tex}
\subfile{02-nervous-system-organization.tex}
\subfile{03-membrane-potential.tex}
\subfile{04-passive-membrane-properties.tex}
\subfile{05-action-potential.tex}
\subfile{06-rate-event-code.tex}
\subfile{07-synapse-I.tex}
\subfile{08-synapse-II.tex}
\subfile{09-plasticity.tex}
\subfile{10-neuromorphic.tex}
\subfile{11-perceptron-learning-algorithm.tex}
\subfile{12-hopfield-networks.tex}
\subfile{14-feedforward-networks.tex}
\subfile{13-neural-populations.tex}
\newpage
\subsection{References}
The pictures used in this summary are from the following books and slide sets and belong to their respective owners.
In the context of the summary they are used for educational purposes only.
\begin{itemize}
\item D. Purves et al.: Neuroscience. Fifth edition. Sinauer
\item Squire, Berg, Bloom, du Lac, Ghosh \& Spitzer: Fundamental Neuroscience. Elsevier
\item Eric Kandel et al.: Principles of Neural Science. Fifth edition.
McGraw-Hill
\item Peter Dayan, L. F. Abbott: Theoretical Neuroscience, The MIT
Press
\item Christof Koch: Biophysics of Computation. Oxford University Press
\item John Nicholls et al.: From Neuron to Brain. Palgrave Macmillan
\item W. Gerstner et al.: Neuronal Dynamics. From Single Neurons to Networks and Models of Cognition. Cambridge University Press (2014).
\item Hertz, Krogh, Palmer: Introduction to the Theory of Neural Computation.
Westview Press
\item Bishop: Pattern Recognition and Machine Learning. Springer
\item The lecture slides of the Introduction to Neuroinformatics course of the years 2012, 2013, 2014, 2018 and 2019.
\end{itemize}
\end{document}