  This tutorial describes challenges and possible avenues for the
implementation of the components of a solid-state system, which emulates a
biological brain. The tutorial is devoted mostly to a charge-based (i.e.
electric controlled) implementation using transition metal oxides materials,
which exhibit unique properties that emulate key functionalities needed for
this application. In the Introduction, we compare the main differences between
a conventional computational machine, based on the Turing-von Neumann paradigm,
to a Neuromorphic machine, which tries to emulate important functionalities of
a biological brain. We also describe the main electrical properties of
biological systems, which would be useful to implement in a charge-based
system. In Chapter II, we describe the main components of a possible
solid-state implementation. In Chapter III, we describe a variety of Resistive
Switching phenomena, which may serve as the functional basis for the
implementation of key devices for Neuromorphic computing. In Chapter IV we
describe why transition metal oxides, are promising materials for future
Neuromorphic machines. Theoretical models describing different resistive
switching mechanisms are discussed in Chapter V while existing implementations
are described in Chapter VI. Chapter VII presents applications to practical
problems. We list in Chapter VIII important basic research challenges and open
issues. We discuss issues related to specific implementations, novel materials,
devices and phenomena. The development of reliable, fault tolerant, energy
efficient devices, their scaling and integration into a Neuromorphic computer
may bring us closer to the development of a machine that rivals the brain.
