1.2. What we have already known about the brain at the time when first
artificial neural network were build?
(Translation by Stefan Turalski, stefan.turalski@gmail.com)
The brain internals have always fascinated people. However, despite of many years of intensive research, until
now, we have failed to completely explain and understand a mystery of brain working. Only during last few
years we have seen essential progress in this area (we will elaborate more on this subject in the next subchapter).
Whereas in the 90ties of 20th century, when the rapid development of the basis of neural networks took place,
there was relatively less information on this (brain) subject. At that time we have already known where the most
important centres responsible for the crucial motor, perception and intellectual functions are located (fig 1.2).
Fig. 1.2 Localization of particular functions in a brain (source of the image:
http://avm.ucsf.edu/patient_info/WhatIsAnAVM/images/image015.gif )
However knowledge about particular brain elements working was rather vague. It was quite clear, how brain
parts responsible for movement controlling or essential sensations (somatosensory) work (fig 1.3), because
numerous diseases, injuries or war wounds let to determine, which movement (paralysis) or sensation defects
are associated with injury of particular brain parts.
Fig. 1.3. Main localizations of brain functions (source: http://www.neurevolution.net/wpcontent/uploads/primarycortex1_big.jpg )
The question about the nature and localisation of more advanced psychological activities inevitably leaded, on
this still quite primitive stage of knowledge. Main observation was that there seems to exist fairly well-defined
specialisation of individual cerebral hemispheres (fig 1.4). Main reason for that situation was a fact that ethical
considerations did not allow to carry out experimental tests on human brain. The afore mentioned practice of
industrious gathering and analysing of all information regarding the relationship between functional,
psychological and morphological changes that are observed in feelings and behaviour of people with particular
brain injury, caused in natural reason (not related to the research itself) was accepted. However a purposeful
manipulation of electrode or scalpel in a tissue of healthy brain in order to gather information about the
particular part functions was an entirely different matter.
Fig. 1.4. Generalized differences between main parts of a brain (source:
http://www.ucmasnepal.com/uploaded/images/ucmas_brain.jpg )
Of course, it was possible to curry out experiments on animals, and it was done very often. However, killing
innocent animals in the name of our curiosity has always been rather morally ambiguous status, even if dictated
by noble interest of a scientist. In addition to that, it was not possible to draw conclusions about human brain
behaviours and properties directly from the animal tests, mainly because in this research area the distance
between us and animals is rather more significant than in case of muscle, heart or blood researches.
What means did the pioneering neural network creators have to equip their constructions in as many features
and properties modelled on the real and natural brain working as possible?
First of all, they knew that brain consists of separate cells (neurons), which are playing a role of natural
processors. The first to describe human brain as a network of connected, however rather autonomous elements,
was the Spanish histologist Ramón y Cajal (Nobel laureate in 1906 – see table in foreword). It was also he who
introduced the concept of neurons, specialised cells that process information, receive and analyse sensations,
and generate and send control signals to all these human body parts that are managed by the brain (i.e. muscles
steering body movement, glands and all other internal organs). We will learn more about a structure of a neuron
in the 2th chapter, because its artificial equivalent is the main component of neural network structures that are
considered in that chapter. On the figure1.5, we can see how, the individual neuron was isolated from
continuous web of neurons that form cerebral cortex. As it was mentioned before, this autonomous cell is a
complex biological processor responsible for all functions and actions of our nervous system (in fact, not only
the brain, but also e.g. elements of sympathetic and parasympathetic nervous system that manages the activity of
all internal organs).
Fig. 1.5. Part of a brain cortex treated as neural network with selected neuron presentation
At the moment when first neural networks were build, the knowledge about neurons was quite distinctive,
thanks to some animal species (for example Loligio squid). These are big enough to allow clever researchers
(Hodgkin and Huxley – Noble price in 1963) to find out biochemical and bioelectrical changes that happens
during distribution and processing of nervous information carrier signals. However, the crucial statement was
that the description of real neuron (in substance, quite complex) could be simplified significantly, by a reduction
of observed information processing rules to several simple relations (these are described in the 2th chapter).
Such an extremely simplified neuron (presented diagrammatically on the figure 6), still allows to create
networks that have intresting and useful properties, which are at the same time very cheap to build.
Fig. 1.6. Simplified scheme of artificial neuron
Elements recorded on the figure 1.6 (especially mysterious ‘weights; marked inside the block symbolizing
neuron) will be discussed in detail in the following chapters, therefore please ignore these for now. However,
please note that a natural neuron has extremely reach and diverse construction (compare to the figure1.7). Its
technical equivalent, presented on the figure 1.6 has substantially cut down structure and is even more greatly
simplified in the area of activities that it is capable of. Despite all of that, we can, with the help of artificial
neural networks), obtain such complex and interesting behaviours, as these that you will find described in
further chapters of this book. It is amazing, how rich and varied are the abilities of the original, biologic network
that assembles our brain!
Fig. 1.7. A artistic view of biological neural cell (source: http://www.webbooks.com/eLibrary/Medicine/Physiology/Nervous/neuron.jpg )
The neuron presented on the figure 1.7 is a product of a graphic fantasy, whereas on the figure 1.8 you can see
an example of a real neural cell dissected free from a rat brain – human neurons look almost identically. Such a
biological neuron has really complex structure, hasn’t it?
Fig. 1.8. Real view of the biological neurons (from the brain of rat) (source:
http://flutuante.files.wordpress.com/2009/08/rat-neuron.png )
Because of the fact that artificial neurons are so simplified, it is possible to realize them technically in an easy
and cheap form of uncomplicated electronic system (first neural networks were built as specialised electronic
machines called perceptrons). It is also fairy easy to model these in a form of algorithm that simulates an
activity of such a cell using standard PC system (or other computer type). In currently utilized systems the
simulation realization is chosen practically as a rule. It constitutes a convenient and cheap tool, which allows
simulation of single neurons, as well as all networks of these.