For a given external reality, the brain makes a structure of models, using
information taken from the external reality or from other models.
We will see how this function works in a specified situation: how a new M-ZM
is made in interaction with a new external reality. This function is described
for a normal and mature brain. The term "normal brain" will be treated later.
Here, a "normal brain" is a brain, which is able to work as it was already
described in the section of hardware facilities. A mature brain is a brain,
which has enough YM and ZM models made during a long time of interaction with
the external reality.
An image is an information which is received as it is, in the same way as it
would be generated by a TV-camera for instance. This kind of information,
without any meaning in fact, has to be integrated by the brain as an image-
model.
As we already know, M-models have to find some entities in that image. They
start by making a 3D-image. This is possible in a rather easy way because
almost all beings have two eyes. So there are two plane images and M-models
will make a 3D-image. Now, the basic problem is that from a 3D-image it is not
an easy task to identify the entities. M-models will use any supplementary
information associated with this 3D-model, as color, contrast, brightness, the
movement of some entities and so on. Anyways, M-models have to associate
entities to YM-models. This process could be affected by mistakes, but,
because M is a model, there will be a lot of crosschecks that will allow to
discover and correct some of the mistakes.
For instance, if something round is discovered, it could be an apple (YM-
apple) or a ball (YM-ball) or anything else.
Once a possible entity is associated with a YM, the M-model will predict how
this YM interacts with the other YMs of the model.
For instance, there is a YM-apple. It has a relation (it is very close to)
with a YM-table. So, from the predicted properties of the table, based on
simulation, it results that it can support an apple, and from the predicted
properties of the apple, it results that it can stay on that table. So, this
relation seems to be good and thus, maybe the YMs are OK.
Now another example: an apple is on a thin branch of a tree. From the
predicted properties of the branch, it results that it cannot support that
apple. So, the choosen YM-apple or YM-branch is not good. M-models have to
change something or to add something (maybe there is no gravity there...) to
be stable.
The exact procedures and methods can be different. Anyway, MDT is a basic
theory and it is not concerned with the technological implementation of the
functions of the brain. It is enough to say that there are basic methods to
solve the problems and also that the methods are not 100% safe, as everybody
knows from his/her direct interaction with the external reality.
What is obtained by this interaction is a preliminary M-model associated with
the external reality. This M-model is in interaction with, at least, one ZM-
model, which develops the M-model based on any other information available in
the brain.
These two processes happen almost simultaneously. As an M-model is made, a ZM-
model takes some information from the M-model and improves itself. Also, ZM
can change or add some information into the M-model, based on information
obtained from other M-models or ZM-models. These two processes are performed,
in fact, almost simultaneously due to this very close communication. They are
called M-(YM)-ZM processes. The aim is to make a better and better ZM-model
associated with a given external reality. As we know, such processes generate
the knowledge and the consciousness.
Faced with the same external reality, every brain makes and operates its own
structure of M-ZM models and so its own reality. For everyone, the reality is
generated by his/her own structure of harmonic/logic models. From this mode of
interaction, it does not result that faced with the same external reality,
everyone makes the same structure of models.
Example 1: If a painter and a forest ranger look at a tree, each will make
another M-ZM-model, and each will think and act based on one's own reality.
Example 2: When we drive a car in the city, M-models transmit the full
information on what is around, but ZM-models, which control the car, will use
only part of it. As the speed increases, ZM will process a smaller and smaller
part of the M-model, to drive the car. This phenomenon can be called the
narrowing of the consciousness field. It occurs every time when the brain is
overloaded.
Basically speaking, everything what was already presented up to now is about
the same for human and animal brains.
The exceptions are associated with symbolic models (which are based on logic).
The animals cannot make any symbolic models.
As we know, the basic function of any brain (human or animal) is to make and
operate image-models. Let's continue with the basic differences between the
human and animal brain.