The Brain, A Decoded Enigma | Page 8

they have to be dynamically calibrated by the activity
of the ZAMs. That is, a ZAM has to know everything is association
with the external organs of a body (e.g. hands, legs for a human). When
a ZAM has to make a simulation, it has to know all the parameters of
the muscles, for instance. An AZM has to know and transmit such
parameters. To do this, AZMs keep a model of any external organ of
that being.
All these models are associated with the hardware implementation of
the brain. We will see later some others types of models which are
associated with the software implementation of the brain.
SOME PRINCIPIAL PROBLEMS
When an M-model is activated it does not know how many entities are
in the external reality. Even more, it does not know which are these
entities. The device will try to find them based on the facilities of the
sense organs, but there is no guarantee that M-models have found all
the entities and no guarantee that the right YMs are associated to such
entities. This is a basic deficiency.
The camouflage and dissimulation are methods which use this
deficiency. By camouflage an entity is not discovered and by
dissimulation M-models associate a wrong YM to an entity.
Let's see another basic problem. Any model evolves to be harmonic
with itself and so, to be stable. This means that, after any change in the
model, it has to regain its stability. If a model has a disharmony, it has
to correct itself based on IR or based on an internal change (IR is not
available in any situation). Thus the model regains its stability, but in
some cases the model could be not suitable anymore to reflect the
external reality. There are many cases when a model is stable but its
predictions associated with the external reality are wrong.
We already defined reality as all the information that is or could be

generated by a model by simulation. The guarantee of a correct reality
is the stability of the model but the stability of the model is not a
guarantee that the model is capable to accurately reflect the associated
external reality.
That is, there is no guarantee that all the entities of a given external
reality are discovered, there is no guarantee that the right YMs are
associated with these entities and so on. The stability of a model is just
a guarantee that all the available information is correlated in the right
way.
There is another class of basic problems associated with the changes in
a model. If a model has to be changed, sometimes there are small
chances to do that. In fact, the only possibility is to make a new model
from scratch, using or not elements and relations from the old model.
This activity could be sometimes so complex that it can exceed the
technical capacity of the brain.
Indeed, a new model must be accepted by the whole structure of
models. That is, any other model of the structure must accept any
prediction of the new model, so that the new structure is stable.
If the new model is good in interaction with the external reality but the
structure of the models is not good enough, then some other models of
the structure have to be changed too. As I said, this process can exceed
the brain's technical capacity of processing. This can be considered as a
design deficiency too.
This explains a lot of situations in common life, when logical
arguments or facts taken from external reality cannot change wrong
models some people have.
As we know, a stable model is a model which correlates in a right way
all the available information. But, there is no guarantee that we gain
enough information to make the right model. This basic deficiency is
attenuated by the fact that there is a structure of models. The structure
of models helps a lot when we interact with a new external reality
because it can make predictions based on the previous interaction with
other external realities. On the other hand, the structure of models is
like a brake for evolution if the structure has problems.
Example: The astronomer Copernicus made a model of the Universe
based on the idea that the Sun is the center of the Universe, not Earth,
as everybody knew at the time. Around the year 1543, very few persons

were able to change the whole structure of models, based on this new
model.
We continue with other basic problems and features.
In the normal activity of the brain, any ZM-model has full access to any
model of the brain. That is, a ZM model can correlate information from
many M-type models and from any other ZM of the brain. This is true