The Brain, A Decoded Enigma
by Dorin Teodor Moisa · English · Gutenberg #14586 · 377,633 chars · public domain (US)
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Title: The Brain, A Decoded Enigma
Author: Dorin Teodor Moisa
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Copyright (C) 2004 by Dorin T. Moisa
THE BRAIN, A DECODED ENIGMA
Dorin T. MOISA
Warning
This book contains a symbolic model associated to the basic hardware
function of the brain.
A symbolic model is a model based on logic only. So, this book is not
recommended to individuals who has the tendency to understand the
external reality based on imagination.
The book can be understand by persons between 12 and 20 years old who
have special abilities in the field of positive sciences.
Also, the book is recommended to persons who already work in the field
of positive sciences (mathematicians, phisicists, engineers and so on).
CONTENT
Introduction
Abstract
Fundamental Terms (keywords)
Definitions associated with the basic terms
The basic hardware elements
Some principial problems
How M-ZM models are build
The human brain (introduction)
The human brain versus animal brain
Human brain: evolution or external intervention
Basic design deficiencies of the human brain
The structure of the brain, the PSM-model
The structure of the brain: functional facilities and types of models
Paranormal phenomena
The normal human brain
The abstract of the functional facilities of the brain
The personality (human only)
The conciousness
Abstract: model dictionary
Example, Tests, Aplications (ETAs)
ETA 1: The model
ETA 2: Truth, reality, communication
ETA 3: Fundamental problems associated to scientific knowledge
ETA 4: General communication language (GCL), dictionary of terms
ETA 5: NULL model
ETA 6: Time
ETA 7: Music
ETA 8: Cinematography
ETA 9: The fundamentalisms of the world we live in
ETA 10: Terrorism
ETA 11: Problems of the human brain evolution
ETA 12: Rattlesnake
ETA 13: The main psychiatric illnesses: paranoia and schizophrenia
ETA 14: Suicide
ETA 15: Normality tests
ETA 16: Dreams
ETA 17: The history of the evolution of the human species, based on MDT
ETA 18: The organization of the human society
ETA 19: The schizophrenic-paranoiac complex (XSPC)
ETA 20: Induced paranoia (XIP) and paranoiac-schizophrenic complex
(XPSC)
ETA 21: Disharmonies of the functions of the brain
ETA 22: Direct demonstration of the function to build image models
ETA 23: Some basic parameters of the brain for measuring the
performances
ETA 24: Animals
ETA 25: Very complicated operations on image models (walk, jumps,
climbing trees) of humans
ETA 26: The brain evolves under our eyes
ETA 27: Principial negative effects associated with the functioning of
the brain
ETA 28: Free-masonry
ETA 29: Problems associated with movie-making
ETA 30: Optical perspective and the quality of construction of image
models
ETA 31: Something agressivity may fight XS1-type schizophrenia
ETA 32: Sex
ETA 33: The internal body
ETA 34: The european spirit
End notes
Bibliography
Introduction
This book contains my original theory, called MDT (Modeling Devices
Theory) on the basic hardware function of the brain (human or animal).
As any scientific theory, it is a symbolic model. Any symbolic model is
based on a limited number of basic terms and a limited number of basic
relations between the basic terms.
For the basic terms and only for them, there are accepted descriptive
definitions. All the others terms are generated by the model, together
with their normal definitions. These definitions are generated by the
model by logical and mathematical procedures.
These are the basic characteristics of any scientific theory and so, I
follow the procedures described above, to make a theory on the basic
hardware functions of the brain.
This theory is in a total opposition with all the actual sciences
associated with the functions of the brain. The present sciences,
associated with the functions of the brain, are not based on a single
fundamental model. In this way, as my theory will be accepted, all what
it was already written in the actual sciences associated with the
functions of the brain, have to be re-written or forgotten.
This attempt of total revolution is necessary because the actual
sciences on the brain don't use normal definitions of the terms; there
are only descriptions associated with them. Because the definitions of
the terms are not generated by a single fundamental model, the logical
corelation between them is not possible. So, the actual sciences
associated with the brain cannot evolve to become positive science
anymore.
In psychology, for instance, about any scientist has his/her own list
of descriptive definition associated with the terms used by him/her. In
this way, it is not possible to make a logical structure to integrate
all the terms used in that field. So, the psychology, for instance, is
not a positive science.
Another example:
Let's consider a classical positive science, as Newton's Mechanics is.
In this symbolic model, all terms have exactly the same definition for
all the scientists. These definition are not changed since 340 years
ago when they were generated by the symbolic model of Mechanics. For
instance, the term "speed" is defined as v=s/t. That is, "speed" means
that the "space" is divided by "time". This definition is a normal
definition generated by the symbolic model of Mechanics not a
descriptive definition.
Let's suppose now that a symbolic model associated with the basic
hardware function of the brain is already created or it will be
created. The first consequence is that all the terms used in
association with the functions of the brain will be generated by the
model by logical and mathematical procedures, together with their
normal definitions. There is no reason to suppose that any descriptive
definition which is already used in the present sciences of the brain
will be compatible with the definitions generated by that symbolic
model.
So, all what is already created in the present sciences associated with
the brain has to be re-written or forgotten.
Regardless of the fact that MDT theory will be accepted or not, a
symbolic model which covers the basic hardware function of the brain
will produce this total revolution in all the sciences associated with
the brain, including psychology, psychiatry, gnoseology, epistemology,
many parts of social sciences and so on.
Let's consider that a symbolic model to cover the basic functions of
the brain is created and is already accepted. The persons who already
work in these fields have to re-start everything about from zero. Their
opposition will be enormous and I have no illusion in this direction.
This theory was created about 10 years ago. Based on my personal
experience, the theory is easily understood by persons with special
orientation on positive sciences, including children's over 12 years
old. Also, the persons who already work with symbolic models
(mathematicians, physicists, engineers and so on) have a high capacity
to understand it.
Let's see what MDT offers.
First of all, MDT treats the brain as a device which processes the
information. In this way, MDT has no direct connection with the
medicine.
MDT is concerning only with the basic functions associated with
information processing and it is not interested by problems as "what
part of the brain is doing something" or "how a function is
implemented". MDT is a theory associated with the processing of the
information and so it has no direct interference with the hardware
implementation of the physical brain.
As a symbolic model associated with the basic function of the brain,
it generates precise definition, based on logic, of all the terms used
in association with the basic hardware functions of the brain. In this
way, all the terms are logical correlated between them.
Examples: MDT generates normal definitions for: knowledge,
consciousness, to imagine, to think, intelligence, emotion, to be
irritate, love, happiness and many others. E.g. the "consciousness" is
the facility of a brain to make and operate a model which contains the
being itself as an element. MDT defines, than, 6 different types of
consciousness which are, of course, defined in the same precise way.
Even more, based on MDT, it is possible to design a logical structure
to implement the function called "consciousness".
MDT explains the basic functions of the brain up to the level to make a
logical design to synthesize all the brain's functions (human or
animal). Of course, a technological implementation of that functions is
not possible now because the computers, for example, have yet a very
low power to process the information and this situation will last, I
think, at least in the next 25 years.
In fact, the brain is treated by MDT as a technological product. So,
there are defined the main design goals and also, the main deficiencies
(by design or given by technological implementation).
There is analyzed the problem if, by evolution, it is possible or not
to evolve from animal brain to human brain.
There are analyzed the design and technological problems, including the
functional illnesses of the brains.
The theory treats also the paranormal phenomenon and suggest some
methods to develop such activities.
The Application section (ETAs) contains also many items as a history of
the evolution of the brain, the evaluation of the problems of
psychological tests and performance tests for a brain, some problems
associated with the present and future levels of evolution of the
brain, some long range problems associated with the development of the
human society (including the terrorism) and many others.
The basic elements of MDT occurs in 1993 and the first written form (on
WEB) in 1997. In 2003 a printed edition of the theory was published (in
Romanian language) by the Romanian Publishing House "Editura Albastra"
and in 2004, in the frame of Gutenberg Project, a new edition also in
Romanian. The process of developing is continuing.
Dorin T. MOISA
moisa@zappmobile.ro
THE BASIC FUNCTIONS OF THE BRAIN
ABSTRACT
This theory, called by me as MDT (Modeling Devices Theory) considers that the
basic hardware function of any brain (human or animal) is to make and operate
image models (or analogic models) which are associated with the external
reality. In this frame, for the human brain only, there is an additional
hardware facility: to make and operate symbolic models.
FUNDAMENTAL TERMS (KEYWORDS)
Image model (or analogic model), symbolic model, simulation on model,
information, truth, reality, input reality (IR), external reality, image,
harmony, logic, general communications language (GCL), logical and
mathematical language.
DEFINITIONS ASSOCIATED WITH THE BASIC TERMS
This theory is a symbolic model. Any symbolic model has a limited number of
fundamental terms. For these terms and only for them, there are accepted
descriptive definitions. A descriptive definition is, usually, not precise
enough for a scientific approach. This lack of precision is due to the fact
that it uses terms which must be defined before. The terms used in the
definition must also be defined using already defined words. This process
seems to be endless.
In any positive science, the descriptive definitions are accepted only for a
very limited number of terms. These are called "fundamental terms".
For instance, in the symbolic model of Newton's Mechanics, the fundamental
terms are mass, space and time. None of these terms have a normal definition
(i.e. generated by the model). They have only descriptive definitions.
Once the fundamental terms are introduced by description, all the other terms
have normal definitions, which are generated by the symbolic model, by logical
and mathematical operations.
Let's see the definitions of the terms used by the MDT theory.
Model: this is a term used on large scale in science and technology. The MDT
theory accepts the definition used there.
A model means some fundamental elements and some fundamental relations between
the elements.
The elements could be of any type (physical objects, the representation of any
object in any form, including pictures of any type or images of any type or
mathematical symbols of any type and so on). In fact, an element could be
associated with anything which can be considered as an entity. The elements
have some properties, which must be specified somehow. There are a number of
relations between the elements, which must also be specified.
An image model (or analogic model) contains an unspecified number of elements
and an unspecified number of relations between the elements. An image model is
just given as it is. It is not possible to specify in explicit and precise
ways which are the elements and which are the relations.
Examples of image models: maps, models of an object of any type, an assembly
of such models including any material elements (water, air and so on), any
representation in any form of such elements.
A symbolic model uses as elements letters, numbers or words. The relations are
of logical or mathematical type.
The most important symbolic model is the General Communications Language
(GCL). The elements are usually nouns and the relations are usually verbs.
Warning: GCL is not really a symbolic model. The GCL just contains all the
elements and all the relations. When a symbolic model is made (a sentence, for
instance), elements and relations from GCL are used. Thus, because there is no
available word, I decided to consider, by extension, the GCL as a symbolic
model. In this frame, GCL has to be considered as "symbolic model".
Once a model given, it is possible to simulate some situations on it. For
simulation, a change must be made to the model. After that, the entire model
will be changed because all the elements have some relations between them.
Any implicit or explicit information which is generated by simulation by a
model, is called "truth". Any truth must be associated with the model, which
generated it. This is the definition of the term "truth" in the MDT theory.
All the information, which is or could be generated by a model by simulation,
is called "reality" associated to that model. This is the definition of the
term "reality" in the MDT theory. We also see here that before declaring the
reality, one needs to declare the model which generated it.
We already used the term "information". This term is a fundamental term. It
has no normal definition. MDT accepts the descriptive definition from common
life and from science. The same situation is for the term "entity".
Warning: in connection with the term "information", something is considered as
information after that "something" is processed somehow by a device which
takes and processes that "something".
This somehow confuse situation is normal for any fundamental term. Just think,
for instance, how one can explain what is "time". The only possibility to
explain what is "time" is to use examples that already use the term "time". In
fact it is impossible to define terms as "mass", "time", "space",
"information" or "entity".
Let's introduce two new terms: "harmony" and "logic".
Once a model is given, it is possible to make simulations on the model, as it
has already been explained. By simulation, it is necessary to change an
element or a relation. The model goes into a temporary unstable situation
because all the elements are connected between them. The model will evolve to
a new stable situation. For an image model, the evolution to stability is
based on harmony laws. For a symbolic model, the evolution to stability is
based on logic. Thus, a stable model is a harmonic or logic model and, after a
perturbation, the model will regain the stability based on the laws of harmony
(image models) or logic (symbolic models). The evolution of any model toward
stability (to become harmonic or logic) is also a basic hardware facility of
the brain.
Because some situations from external reality can be associated, sometimes,
with both types of models, there can be a corespondence between harmony and
logic.
Thus, the implicit definitions of the terms "harmony" and "logic" are
associated with the methods to regain the stability of an image model
(harmony) or symbolic model (logic). An "implicit definition" means that we
are able to recognize the effect of harmony or logic in an informational
structure.
We are now in the situation to present the basic hardware function of any
brain, based on the terms, which have already been defined.
The basic hardware function of any brain (human or animal) is to make models
associated to external reality and to predict, by simulation, the possible
evolutions of the model. Because the model is associated with external
reality, it is possible to predict by simulation some probable evolutions of
the external reality.
We already used the term "external reality" which is not defined yet. This
fundamental term is considered as a source of information, which is not
localized in the structure of models of the brain. I want to emphasize that
the external reality is not a source of information, but is just considered so
by any brain.
Thus, one of the main hardware functions of the brain is to make models of the
external reality and to predict, by simulation on the model, the possible
evolution of the associated external reality.
We already defined the reality as all the information which is or could be
generated by a model. This means that we understand the external reality by
the reality, which is generated by a model, which is associated with the
external reality.
Example: For a given external reality, any person makes an associated model.
Any person has his/her own model associated to the same external reality. We
think and act based on our own reality and not based directly on the external
reality.
In fact, external reality is rather an invention of the brain to explain its
structure of models.
THE BASIC HARDWARE ELEMENT
Let's see what is the basic hardware element of a brain (human or animal).
There are some image-type models called M-models, which are associated with
the sense organs (eyes, ears and so on). M-models work in association with
some YM-models, which already exist in the brain. YM-models are concept
models. A concept-model is a simplified model which, in this way, fits a large
class of similar models.
Example of YM models: "dog", "table" and so on.
M-models have to discover as many as possible entities in the external reality
and to associate a YM model to any entity. Once an entity was firstly
associated with a YM, M-models will predict its evolution based also on that
YM.
Example: if an entity was associated with a YM-dog, the M-model is able to
predict how this YM performs in connection with all the other YMs of it.
Any prediction of M with that YM included is compared with the information
obtained by M from external reality. The information obtained by a M-model
from outside during the comparison process, is called "input reality" (IR).
We just introduced a new term as "input reality" or IR. IR is the information
obtained by an M-model from outside (from external reality or from other
models) to improve its predictions.
If the prediction meets IR, then M will try another prediction to improve its
quality. If one or more predictions do not meet IR, then M will replace that
YR with another, and the process will continue. This process will continue so
that all the entities which are discovered by M-models will be associated with
some YMs and all the predictions of M must confirm the M-model, unchanged.
Such a model is, thus, a stable model. When M is stable, all YMs are
integrated in M in a harmonic way.
The main function of M-models is to make a preliminary harmonic model (stable
model) associated with an external reality.
Conclusion: a M-model interacts with a section of the external reality. M will
be a model made in an informational way by analogy with that section of the
external reality. Because M is a model, all the elements are connected between
them in a harmonic way, so that the model is stable. This stability is
verified on and on in an automatic way, as long as a specific external reality
is in interaction with the specific M-model.
M-models interact with some other type models, called ZM-models. ZM-models
take some information from one or more M-models and continue the construction
of models associated with the corresponding external reality. To do this, ZM-
models interact with the other ZM-models of the brain to improve M-models.
M-models are just preliminary models based on YM-models. A ZM model will take
any information from any other M and ZM models of the brain, to improve it.
Example: an M-model is associated with a bus that transports people. A ZM-
model takes this information and tries to see if this bus transports tourists
or is a public transport vehicle. To do this, it will use information taken
from any other ZM-models and M-models. The aim is to make a ZM-model, which
reflects as well as possible a section of the external reality. Because ZM is
a model, it is stable and because this model is integrated in a structure of
other ZM-models, the structure of ZM-models is stable too. This problem will
be treated later in details.
ZM-models are long-range models. This term will be explained later. Here, the
"long-range model" is understood as a model, which already developed its
elements as self standing models.
ZM models are the main models, which reflect the external reality.
We define now two very important terms: knowledge and consciousness.
Knowledge is associated with the facility to predict the evolution of the
external reality based on a structure of harmonic/logic models. This structure
was made by a large number of interactions with many sections of the external
reality and so it already generated a large number of good predictions. This
means that the only guarantee of the correctness of the knowledge is the
confidence in that structure of models. This issue will be developed in
details later in the book.
The consciousness is the facility to make and operate a model, associated with
the external reality, where the person itself is an element of that model.
When such a model is activated, it will also find the position of the person
in the model and so it will predict the position of the person in the external
reality. This issue will also be developed in detail in another part of the
book.
We will now develop some issues associated with the term "knowledge". We
already defined knowledge as the capacity to predict in a correct way the
evolution of the external reality.
Here we use the term "correct". Let's see what it means. This term has two
definitions. One situation is when a model makes a prediction and the
prediction is compared with IR. If the prediction meets IR, then the
prediction is "correct". Unfortunately, there are very few situations when the
comparison between prediction and IR is possible.
For instance, building a bridge. A problem is, for instance, if the bridge
will be stable or not in case of an earthquake. Here we need a guarantee that
the bridge is properly built and there is no possibility to verify this based
on IR.
The second definition of the term "correct" is: the brain will consider as
"correct" any prediction based on a harmonic/logic structure of models. To be
harmonic, the structure was already verified, based on IR in many other
situations. So, the only guarantee of a "correct" prediction is the confidence
in that structure of models.
MDT is associated with the basic hardware functions of the brain. Once we
described the hardware structure, everything what the MDT predicts is based on
what the hardware is able to do. What MDT says about knowledge is not another
theory on knowledge but what the hardware is able to do.
Any experiment is based on a model. That model tells us what we are doing and
the same model tells us what we get and what we see. Any model that makes the
experiment just improves itself. An improved model will make better
predictions and that is all. There is no guarantee associated with the
knowledge except the confidence in our own structure of models.
Let's see another aspect. We saw that any experiment is based on a model. The
model tells us what we did and what we get and see. If there are many persons
who participate in an experiment, everyone will make his/her own model based
on his/her own structure of models. What everyone gets and sees depends on
one's own structure of models.
Example: up to around year 1500 everybody knew that the Earth was the center
of the Universe. This idea was supported by direct observation of the sky but
also by a powerful structure of models. So, in that period, the astronomers
were able to calculate Sun and Moon eclipses, understand and calculate many
parameters associated with the movement of the Moon, Sun and stars. Even the
Holy Book supported this idea, at least in an implicit way. In that period,
the idea that Earth is the center of the Universe was correct.
I want to emphasize again that the situation is generated by the work
principle of the brain. It does not matter if we like or not this situation!
The situation will be the same forever. For instance, Newton's Mechanics
considers that there is a fundamental field of forces called "gravity".
Everybody considers that the gravity exists. But Einstein says that there is
no such a field of forces; what we see is just an effect of the distortion of
the space due to mass. If Einstein is right, the idea that there is gravity is
not correct anymore. See also the applications.
So, in every moment, the brain will consider as correct everything which is
generated by its structure of stable models.
Some scientists could consider these assertions as unacceptable, but
regardless of the fact that we like or not such a situation, the brain is able
to do only what the hardware structure is able to do.
There is another term that has some associated problems. This term is "wrong".
If a model makes wrong predictions, this usually does not mean that the model
is wrong. It means just that the model is not suitable to the given external
reality.
Faced with a new external reality, the brain will activate the model which
makes the best predictions associated with that external reality. If a model
makes wrong predictions, we have to change the model with another one or to
modify the model.
Example: Newton's symbolic model of Mechanics makes wrong predictions
associated with the objects moving at a speed comparable to the speed of
light, but its predictions are good (correct) at lower speed.
In any situation, the terms "correct" and "wrong" must be associated with a
model or with a structure of models.
We already described the first basic hardware facility associated with the
brain (human or animal). It generates truth, reality, knowledge and
consciousness. Now we will describe the second basic hardware facility of the
brain. This is the action on the external reality.
We already saw that faced with a section of the external reality, the brain
makes at least one ZM model. A ZM model works in association with any
available (or several) M-model and with any other ZMs of that brain. The main
ZM is able to predict in a correct way the evolution of a section of the
external reality. Such a ZM is able to make a new class of long-range models
called ZAMs.
ZAMs are artificial and invariant. An artificial model is made without any
direct interaction with the external reality. An invariant model is a model,
which cannot be changed by direct interaction with the external reality.
A ZM model will make a ZAM model in order to modify the external reality. Once
a ZAM is made, it becomes a reference model in changing the external reality.
To do this, the ZAM-model works in connection with a number of AZM models. An
AZM is a model which is already connected to the execution organs of a being
(for human beings these are legs, hands and so on).
Once a ZAM is activated, it will simulate the requested action using any
information from all models of the brain. Based on simulations, ZAM will
determine if it is able or not to meet the goal. If the simulation shows that
the action is possible, then the ZAM will activate AZM models for action on
the external reality. The ZAM will control the AZMs to act on the external
reality exactly as in the successful simulation, with good chances of success.
If by any simulation the objective is impossible to reach, the brain will be
blocked to do that activity.
Example: if a person has to jump over an obstacle, that person will know very
fast if the jump is possible or not. The person knows this, because a ZM makes
a ZAM-model, which is associated to the external reality (the person itself,
the supporting surface and the obstacle, as main elements). The ZAM then
simulates the jump on the model. If the simulated jump fails, the brain is
blocked to do the action. If the jump is done with success in the simulation,
the ZAM will control the body during the jump exactly as it was in the
simulation, with good chance of success.
No action on the external reality is possible without a successful simulation
of that action. The action will be as in the successful simulation. Both in an
immediate action and in an activity that has to be done in the future, any
brain follows this procedure.
We shall add some considerations about the speed of action on external
reality. So, when we walk on a plane surface, for each step there is at least
one simulation before the step is done. Due to a large number of internal and
external factors, any step is unique. Thus, if we walk on a raw surface (a
stony trail in the mountains, for instance) not only every step in based on a
simulation but even during the execution of a step, it is possible to make a
new simulation based on new data and so a step in execution can be modified at
all time to meet the goal as ZAM requires. Thus, a very complicated activity
as walking on a mountain trail, can be done very easily and even elegantly,
based on continuous predictions and simulations associated with every step.
As it was already emphasized before, this procedure to simulate in advance any
activity on external reality is followed in all situations, regardless if the
activity is immediate or it has to be done in the future.
We have already described the two main hardware facilities of the brain (human
or animal). Here is a preliminary abstract of the main hardware models of the
brain:
M-models: these models are associated to sense organs. The brain tries to make
a preliminary model of the external reality. To do this, it uses a number of
YM concept models. The main activity is to find the entities of the external
reality and to associate to any entity a YM model. Then, by simulation on the
model, M-models try to integrate any YM model in the structure in a harmonic
way. That is, any simulation of interaction between a YM and any other YM-
model must confirm the M-model, unaltered.
If, for instance, some predictions of an YM1 model in relation with an YM2
model are not compatible with the prediction of the YM2 model in relation with
the YM1 model, then M has to change YM1 or YM2, or some relations, or some
other YMs, so that the M-model is stable. M-models work in an automatic way,
trying to be stable in interaction with the associated section of the external
reality.
YM-models: they are concept models associated with all the entities, which
have already been discovered by the brain by M-model activity. When a new
being is born, there are practically no YMs. They are made by direct
interaction with the external reality.
ZM-models: they are the main long-range models of the brain. They generate
knowledge and consciousness. Also they make YMs, ZAMs and AZMs. They are able
to take any information from any other model of the brain. ZMs can replace a
YM-model with another if something is not OK after an advance prediction and
simulation based on any available data. They also control ZAM-models during
their activity.
ZAM-models: they are artificial and invariant models. An artificial model is
not generated by direct interaction with the external reality. An invariant
model is a model, which cannot be changed by direct interaction with the
external reality. ZAMs are models, which act on the external reality. Once a
ZAM was made and activated by a ZM, it will simulate the activity, using any
information from any model of the brain. By one or more simulations, the ZAM
will find the right solution. If it fails to find a solution, then the ZM will
make another ZAM and the process continues.
AZM-models: they are associated in a direct way to the organs which can act on
external reality. They are ready-made when a being is born, but, to be used,
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 for any ZM of the
brain.
In the complex interaction between a brain and the external reality, there is
a single ZM at a time, controlling that being. This ZM is called a local-ZM or
an active-ZM. A ZM can be changed to another in a dynamical way, so that the
being does many activities in time-sharing.
This activity is not simple. So, when a local-ZM is deactivated, it has to
store the conditions, to be able to resume when it takes control again. There
are problems associated with this activity. Some of the information can be
lost or the external reality may evolve in the mean time so that the stored
information will be of no use. In this way, any model, which takes control of
the being, has to initialize before being able to regain full control. This
activity of initialization is very complex and in some situations it might
contain errors. Thus, it is rather difficult to do many activities in time-
sharing.
There is also a basic problem associated with the term "knowledge". As we
know, the knowledge is associated with the predictions of a structure of
models.
So, the knowledge is associated with the structure of models and not with the
external reality, as we'd like it to be. We should never ever forget this
thing. Even more, knowledge is a non-sense if we do not declare the structure
of models.
Example: in any positive science, it is usual to say that something is true
based on a specified theory (model).
HOW M-ZM MODELS ARE MADE
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.
THE HUMAN BRAIN (Introduction)
The basic difference between the animal brain and human brain is the capacity
of the human brain to make and operate symbolic models. The animals are not
able in any way or form to make and operate symbolic models.
We already analyzed how a human or animal brain interacts with an image to
make an image-model. For the symbolic models the interaction is different.
A symbolic model, as we know, uses as elements letters, words or numbers. When
a human brain interacts with such elements, the M-models will contain such
elements as specialized YM-models. Such YM-models contain all the shapes of
the letters, for instance. It is not necessary to discover the elements,
because they are there in an explicit way.
All the symbolic elements are contained in a symbolic model called General
Communication Language (GCL). There is a spoken language and a written
language, as directly interacting symbolic models. This is true only for
cultural zones which use alphabets. There is a specific application which
treats this problem.
For a given written text, we have all the elements and all the relations
between the elements, in an explicit way, as words. Usually, the elements are
the nouns and the relations between them are the verbs. Any sentence is a
symbolic model, for instance.
Example: the sentence: "I go home" has two elements "I" and "home" and a
relation between the elements as "go".
The stability of the symbolic models is based on logic. When a symbolic model
is stable we call it a logical model. A logical (stable) model can be
understood by anybody who can make and operate symbolic models.
Sometimes there is a correspondence between image-models and symbolic-models
as in the following example.
Example: Let's analyze the sentence "An apple falls from an apple-tree". We
have two elements and a relation between them. On the other hand, we can make
an image-model that describes the same situation: an apple falls from an
apple-tree.
So, the logic could have been born in the process of translation from an image
model to a symbolic model (when the translation is possible). As an image-
model is stable based on laws of harmony, a symbolic model is stable based on
the laws of logic.
Here we have in an implicit way the definitions of harmony and logic, as the
rules and methods to ensure the stability of an image-model (harmony) or a
symbolic-model (logic). An implicit definition means that we are able to
recognize the effect of harmony or logic in a structure of data.
THE HUMAN BRAIN VERSUS ANIMAL BRAIN
MDT is a theory that treats the human and animal brain in the same framework.
I present here a possible evolution of the brain, from animal brain to human
brain. It is very important to specify that the theory is like a tool: it does
not support and also does not reject the evolutionist theory. MDT just
describes the situation.
For any external reality, the brain (human or animal) will make an image-
model. This function is basically the same for human and animal brain.
In a given external reality many similar elements could exist. For any
element, the brain has to make a YM-model.
For instance, a dog has to make a YM for any dog which it meets. Such a big
number of models use a lot of the brain resources.
When there are many similar elements, a solution is to make a concept-YM. Such
a YM will fit a big number of similar elements. This reduces the quantity of
data to be processed by an animal brain, and so, the brain becomes faster and
more efficient.
Thus, the first level of evolution of the brain (level 1) is the extensive use
of the concept models. This level is, probably, reached by all animals.
Observation: the human and animal beings continue to use, for some special
situations, pure image models. A pure image model is a YM-model associated
with a single entity of the external reality. For instance, a cub has a pure
image model of its mother.
The first step of the evolution of the brain is based on concept models. A
concept model fits an entire class of entities of the external reality. During
the interaction, the brain will use a concept model and then, in M-ZM, new
properties will be added, or even new elements, if necessary, to understand
better and better the external reality.
The evolution of the brain continues with level 2. This new facility is based
on label-models. As we know, faced with a given external reality, the brain
makes an M-ZM model that is able to predict the evolution of the present
external reality. Such models are called local-M-ZM. On level 2, it is
possible to make a new type of models, which are called label-models. A label-
model is able to activate a ZM-model, from the available models of the brain,
regardless of the local-M-ZM.
Example: an animal senses a specific smell. This can be associated with food
or with danger, for instance. In such a situation, the animal can activate a
specific ZM-model, which has no direct connection with the local-M-ZM model.
This is level 2 of the evolution of the brain.
At this level, a special kind of communication between animals occurs. This
kind of communication based on label-models is used by human beings as well.
It is not precise enough and is also very limited, but useful in many
situations, and very fast too.
The level 2 is the highest level achieved by the animal brain. The evolution
of the brain continues with level 3.
We already saw that, at level 2, a label-type model activates a ZM model. The
next step is to activate not the whole model, but only some associated truth
of the ZM-model. In this way, the brain has to manage a reduced quantity of
information and so becomes more efficient.
This is a critical point, because it is the barrier to separate the animal
world of human world.
Thus, there is a ZM-model and an associated label-model. The problem is to
associate to the label-model only some truths generated by the associated ZM-
model. A ZM-model is an image model, and so its truths are also of image-type.
The problem is to record such truths in a different way, based on a totally
new function.
MDT cannot indicate how exactly this facility works. The theory is not
concerned with the technological implementation of the functions. The theory
just says that some truths generated by a ZM-model have to be recorded in a
different way. In this way, the label-models become words, and the associated
truths become symbolic definitions of the words.
On level 3 a label-type model can activate an associated ZM model, but it can
activate only a collection of truths as well, which are different from the
'ordinary' image-truths of the ZM.
It is possible that the General Communication Language (GCL) appeared based on
this facility. The presence of a GCL in a brain will characterize that brain
as a human brain.
Example: when the word "dog" is heard, it is very probable that we activate at
least one suitable ZM. But when we use the sentence "I go to the forest with a
gun and a dog", it is very probable that we do not activate any ZM-model. The
sentence is understood based on symbolic models and based on logic and so we
do not need any image-model. In this way, the quantity of information that has
to be processed by the brain is reduced very much. The image models will be
used only when we have to make a precise model of the action.
The human brain continues to evolve with level 4. On this level we have words
and associated symbolic definitions, but no ZM-image-model.
Example: Let's take the following words: "this apple", "apple", "fruit",
"food". "This apple" is associated with a pure image model. "Apple" is a
concept type image model. "Fruit" and "food" cannot be associated with any
image model (we cannot imagine what is fruit or what is food).
So, on level 4, the human brain can make and operate symbolic models without
any connection with image-models.
On this level it is possible to develop logical and mathematical languages
and, in this way, to make positive sciences associated to the external
reality.
Example: Newton's Mechanics is a symbolic model associated with the physical
bodies. The basic terms of this symbolic model are mass, space and time. None
of these terms can be associated with image models.
The evolution of the brain continues with level 4+, but I prefer to call it
level 5 (up to now it is the highest). This level was attained only 100 years
ago. On this level the symbolic models break totally with image models.
Example: Newton's Mechanics describes the movements of physical bodies. But we
can imagine such movements. Here Newton's symbolic model can be translated
also in image models.
The pure symbolic models cannot be translated in any image models. The only
symbolic model of this type is Quantum Mechanics.
Example: in association with Quantum Mechanics there is a "classical" problem
called "the dual nature of light". There are some experiments, which prove
that light is a wave. But there are also some other experiments, which prove
that light is made of particles. It seems that we have big logical problems
here. The aberration with "the dual nature of light" is supported also by some
great physicists (R. Feynman, for instance).
Physicists in Quantum Mechanics already solved the problem of the nature of
the light. The "dual nature of light" is not a problem of Physics, but a
problem of thinking.
The problem occurs when the physicists try to explain to us what happens. At
that moment, they use terms as "wave" or "particle" which are associated with
image models. The same terms, in Quantum Mechanics, are associated with
mathematical formulae. There is no connection between the world of Quantum
Mechanics and the world of image models. If someone forces such a connection,
then some big logical problems can occur.
As MDT says, any information is non-sense without declaring the model that
generated that information. In the above example, the nature of light is well
understood by physicists in the symbolic model called Quantum Mechanics. If we
don't know Quantum Mechanics, then it is not possible to understand the
answer. So, if we do not know Quantum Mechanics, then it is forbidden to ask
any question associated with that field.
Let's evaluate the world based on these levels. There is a fraction of the
population who is staying on level 2, and just occasionally goes on level 3.
The majority of the population is on level 3, and occasionally goes on level
4. There is a small fraction, which is on level 4, and occasionally on level
5. This fraction produces scientific and technological advance.
To understand the MDT theory, at least level 4 is necessary.
HUMAN BRAIN: EVOLUTION OR EXTERNAL INTERVENTION
Some activities of the human and animal beings are similar. So, there is an
idea that evolution from animal brain to human brain could be possible.
As we already emphasized, MDT is just a tool, which is used here to see if
there is any possibility to evolve from an animal brain to a human brain. The
theory does neither support, nor reject such a possibility.
Based on MDT, the main difference between a human brain and an animal brain is
the facility of the human brain only, to make and operate symbolic models. The
common part of the two types of brains is the facility to make and operate
image models.
The evolution problem is to see if there is any possibility to change some
parameters in the structure of image-model devices to reach the capability of
making and operating symbolic models. On the other hand, a new hardware that
should be added to the animal brain is considered as not compatible with an
evolutive process.
As we saw in the previous section, the highest level reached by the animal
brain is level 2. With a peak on level 5, the superiority of the human brain
is huge.
Let's see some arguments that support the evolutive process. For instance,
let's analyze whether by increasing the level of conceptualization of the
models, it will be possible to get closer to the ability to make and operate
symbolic models. Thus, if a class of models is more and more conceptualized,
such models should be so simplified that they could be very close to a
symbolic definition. Therefore, a change from level 2 to level 3 could be
reached by evolution.
But, let's analyze an example. So, we have "this apple", "an apple", "a
fruit", "food". This is an example of increasing level of conceptualization
with the last two items as symbolic elements. The animals have a shortcut by
making a model to tell them if what they meet is or not food. In this way, the
animals have a fast solution for problems based on image models. There is no
advantage to increase the level of conceptualization. Thus the evolution could
be blocked by a fast solution, based on image-models.
The advanced conceptualization should be supported in a group of vulnerable
animals. To survive, the communication could be decisive. By increasing the
level of conceptualization, the communication could be more and more precise.
This seems to be the only serious argument for increasing the level of
conceptualization. On the other hand, there is already a system of
communication on level 2. Thus, a sound or a combination of sounds is
associated with a label-type model. It can activate any ZM-model. This type of
communication is faster than that based on symbolic models and usually precise
enough for the normal necessities of a group of animals. Unfortunately, here
we did not see again any advantage from increasing the level of
conceptualization.
But, if, for a group of animals, there is a lot of information which comes in
fast succession, then the animals will be forced to make more and more
simplified models and this should force them to increase the level of
conceptualization.
Let's see another example. A person goes somewhere in the desert. Without
special equipment, his chance to survive should be very low. But, around him,
could be some animals which survive without special efforts. For animals, it
is more important "to invest" in "equipment" then to increase the level of
conceptualization of the models.
Anyways, at least in theory, it is possible to evolve from an animal brain to
a human brain based on an increase in the level of conceptualization. If the
animals have or not the tendency to do this, is another issue.
Let's analyze again the evolution of the brain. A concept model is a model
which fits a large number of entities. It has to be recorded, maybe, by the
same hardware as the hardware that records a normal image-model. Also, there
must be a connection between a concept model and every particular model
covered by it.
By increasing the level of conceptualization (e.g. from "apple" to "fruit")
the structure becomes very complex. The structure becomes even more complex
when it evolves from "fruit" to "food". In theory, an evolutive process could
produce this process but the increase of the complexity is so huge that it is
difficult to believe that this could be produced without specialized hardware.
Level 2 is very close to level 3, but, as we see, no animal was able to reach
level 3. Even the most advanced animals, like dolphins, have no tendency
towards level 3.
The first drawings on cave walls were dated back to about 150000 years ago.
Such drawings must be produced by some long-range image-models. But, such
drawings are of no use without some explanations (symbolic messages). The
reason is that the same drawing can be associated with a lot of situations. It
is fair to consider that, at that moment, the primitive human beings were able
to use a symbolic model for communication (a primitive language).
One idea is that the increasing capacity of the brain to make long range
image-models was a support to make also symbolic models. This idea cannot be
supported, based on MDT.
Indeed, the drawings made by 5 to 12 year old children are rather primitive
drawings. At such age, children have very few long-range models. But they are
able to make and operate symbolic models, including languages to communicate
with computers.
Thus, it seems that the long-range image models are not necessary to make
symbolic models. Also, this supports the idea that the symbolic models are
made by a special hardware.
The existence of a specialized hardware is based on the following:
There is an image model and the associated label-model (a word). The word has
a definition (based on other words). It is clear that there must be a hardware
to record the image-model and another (associated) hardware to record the
definition. On level 4, the image model does not exist anymore.
If this new hardware should be build based on evolution, it is difficult to
understand why we have no intermediate stages. The dolphins, which are
considered as the most advanced animals, have no tendency to build symbolic
models.
There are some experiments with monkeys, which can be understood as support
that some monkeys are able to make symbolic models. Such cases can be
generated by a software implementation of the function to build and operate
symbolic models.
As we already know, a model in PSM is very efficient but it blocks the
evolution (the model is transmitted unchanged or with small changes, from a
generation to another). If an animal builds, e.g. by accident, an advanced
model of interaction with the external reality, such a model cannot be
transmitted to the next generation. Only if a hardware implementation exists,
a new model will be transmitted to the next generation. This seems to be a big
problem for the evolution of the beings.
Without a hardware implementation, the solution is to transmit such models
based on education. If there were groups of monkeys which lived together for a
very long time, then a good model could be transmitted from a generation to
another by education. In this way, a hardware implementation is built up also
if the time available is long enough.
After many generations of monkeys who are forced to build symbolic models, it
is possible, theoretically, that some hardware occurs to support the symbolic
model building. This could be the process that generated the human brain by an
evolution process.
The main argument against evolution from animals to humans is the fact that
the 2 years old children are able to build and operate symbolic models. At
that age they haven't either enough long-range models to understand the
external reality and they are not capable to build such models. The maturity
of a human being is reached around the age of 18, and thus the facility to
build symbolic models is clearly a hardware facility.
Conclusions:
1. Long-range image-models are not an explanation for the occurrence of
symbolic models.
2. The symbolic-models could occur from image-models by a huge increase in the
level of conceptualization in very special conditions (e.g. large groups of
monkeys which live together for a very long time).
3. The symbolic-models are built and operated by a specialized hardware.
There are two possibilities: either evolution if statement 2 is valid or
external intervention if not.
BASIC DESIGN DEFFICIENCIES OF THE HUMAN BRAIN
The theory treats the brain as a technological product. So, the theory
considers that a designer existed. He had to fulfil some design requirements.
Any technological design has some deficiencies. We shall guess them in this
section.
This theoretical and abstract designer is outside of the theory and we are not
interested by it. It could be "Mother Nature" or God or an extraterrestrial
civilization or anything else.
These deficiencies are described here mainly for the human brain, but some can
be met also in the animal brain. The design deficiencies as MDT can detect
them, are:
XD1: The tendency to associate an image-model to any situation met by a
person. This deficiency is explained due to the "image nature" of the brain.
This deficiency explains why so many persons "stay" on level 3, when level 5
is accessible since 100 years ago. This deficiency can be corrected by
education.
XD2: There is no hardware protection to prevent the uncontrolled jump from a
model to another, in interaction with a complex external reality. The
stability in a model is a quality parameter of a brain.
Long-range models can stabilize a person. The XD2 deficiency is not related to
them. XD2 is related to the capacity to stay in a model, when faced with a
complex external reality. This deficiency can be corrected by software
(education, for instance).
The lack of stability in a model can induce the illness called schizophrenia
because this lack of stability has the tendency to favor short-range models.
Indeed, when there is no stability in a model, the brain will make a
specialized model for any particular situation met in the external reality.
Such models are not able to see that some different facts can be correlated.
Only a long-range model can detect such correlation. So, the stability in a
model is a parameter of quality for a brain and the lack of stability
indicates a low quality brain.
This deficiency can be met in the animal world too. For example, a dog has to
watch a perimeter. That dog can jump from watch-model to food-model, if it
gets food from strangers. Such a dog is a low quality dog, due to the lack of
stability in the model.
The dolphins have a good stability in a model, and so, we consider them as
advanced animals.
For human beings, the lack of stability in a model is a major drawback. Such
persons are not good for any complex activity.
XD3: This is a basic deficiency. Let's start with its description, based on
examples.
So, the brain interacts with an external reality and makes a harmonic model
with 3 elements. If, that external reality has, in fact, 4 elements, the
missing element cannot be discovered based on the 3-element model. As a 3-
element model has a number of wrong predictions, it is not easy to see what is
the problem from the analysis of the mistakes. The reason is that, once the 3-
element model is activated, the reality is just that one which is generated by
this model. There is no other reality! We cannot be outside of our active
model. In such a case, the brain tries to correct the model. Usually, it will
try to correct the model by changing the importance of some elements or
relations. Sometimes this procedure works, and the brain will continue to use
the 3-element model.
Such a situation occurs when we have not enough long-range models. In the
above example, the situation can be corrected if there is a long-range model,
which contains a 3-element model as an element of it. But even so, by
analyzing the mistakes, it is not easy to understand what is the problem.
A brain affected by XD3A is not able to predict that a model might be missing
some elements. A person, who can fight XD3A, can predict such a situation and
will treat any model as preliminary.
The brain makes models based on the available data. Such models are made in a
harmonic/logic way, but the stability of a model is not a guarantee that the
model is good in interaction with a complex external reality.
We define XD3A as a design deficiency, which means that a brain is not able to
predict the possibility of a missing element or relation in a stable (harmonic
or logic) model.
Another case: a brain has a stabilized model with 100 elements. This model
already generated a big number of correct predictions. At one moment, the
external reality is changed, and now there are 101 elements. As we know, to
correct a model means to reconstruct everything from scratch, using or not
components from the old model. This task could be so difficult that it exceeds
the technical capacity of the brain. In such a situation the old model is
fragmented, and the brain uses it in this way. Of course, this can produce a
lot of negative effects, including induced psychiatric disorders.
We define XD3B as a design deficiency, which means that a brain is not able to
reconstruct a model, once the model is detected as a wrong model in
association with a new external reality. We can express this also as the
impossibility of a brain to correct a XD3A deficiency, once it was discovered.
XD3-deficiencies are widespread in the current activity of human beings. There
is no reference to know that all the entities of the external reality are
associated with the right YMs in the associated model. For us, the external
reality exists only if it is associated with a model. Once we activated such a
model, the reality is what the model says. We cannot be outside of our active
model.
Once we have a model associated with a specific external reality, the model is
considered as a good model based on the predictions which are already done.
There is no guarantee that the model will continue to be good in any situation
and any time. A good quality brain has to know this and to predict some
negative effects associated with such a situation. So, this deficiency can be
controlled by software (education, for instance).
XD4: This is a deficiency associated only with image-models. It does not exist
in a symbolic-model environment.
For an image-model there is no possibility to know the importance of an
element or relation. The brain will choose in a more or less arbitrary way the
importance. A model can be harmonic (stable) for any importance which is
associated with its elements and relations.
A "lightly" negative consequence of this deficiency is the fact that, faced
with a given external reality, almost any person makes a personal image-model
associated with that external reality. We will see later that, for extreme
situations, such deficiency is associated with the psychiatric disorder called
"paranoia".
The symbolic models do not have such problems. Once a symbolic model is made
in a mathematical environment, the "law of the propagation of the errors" is
able to predict the importance of any element or relation.
For instance, if we have a complex mathematical formula, the law of the
propagation of the errors will tell us how much the result is changed if an
element is changed with, let's say, 1%.
We already used the term "correct" associated with the importance of an
element or relation in an image model. If there is an external reality and two
associated models, one image-model and one symbolic-model, and if the two
models have the same predictions, then the importance associated with the
elements and relations of the image model is correct. If not, the right
importance is that of the symbolic model.
The above method is not good in any practical situation. In fact, there is no
method to know if we associated the right importance to any element or
relation of an image-model. This is XD4.
XD5: this deficiency is a technological one. It means that there is no
hardware or software method to erase a model of the brain. A model is made
forever. It can be destroyed only in an uncontrolled way due to the
biological deficiencies or the brain.
The consequence of this deficiency is huge in many practical situations. The
problem is developed more in another section of this book.
THE STRUCTURE OF THE BRAIN, THE PSM MODEL
The Protection and Surviving Model (PSM) is the basic image-model of any
brain. When a new being is born, it has only this model in its brain. This
model is very complex and it will be described in this chapter.
There is a section of the PSM, which contains a collection of short-range
models. They have to act very fast to provide minimal protection for that
being (including newborn beings) in some specific dangerous situation. These
activities are called "reflex actions".
The PSM contains also some basic models, like the model to keep in the
eyesight a moving entity from external reality, or the model to touch by hand
an entity in the range of the hand. There is also a collection of models
associated with equilibrium and the general stability of the external body,
together with a model of it, of course.
There are also a number of long range models which contain the instincts to
survive unconditionally, forever (basic design requirement).
During the period of growing, others models can be included in the PSM, models
which are associated with the educational process. Such models have to prepare
the being to live in a specific external reality.
By accident, any other models can enter the PSM, but some of them can produce
big problems for the future mature being, mainly paranoia type illnesses (see
ETAs).
The basic characteristic of any model from the PSM is that such a model is
invariant. It cannot be changed regardless of the information obtained from
the external reality.
The main goal of the PSM is to ensure that the being will survive
unconditionally, forever. To do this, the PSM is able to build elements, which
are activated to self-develop as models.
So, when a new situation from the external reality is met, and there is no
model to understand it, the PSM is automatically activated and tries to solve
the problem, based on some reflex actions, or based on some instincts. It also
makes a specialized element, which is activated as a model. The new model
tries to understand the new situation by independent activity, in interaction
with the external reality. When that situation is met again, the PSM is not
activated, and the specialized model solves the case. So, as a being gains
more and more experience, the PSM is not activated, but one of the specialized
models is activated instead.
Regardless of how many models are in a brain, if a new external reality occurs
and there is no model to understand it, the PSM will take the control in the
way already described.
When PSM controls a being, this can be recognized by the fact that the
consciousness disappears, as the normal structure of models is deactivated by
the PSM. This situation is called as shock-status.
THE STRUCTURE OF THE BRAIN: FUNCTIONAL FACILITIES AND TYPES OF MODELS
A basic functional facility of the brain is that any model can develop any of
its elements as a model. Once a model activates an element, that element is
able to develop itself as a model, by direct interaction with the external
reality and with any other model of the brain.
Another functional facility is described here. We see that a model can
activate any of its elements to develop itself as a model. But, even if an
element is already developed as a model, the main model continues to treat it
as an element. This important feature will be developed below.
So, a main model has an element. This element has some properties. To
integrate that element, the main model uses these properties. Now, the
problems could be like: "why that element has such properties?" or "how such
properties can be changed?" To answer such questions, the main model has to
develop the element as a model. Once an element is developed as a model, its
properties appear to be truths generated by the model. So, depending of the
point of view, referring to the same entity, we discuss about an element with
some properties, or about a model with some associated truths.
Once an element is developed as a model, the model can be changed. A changed
model will have other associated truths, so that, when treated as an element
of the main model, it has another set of properties. Thus the properties
cannot be changed in a direct way, but through the changes in the model.
In any case, a main model can operate only with elements, regardless of the
fact that the element is or not already developed as a model.
We already use terms as "long range models" or "short range models". Let's
define them.
A long-range model has already been defined as a model with its own elements
developed as models. But here we will prefer another alternative definition. A
long-range model is a model which reaches its aims by activation and
deactivation of some of its elements. Such elements are already developed as
models.
A short-range model reaches its aims by direct activation.
Example: to switch on the light in a room, a ZM model will make a ZAM. That
ZAM will simulate the action. Based on this simulation it will activate an AZM
which, in turn, will switch on the light. The ZM-model will confirm the
success of the activity of the short-range ZAM model.
Example: To travel from a place to another, a ZM will make a ZAM. The ZAM will
make some ZAMs. These ZAMs will make some others ZAMs. For any specific
activity there will be a ZAM. Once a ZAM has reached its aim, it will be
deactivated by the ZAM-model which activated it, and a new ZAM is activated.
The general control belongs to the main-ZAM. The main-ZAM can be modified by
the main ZM. Long-range models do such activity.
Example: we enter a room and switch on the light. The light really switches
on. A local-ZM gets this information based on IR. But, a long-range ZM, which
contains the local-ZM as an element, understands that the light had been
broken, and now it is on. The local-ZM acts here as a shorter-range model. It
does not understand the general environment. The main-ZM (which contains the
local-ZM as element) is a long-range model.
We already saw that any model can activate any of its elements to self-develop
as a model. Once an element is activated, it develops itself as a model. In
turn, this new model can also activate as a model any of its elements. This
"depth" has only technological limits. In fact, almost any model of the brain
is a long-range model. The definitions, which are already given, respect this
feature.
Now we shall present a list with the main models of a brain:
ZAM: these models are usually long-range models. A ZM model makes them. Their
main function is to change the external reality. They are made for immediate
activation (to drink water from a glass, for instance) or they could be models
that give the orientation of the whole life of a person or anything between
these very large limits.
Such models are not changed by direct interaction with the external reality.
If a ZAM fails to do something, the upper ZAM or the local-ZM will build and
activate another ZAM.
During their activity, they have full access to any resource of the brain
(internal or external, by a ZM model).
AZM: these short-range models are direct-action models. They are connected
directly to different organs which can act on the external reality (hands,
legs..) They keep precise information about such organs. When a ZAM model has
to make a simulation of a specific action, the AZM models have to give precise
information about every feature of the associated organs.
Referring to ZAM and AZM models, any action on the external reality is based
on a simulation. Without a successful simulation, the brain is not able to do
any activity.
Once a simulation is a success, the main ZAM will activate the action (in
connection with local-ZM). The action will be the same as the simulated
action. This procedure is followed by any ZAM in any activity.
There are some exceptions. When the PSM takes control, some reflex-models are
activated without initialization and without simulation. The reason is the
highest speed of action, even if the action is not the right one.
ACTIVE-TYPE MODELS (normal ZM-models)
ZM models are made mainly by direct interaction with the external reality.
They generate the knowledge and consciousness. They are self-activated in any
situation when they are able to predict in a good way the possible evolution
of a given external reality.
A ZM, which interacts directly with the external reality, is also a model,
which controls the whole body. They build, activate and deactivate any ZAM,
based on a set of goals.
A long-range ZM model also controls a local-ZM. This is able to modify a
local-ZM model, based on long-range predictions.
The whole activity is supervised by PSM. Usually the PSM is activated only
when all the available ZMs fail to control the interaction with the external
reality.
A ZM model has full access to all the resources of the brain. It can take any
information from any part of the brain and can make any model based on any
available information.
By analyzing the normal activity of the brain, one understands that some
activities use only a limited number of models. The access to some models is
easier than to others. We can find very fast some information and find more
slowly other. This suggests that some models, which are usually employed
together, are grouped. We define a quasi-structure of models called MZM. A MZM
is a group of models, which are used often together. They can be associated
with some specific complex activities (job, hobby, family life, car driving
and so on).
STORY-TYPE MODELS
These are transition-ZMs. When there are some information from the external
reality, the normal activity of the brain is to build a normal ZM-model or to
find the best available ZM to integrate that information.
When the quantity of information is high, the brain has no technical
possibility to follow this normal mode of interaction. It is forced just to
record the information in a string-type mode. Such a record of data is called
a story-type model (S-M).
Note: some persons who already read this book were disturbed by the fact that
there are many sequences which are repeated in different parts of the book.
Unfortunately for such persons, this happened because they make story-type
models instead of a normal model. If they make story-type models and if there
is a repeated sequence, the local-ZM will jump back to the place where the
information was previously met. At that moment, the story-type models are
fragmenting. The person has lost the connection with the story-type model and
is forced to make a new one. Also, the person could try to reconnect the old
model with the new one, but this is difficult. For a person who makes a normal
model, when a sequence is repeated, this sequence will only confirm the
normal model and this is very good for the model.
Story-type models can be used as a source of information to make or develop,
off-line, normal models. Any element of such models can be developed as a
normal model later.
Although many people use this type of interaction with the external reality,
this mode of interaction is not efficient and uses a lot of the limited
resources of the brain.
Indeed, a story-type-model records the information in an explicit way, about
the same way as it is recorded on a tape-recorder. This mode is a very
primitive way of recording data. A normal model can generate a huge quantity
of information by simulation. Such information is not recorded there in an
explicit way.
Even more, a story-type model introduces non-normal relations between some
elements. As we know, a story-type model is made by elements connected between
them in the order of occurrence. So, two elements, which could have no
connection between them, could be recorded with a relation between them if
they occurred together. Anyway, there is no control and no long-range model to
control the recording of a story-type model.
Unfortunately, such models are very spread out all over the world, due to the
fact that there is too much information, and due to some big deficiencies of
the education policy.
So, an education based on normal models will reduce very much the quantity of
information, which has to be processed by a brain. The present education
policy is based on assimilation of external models. That is, the capacity to
build models is not used. So, faced with a huge quantity of information, the
population is forced to make story-type models. This will reduce even more the
capacity of the population to make normal models.
Example: a taxi driver must know any route in a city. There is a huge number
of such routes and he has to learn each, both directions. If the normal model
of the city is learned, then that taxi driver is able to find a route in any
conditions. Except for the normal model of the city, it is not necessary to
learn anything else. By story-type models (to learn routes) he has to increase
the quantity of information with every new route. This is an example, but the
situation is met in almost any field of activity. In practice, both methods
are used.
Story-type models developed as long-range models are very dangerous, because
they can stimulate induced-paranoia (XIP) or a schizophrenic-paranoiac complex
(XSPC). This is so because a story-type model has special relations between
its elements. Such relations are generated by the arbitrary occurrence of the
elements and thus, to transform the story-type model into a family of normal
models becomes difficult (the brain has to build from scratch several new
normal models, based on the information generated by a story-type model, and
this is not easy).
The story-type models are integrated in the normal structure of models and
they are controlled by that structure.
SHIELDING MODELS
We already saw that any model evolves independently, by itself, based on the
information taken from external reality or from others models. The aim of any
model is to gain its stability. Once a model has a problem, it will continue
to be active up to the moment when it regains stability.
There are some problems without solution. The model will continue to look for
a solution forever. This activity can produce negative effects on the overall
stability of the structure of models of the brain (it consumes a lot of
energy).
The main problem without solution is death (human beings only).
This is a basic problem. So, there is a model which predicts the death of a
person and that model has no solution to the problem. When there is no model
to solve a problem, the PSM is activated. The PSM has no solution too and so
it will make a specific model to solve the problem. But the new model has no
solution either, and so, a dangerous loop is activated. This activity could be
very dangerous for the stability of the structure of models of any mature
human being.
Since the oldest times, the human beings found a solution: shielding models.
A shielding model is a model, which is made to prevent a normal model from
activating the PSM and also to transmit to the model with problems some
information to stabilize it.
The best-known shielding model is religion.
Observation: as a person becomes older and older, the prediction of death is
more and more precise. The person has the tendency to become more and more
religious. Also, when a population is under stress, it has also the tendency
to become more and more religious.
A shielding model is associated to a normal model which has problems. A
shielding model is not based on external reality. It cannot be included in a
normal model, as the normal model cannot include a model which is not based on
external reality.
The reality generated by a shielding model can be called "illusion".
The shielding model can be made for any problem without solution. Such models
reduce the nonsense activity of a brain and so, there is more energy to solve
the normal problems. But, such models could be also very dangerous. The
activation of a shielding model also deactivates the protection structure of a
person or at least some section of it.
The shielding models are the main models, which can pass from 'normal-to-PSM'
zone to PSM. Such changes could be very dangerous for that being, because some
protection models are deactivated forever.
The shielding models are partially integrated in the normal structure of
models and so, the structure can, partially, control them.
ACTIVABLE MODELS (WBAM)
A ZM could predict a future situation of the external reality, which has no
associated model. Such a situation can activate the PSM. To prevent this, the
ZM can make a would-be active-type model (WBAM). Such a model is not created
by direct interaction with the external reality. Such a WBAM acts as a
shielding model up to the last moment before the activation. After activation,
it becomes a normal ZM model.
A normal ZM is built in direct interaction with external reality. WBAMs can be
associated with the external reality without previous interaction with it.
Note: the emotion is defined in MDT as a transient situation between the
activation of the PSM and the moment when a normal suitable model is
activated. The activation of the PSM can be prevented by a good WBAM (of
course, if that situation was predicted by a main ZM).
WBAMs are included in the normal structure of the models and they are
controlled by it.
ILLEGAL MODELS (XZM)
All types of models described up to now are normal models. They are included
in a harmonic/logic way in the structure.
There are some models, which are not included in the normal structure of
models, or they have lost their normal connection to the structure. Such
models are called "illegal models" or XZM.
There are many situations which can produce illegal models. A case is when a
new model is not finished because the specific external reality, which
produced it, is no met anymore.
For instance, somebody has been involved in a car accident. A new model is
started, but because such situation will not be met again in the near future,
the model is not finished, because there is no external reality to finish it.
Such model could evolve as an illegal model.
Observation: there is an empirical method of the "classical" psychiatry to
stimulate or even to force a person (mainly children) to tell everything which
is associated with a traumatic situation. MDT says that such a method is very
good because, in this way, a possible illegal model will be forced to connect
to the normal structure of models and so, the long-range negative effects are
prevented. As we see, MDT can explain exactly why this psychiatric empirical
procedure is good, as MDT was not even created specifically for the
psychiatric field!
Another situation when an XZM could be created is when a model is too large.
Such a model could be fragmented and some components can lose the normal
connection with the structure. The fragments can evolve as illegal models.
The story-type models are also candidates to become XZM (at least some parts
of them).
A major cause of the occurrence of illegal models is technological problems.
As we know, a normal structure of models is made of many models, which are
connected together in a harmonic/logic way. The models communicate between
them but, if the communication is not good due to technological problems,
some models can become illegal.
Such process can also generate half-XZM models. Such models have little
communications with the other models, or the communication can be only in
association with some other models, or only in association with some specific
situations of the external reality.
Because such models are no controlled anymore by the normal structure of
models, they can contain anything. They can obtain information from the
external reality or from other models, or they can create and activate models
which can act on the external reality (ZAM and AZM).
XZM models could be dangerous, or even very dangerous, because a person can do
some things outside his/her consciousness. A person that has such models does
not know that such models exist in his/her brain. Some of these models can be
detected during hypnosis practice.
XZMs can explain somnambulist-effect, double-personality, and many illogical
or bizarre activities. They can also explain some crimes, including the
serial-killer phenomenon or terrorism-related crimes. Such a person is just
"remote-controlled" by the XZMs.
The illegal models can explain also some paranormal phenomena.
PARANORMAL PHENOMENA
Telepathy is considered as a direct communication between two brains. Even
more, this kind of communication is performed at great distance between the
two brains and through any kind of media.
Unfortunately, this kind of transmission of information is not possible, based
on the laws of the nature. In order to transmit information, it is necessary
to transmit energy at the distance. The known fields of forces (electric,
magnetic, electro-magnetic and gravitational) do not meet the requirements for
such a transmission. Even more, even if there is a field of forces which can
propagate at large distance through any kind of material, in order to transmit
information, modulation of the energy, depending on the information, is also
necessary. At the receiver it is necessary to demodulate the energy changes,
in order to get the message.
Some could say that the information could be transmitted by a 'shortcut',
without transmitting the energy at the distance. This interferes with the
basics of the sciences of nature.
Anyways, I believe in natural sciences, and the only conclusion is that, for
now and forever, telepathy, as a direct transmission of information from a
brain to another, does not exist.
MDT explains "telepathy" in the frame of the laws of nature, without any kind
of transmission of information at the distance. The phenomenon is based on the
huge capacity of the brain to process information and on XZM models.
As we know, the basic function of any brain is to make models and to simulate
the possible evolution of them. A model, which is associated with an external
reality, is able to predict the evolution of that external reality. So, at any
moment, we make predictions associated with the external reality, and the
majority of them are good.
Now, let's suppose that a person has a special relation with another person,
as a mother and her child, for instance. The model associated with her child
could have been active for many years. Such a model could become a XZM model.
This XZM is active outside the control of the mother. Such an XZM could
simulate the interaction between the child and different kinds of
environments. When a negative prediction occurs, such a model can transmit a
message to the local-ZM. The mother "receives" a message. The "receiver"
cannot find the source and the reason for that message, because an XZM-model,
not belonging to the normal structure of models, transmits the message. It is
very easy to consider that such a message is transmitted by "telepathy".
So, MDT considers that such messages are generated by simulation on an XZM-
model and so, they are just predictions. In some cases, such predictions could
be correct (the predictions which are not correct are forgotten !!!). Such
messages are not related with the external reality.
Some of such predictions could also be obtained during a hypnosis session,
because hypnosis is associated only with XZMs.
The same basic explanation is valid for the clairvoyance phenomenon. In such a
case, the XZM is associated with a specific external reality, or with an
illness.
Such predictions could be correct for many situations, but, because they are
just predictions, there is a limited guarantee on their correctness.
Example: a person was "seen" by a clairvoyance medium. This medium was asked
on the status of the heart of that person. The answer was that the heart is in
a good shape. The answer was correct. But there was a "little" problem: that
person was wearing a pacemaker, which was not "seen" by the medium, in
accordance with MDT.
MDT can be used to see how to develop such paranormal qualities. First of all,
for it, let's remember that XZM are image models and so, developing the
interaction with external reality based on image models is strongly
recommended. Also, a natural tendency towards image models is mandatory.
Such persons must be well balanced, or able to obtain a stability status by
different methods, so that the normal structure of models has a reduced
activity. Such persons must have a reduced tendency to control the activity
associated with the problem (to reduce even more the activity of the normal
structure of models).
It is also very important to obtain as much as possible information by direct
interaction (based on image models) with the problem. The information based on
symbolic models could be useful too, after translation on image models.
MDT considers that XZM models are image models. But, there is a supposition
that some symbolic-models could be illegal too. If so, an XZM-symbolic model
could explain, e.g., how some persons can perform extremely complicated
arithmetical operations.
THE NORMAL HUMAN BRAIN
This section was intended to treat the subject declared, but instead, it is
just an evaluation of the problem. The reason is the inexistence of sufficient
data on XZM models.
To make a local model on the normal human brain, we take some conditions from
MDT, as follows:
C1: The PSM must act to protect the being and to ensure the unconditional
survival, forever, of that being. The PSM must also contain some models
associated with the society in which the being lives. The PSM must not contain
ordinary models.
C2: Any model of the brain must be stable (harmonic or logic).
C3: The whole structure of models must be stable. That is, any truth of any
model must be accepted (or at least not rejected) by any other model of the
brain.
Let's develop a little this local model.
The main condition of normality is that the person has to be accepted by the
society. That is, the person has to integrate in that society. For a cannibal-
type society, the person has to integrate in that society. Otherwise he will
be rejected by the society. The limits or normality are, as we see, very
broad.
For a democratic society of our time, some of the conditions of normality are
"not to kill", "not to steal" and so on. Such models must be in the PSM and
this goal is achieved by education since many generations.
Let's consider that a person makes a model to kill someone. If this model is
blocked by PSM, that person can be considered as a normal one.
However, if a person makes a model to kill someone and, in some conditions,
the PSM does not work properly, that model can be activated. Based on MDT,
such a situation is a hardware problem and so, that person is not a normal
one.
In "classical" psychiatry, they make a test to understand if the person was or
not responsible for his/her acts. Based on MDT, as I said, here we have a
hardware problem and so, the fact that the person was or not conscious of what
he was doing is not relevant. Even more, based on MDT, a model cannot be
destroyed by any hardware or software facility of the brain. So, a punishment
has no effect.
If a brain has a hardware problem, there is no solution to correct it. The
main reason is the fact that any model is connected with almost all the models
of the brain. Even XZMs must have some connections. In order to remove a model
by external action, it is necessary to know the exact hardware structure of
that brain and this, as I think, will be not possible at least in the next 50
years.
C1 asserts also the condition that the brain must not contain ordinary models
(O.M.). This condition is necessary because if an O.M. is included in PSM,
that model becomes invariant (it cannot be changed by any information from the
external reality). So, if an O.M. is included in PSM, any information obtained
by IR from external reality must be compatible with that OMPSM. If not, that
information must be distorted to meet, somehow, the condition requested by the
OMPSM. When there is an OMPSM in the brain, this is an illness called
"paranoia".
A person with an OMPSM must distort the information obtained from external
reality to meet the conditions requested by the OMPSM.
Example: The authentic communists have included in PSM the OMPSM called "the
working class is the leader of the society". Regardless of the external
reality, they have a harmonic/logic structure of models based on this model.
Fortunately, the absolute majority of the communists have no such model
included in PSM and so, they are normal persons.
Example: Usually, drugs create an OMPSM called "use them". Such persons will
continue to use drugs regardless of any information associated with their
negative effects. This is a special kind of paranoia.
Example: smoking is also a form of paranoia, due to the same reason, as above.
After many years of smoking, some persons can give up smoking. This could
happen if, for instance, the person gets ill. The illness could make a non-
smoking model, which enters the PSM too.
The C3-condition states that the whole structure of models must be
harmonic/logic. This condition is not easy to meet. First of all, there is a
limited capacity to refresh the whole structure of models. The refresh
capacity for some persons could be under the requirements. Such persons could
evolve to a form of schizophrenia.
Let's consider now a person-A, who meets the C3 criterium. At one moment, an
important model becomes useless (for instance, an important person B
disappears from the life of A). In such case, person-A has to refresh the
whole structure of models. This task could exceed the technical capacity of
refresh (mainly for older persons).
It the refresh capacity is exceeded, one possibility is to make shielding
models. If a person has too many shielding models, such a person cannot be
considered as a normal person. Such persons can be detected, e.g. due to the
fact that they don't want, or they cannot discuss about some subjects.
XZM models are not taken into account because of the lack of enough data about
them. XZMs can explain the somnambulistic-effect, multiple personalities or
even some nonsense crimes.
There are killers who don't know why they kill other people. Many of them seem
to be normal persons, as their friends can confirm and also they can be
integrated in society. XZMs can be an explanation for their crimes. Indeed, an
XZM is a model which is out of the control of the normal structure of models.
Such models can become active-models in some situations (due to the hardware
problems of that brain). The killer is so "remotely-controlled" by the XZM.
Such killers cannot be detected by a lie detector. The explanation is the fact
that there is no normal model that makes the crime and so, there is no reason
to pretend or hide something.
As I said, this section is just for evaluation. As new data will be obtained
in association with XZMs, the section will be developed.
THE ABSTRACT OF THE FUNCTIONAL FACILITIES OF A BRAIN
Let's make an abstract about all the functional facilities of a human brain.
Almost all the facilities, which are not related with symbolic-models, are the
same for animals.
BF1: To make models associated or not with a section of the external reality
BF2: To refresh, on and on, the M-models by prediction and comparison with IR,
so that M-models reflect better and better the dynamic external reality.
BF3: The continuous self-refreshing of some ZM coupled with M-models. The goal
is that these ZM-models reflect better and better the external reality. For
this, ZM must take into account any other ZM-model of the brain as well.
BF4: To simulate, continuously, the possible evolution of the associated
external reality, even when a ZM is not connected to M-models.
BF5: One of the main conditions, which must be fulfilled by any model, is to
become stable (harmonic or logic). That is, any simulation on a model must
reconfirm the model in the same shape. If a disharmony or logical
contradiction is detected, the model must regain its stability by IR (from
external reality or from other models). Moreover, as any model is already
integrated in a structure of models, any other model must accept any result of
any simulation on any model. This condition ensures the general stability of a
structure of models. A real brain does not easily meet this condition.
BF6: Any ZMs are able to activate, in time sharing, many ZAM models to do many
activities. However, there is a single ZAM which can act on the external
reality at a given moment of time. The reason for it is that, before
activation, any model needs to initialize using data taken from external
reality. When a ZAM is deactivated, it needs to store data for future
reactivation. This method is fast, but if external reality is changed too
much, such data is no more valid. In this case, the activated ZAM has to find
the new conditions of initialization, based on ZMs. The brain uses both
methods. By description of the process, we see that it is not easy to do many
activities at the same time (in time-sharing), and it is easy to make
mistakes.
BF7: The facility of any model to gain information from any other model of the
brain. However, due to the technological implementation, it is possible that
some models have a better communications with some models, and not as easy
communication with other models.
BF8: Any model has the facility to develop any of its elements as models.
Thus, it is possible to have a nested structure of models. The "depth" of this
structure has only technological limitations.
These facilities generate the knowledge and the consciousness, based on a
structure of stable (harmonic or logic) models. Such structure is able to
self-develop in an unknown external reality.
For a given brain, in interaction with an external reality, there are a number
of features which will be described now. That is, as a brain has many modes of
interaction with external reality, a particular brain could use mostly only
some of them, as follows:
SF1: If there is a difference between reality (prediction) and the external
reality (IR), a brain has some possibilities:
SF1.1: to correct the model based on IR (knowledge)
SF1.2: to modify the external reality (creativity)
SF1.3: to store IR in a story-type model
SF1.4: to ignore or to forget that IR
SF2: When a model is "correct", but it cannot be integrated in the structure
of models, there are some possibilities:
SF2.1: to make a shielding model (the external reality is considered as wrong)
SF2.2: to modify the whole structure of models (knowledge at any price, but
sometimes this can exceed the technical possibilities of a given brain).
SF2.3: to modify the model (i.e. to distort the importance of some elements or
relations so that, the modified model can be accepted by the structure). When
this procedure is followed, we have a paranoiac behavior.
SF2.4: the model with problems is ignored, or it is recorded as a story-type
model.
SF3: when there is an external reality and no suitable model, there are some
possibilities:
SF3.1: to create a suitable model, initiated by PSM
SF3.2: to ignore that external reality
SF3.3: to record that external reality based on a set of more or less
fragmented story-type models.
THE PERSONALITY (HUMAN ONLY)
The personality is treated here for human beings only. However, some
characteristics (which are not related in a direct or indirect way with the
symbolic models), are about the same for animals.
The personality is given by the whole structure of models of a given human
being. We shall develop this very complex concept. To do this, at the
beginning, we shall see a number of features in a rather random way and then,
based on these descriptions, we shall list some important parameters which
characterize the personality.
We know from the general theory that any brain makes models and simulates the
possible evolution of these models. There are no restrictions in connection
with the aims or goals of such simulations. Even for a simple model, the
number of different simulations could be high. Of course, a model will not
make all the possible simulations.
A characteristic of the personality is associated with this diversity of aims
and goals of any model.
A structure of models could evolve in a chaotic way, out of control. Another
parameter of the personality is associated with the capability to control such
a diversity of evolution of a structure of models.
As we know from the general theory, the stability in a model is a brain
quality parameter. Thus, the aims and goals of any model have to be controlled
by a limited number of long-range models. Without such long-range models, the
structure can evolve in a chaotic way (this is a form of schizophrenia).
Faced with a new external reality, the model which gives the best predictions
of the evolution of that external reality will be activated. However, when the
external reality is complex, the main model has to activate some other models,
to be able to predict better and better the evolution of that external
reality. A parameter of the personality is the capacity to keep control of the
main activity even when the main model activates some others model. Thus, the
stability in the main model is a parameter associated with the personality.
Example: there are some persons who start from a subject and evolve in a
rather chaotic way to other subjects so that the main subject is sometimes
forgotten.
Another parameter of a personality is associated with the fact that, although
the structure of models has to be stable, the structure must be compatible
with some models imposed from outside, by education. Without some main models
imposed from outside (by education), a human being will be not compatible with
the external reality.
By education, some models must be present in any brain (some of them must be
in the PSM). Any human being is able to integrate into society, based on them.
There are now very big problems associated with education, in the present
human society. The main problem is the fact that the society (including in
most advanced countries) is evolving very fast based on symbolic models and
the education is not able to keep the pace with this fast evolution. E.g. the
usual method of education is to impose some story-type model (i.e. some models
of "how to do"-type). This method has increased too much the number of models
that must be stored by the brain and the brain is not capable anymore to store
and use all of them. Based on MDT, the normal solution should be to store some
normal models that can be tailored by each person to any specific situation.
Another parameter is associated with the tendency to think and act based on
long-range models or short-range models. Some persons behave based on a number
of long-range concept models (principles) which are used in any situation.
Other persons have specific short-range models for any specific external
reality. The personality parameter is typically situated between the two
limits mentioned above.
From the general theory, we know that some models generate knowledge and
others are used to modify the external reality. Thus, there are personalities
oriented mostly to knowledge and others are oriented mostly to change the
external reality.
There are persons who assimilate easily external models and others who prefer
to make their own models.
Also, there are image models and symbolic models.
We can make a partial matrix associated with a personality based on the
capacity to make/assimilate image/symbolic models, for instance.
Another very important parameter is associated with the content of the PSM. As
we know, a number of external models must be included in the PSM, by the
education process, so that the person is integrated in society. Unfortunately,
a lot of models could enter in PSM, in an uncontrolled way. Some of these
models could be bad models. They can be built, e.g. if a person is born and
lives (at least in childhood) in a bad environment. For a person who has such
bad models, there is still a chance to integrate in a normal society, by
making some shielding models. However, a shielding model is, usually, not safe
enough. Thus, in some situations, a person can act based on the bad models and
not based on the shielding models which had helped him/her to be accepted by
the society. Unfortunately, it is very difficult to know in advance the
content of the PSM, because the PSM acts only in very special and critical
situations. To be understood, this subject needs a lot of further work.
Here we present a general theory. It cannot go beyond some limits because the
technological implementation is, usually, not taken into account. However,
based on the theory, it is possible to develop the subject for specific
applications.
Now we shall list some parameters associated with the personality, based on
the above discussion. Some of the parameters associated with the personality
could be:
The orientation to image models
The orientation to symbolic models
The orientation to knowledge
The orientation to action on external reality
The orientation to make new models
The orientation to assimilate new models
The orientation on short-range models
The orientation on long-range models
The parameter associated with the diversity of action
The parameter associated with the stability in a model
The parameter associated with the conformity to society requirements
The parameter associated with non-standard models from PSM
A table could be made, for any person, with numerical values associated to the
above parameters. To do this, a local model must be developed. That model has
to contain a set of standard procedures to obtain such parameters.
This chapter, which is associated with the personality, refers only to normal,
mature persons (as these terms are already defined). The pathological cases
are not taken into account here. In fact, to study the pathological cases is a
nonsense before defining the normal situation.
This general theory, as it will be developed for specific situations, is
useful to understand also pathological cases. For instance, MDT defines XZM-
models (illegal models) as models which are not integrated in the normal
structure of models. Such models could be very important to issues related to
the personality, but there are still few data about XZM models.
There is another very important parameter associated with the personality,
which was not described above; it is a parameter associated to the
consciousness. Because it is so important, it will be described in a separated
section.
THE CONSCIOUSNESS
It is considered that there are some long-range ZM models (image or symbolic),
which contain the being as an element. When such a model is activated, it has
to initialize. That is, it has to find the positions of all the elements
(including the being itself) and to find all the relations between the
elements by interaction with the external reality.
The consciousness is the capacity of a brain to make and operate a model,
which contains the being as an element.
It is very important to emphasize that such models are normal models, which
are made by that brain in interaction with the external reality. Such models
cannot be assimilated by education, for instance.
The level of consciousness is associated with the capacity of that brain to
find and refresh, in a continuos way, the position of the being in a model.
Such models are long-range models. Their elements are already developed as
models. Some models can also contain some elements associated with the person.
The number of planes of consciousness could be high.
Example: I am a Romanian citizen. I live in Europe, so I am also European. I
have a job; I have a position there. I live in a block of flats; I have also a
position in relation with the others who also live in my block of flats, and
so on.
There are some models, which does not contain the person in an explicit way.
This is level-1 of conciousness. Only some parts of that person are taken into
account. The consciousness is of level 2 when the person appears in an
explicit way in relation with other persons. On level 2, the person is
integrated in a group; the person knows the aims and the rules of the group
and acts accordingly.
Examples: when a person drinks water from a glass, the person does not appear
in an explicit way; only some components of that person are taken into
account. If the person knows what he is doing, and is able to predict his
evolution, then he is on level 1 of consciousness. If a person plays a game in
a team, and he knows the aims and the rules of the group and communicates with
the members of the group, then that person is on level 2 of consciousness. On
level 2, the person is integrated in the model, as an explicit element, as any
other person of that group.
Problem: On level 2, a possible problem is to consider one's own activity as a
good one, and to consider that some other members of the group are low quality
persons. This could happen with a non-homogenous group, but also it is
possible that the model is a low quality one (the person has made a low
quality model associated with the aims and the rules of the group). As we
know, any model is made to be stable (logical or harmonic). We also know that
the stability of a model is not a guarantee that the model reflects in a good
way the external reality. Thus, for a good level 2 of consciousness, it is
necessary that all the members of the group have about the same basic model.
Observation: it is possible that faced with a new external reality, for which
there is no available model, the PSM activates itself. As the PSM is
activated, all the normal models are disabled and so the consciousness
disappears. Such a situation is called "shock status". The consciousness
returns only after the normal structure of models regains control.
The highest level of consciousness is level 3. There are few persons who are
able to reach level 3 of consciousness. It is not easy to understand the
explanations associated with this level.
On level 3, a person is able, e.g. to think with "the others' head". Also, on
this level, a person is able to see how the others see him. This implies to
make a model which contains the model of the group as an element in a longer-
range model.
On level 3, the brain has to work very hard. There are few person who are able
to do such an effort. It is harder to do such an effort on image models than
on symbolic models. Usually, level 3 of consciousness is met on symbolic
models. However, the word "empathy" can be associated on image models, with a
low level 3 of consciousness.
Note: Level 3 requests a hard effort for a brain and at the same time, the
personal advantage from such effort is not too high. Thus, the absolute
majority of the population is on level 1 and 2.
The persons able to stay on level 3 are the elite of a group.
Example: let's see an example involving car driving. On level 1, a driver is
reacting only when a situation occurs, or is about to occur. On level 2, a
driver is able to predict what the other drivers will do beforehand. On level
3, a driver is able to understand every driver around him, and he is also able
to take in account some possible problems, which can occur in association with
the overall traffic problems. Of course, the best drivers are those on level
3, but the effort to stay on level 3 is so big, that, at some moments, the
brain will not be able to do such an effort, and the driver "drops" on level
1, when he can cause accidents. This could be the explanation of some
"inexplicable" accidents, with persons who are considered as very good from a
professional point of view. Of course, this is a very general problem; it is
not related only with car drivers.
We already defined the elite of a group as those persons who are able to stay
on level 3. Let's consider that a person has to work in a position where one
has to take care of the community. Such persons must anticipate what problems
could occur in future, to be able to protect the community. Level 3 is
absolutely necessary. But, there is a problem. When a person is to be selected
for such a job, he has to gain some abilities. The problem here is that such
abilities are, usually, obtained after some specific training.
The training courses have, as main goal, to ensure that the students have
assimilated a number of models. When a problem associated with such models
occurs, they will activate the suitable model, and so they will solve the
problem. But, to be able to do the job in a good way, the main quality is not
to have the right model, when the problem occurs, but to anticipate fast
enough, what kind of problem will occur. That is, to be on level 3. I never
heard that the selection of personnel is done based also on the level of
consciousness criterion. Even worse, the persons who are able to assimilate
easily new models, have a reduced capacity to make their own models (as level
3 requires) and so, the present system of education stimulates the students to
have a low level of consciousness.
The present level of development of the human brain is too low to have, on a
large scale, a level 3 of symbolic consciousness.
The consciousness based on symbolic models is requested in any situation when
an elite group is necessary. In such a situation, every individual of the
group is associated with a symbolic element. Such a symbolic element contains
nothing which could be associated with the "human" part of an individual (no
emotions, no feelings, no love and so on).
Let's see now the consciousness in the animal world. Some superior animals,
which live in packs, know their position in the pack. So, there is a form of
level 2 image consciouness for such animals. Of course, such a level is
associated with a single model, which is made by every individual of the pack.
Even more, the position of every individual could be changed in time.
But what about ants. There is very little probability that an ant is able to
make models in interaction with the external reality. The ants are based on
the models of their PSM, (which are ready made when they are born). For
instance, level-2 of consciousness could be recognized when there is a
competition between the members of the group, as it happens in a pack of
mammals, or when an individual has to be trained. Such things cannot be met in
the world of the ants. Thus, ants have no consciousness (except level 0) as a
result of their incapacity to make models on their own.
Some superior animals, which live in association with human beings (e.g.
dogs), are able to create on their own some models of interaction with the
human beings. So, they could have level 2 consciousness.
ABSTRACT: MODEL DICTIONARY
M: these are models associated in a direct way with sense organs (M-eyes, M-
ears and so on).
YM: concept models directly or indirectly associated with different entities
of the external reality.
ZM: General long-range models. For any external reality, the brain makes one
or more ZM-models. They generate the truths, the reality, the knowledge and
the consciousness.
ZM-models are activated by the associated external reality. There are also ZM-
models that are not associated to an external reality (e.g. when we solve a
problem of mathematics).
Any ZM-model associated to an external reality works in association with some
M-models, and also in assocition with any other ZM-model.
MZM: this term is not associated with a model, but with a structure of
different ZM, YM, ZAM, and AZM models. These models are very often used
together. Such a structure is generated by the technological implementation of
the brain, and it optimizes the activity of the brain in a section of the
external reality.
ZAM: these models are long-range models used to modify the external reality.
They are artificial models (they are not generated by direct interaction with
the external reality) and they are also invariant (they cannot be changed by
direct interaction with the external reality).
AZM: these models are associated with the organs that can interact with the
external reality (hands, legs and so on) in a direct way.
XZM: these models are called also "illegal models", because they are not
included in the normal structure of models. A normal model is a model for
which any prediction is accepted in a harmonic/logic way by any other model of
the structure. XZMs are, thus, individual models which have no normal
communication with other models. Thus, a brain is not able to detect such
models. In some situations, such models can become active and gain control of
the being. They can also transmit some information to the normal structure of
models.
WBAM (would be-active models): such models are artificial models that are
generated by a ZM-model. Thus, a ZM-model predicts a situation for which there
is no normal model. If a new external reality occurs, and there is no normal
model to understand it, the PSM is activated. A ZM-model can make a WBAM-
model, based on its predictions, so that, when the new external reality
occurs, the ZM will activate that WBAM and so PSM is not activated.
SHIELDING MODELS: Any model has the tendency to become stable. There are some
models which cannot become stable. Such models can destabilize the whole
structure of models due to some infinite loops performed in order to gain
stability (the model with problems will activate some other models, including
the PSM, in a continuous way). A shielding model is created by the main ZM. It
intercepts some truths which can activate some other models (incuding the PSM)
and transmits to the model with problems some information which stabilizes it.
The reality generated by a shielding model is called "illusion". The best
known shielding-model is religion. This shielding model stabilizes any model
which predicts the death of the person so it blocks the activation of the PSM.
STORY-TYPE MODELS: Faced with a new external reality, the normal tendency of
the brain is to make a normal model, or to activate a suitable model from its
collection of models. But, when the external reality is changing very fast,
this procedure cannot be followed. In this case, the brain records the
information based on short-range models. These short-range models are
connected between them based on the order of occurence. Such a model (string-
type) is called "story-type model". Story-type models are used later ("off
line") to make or improve the normal models.
PROTECTION AND SURVIVAL MODEL (PSM)
This is the fundamental image model of any brain. When a new being is born,
the brain contains only the PSM. The PSM contains a collection of basic short
range models (e.g. reflex actions) and long-range models (e.g. the instincts)
for a minimal protection of that being and to ensure the unconditional
survival of that being, forever (these are the basic design features).
The PSM contains also a model of the external body (bones, muscles, and so on)
and also some basic models of interaction with the external reality (e.g. the
model to follow with the eyes the movement of an entity from external reality,
or the model to touch an entity from external reality, which is in the range
of the hand). There are also some models to ensure the equilibrium of the
physical body.
Faced with a new external reality, the PSM is activated and it tries to solve
the problem, based on its short-range models (e.g. reflex actions), but it
will also create a new element, which is associated to the new external
reality. Once the new element is created by PSM, this element is self-
developing as a model, in order to understand the new external reality. When
such an external reality occurs again, the specialized model created during
the first occurence of the new external reality will be activated instead of
the PSM. Such models are normal models (they do not belong to PSM).
Thus, as a new born being gains experience, the PSM will not be activated, but
the models previously created in the interaction of that being with the
external reality.
A model, which belongs to PSM, cannot be changed regardless of the information
received from external reality (the PSM contains only invariant models). In
special conditions, e.g. when a big danger exists for the being (as detected
by PSM), it is possible that a new model enters the PSM. Basically speaking,
any model can enter the PSM. For a normal brain, the PSM must contain only
"standard models" (see the general theory and ETAs) because, once a model is
in PSM, it cannot be changed regardless of the information received from
external reality. Even more, any information from external reality can be
accepted only if it can be accepted by PSM.
Example: Let's suppose that in the PSM of a person there is a non-standard
model which considers that the frogs are very dangerous. Regardless of the
information received from external reality, that person will be horrified when
frogs are around.
The content of the PSM is very hard to be known because the PSM is activated
only when there is no normal model to understand the external reality.
The PSM is an image model and it will remain so forever.
EXAMPLES, TESTS AND APPLICATIONS (ETA) ASSOCIATED TO THE MDT THEORY
These ETAs are intergrant parts of MDT and show how it works in some specific
cases. The order of occurence of the subjects is random. MDT tries to keep its
generality as much as possible, independent of the technological
implementation of different brains.
ETA 1: The Model
The model is a collection of elements and relations between the elements.
There are two types of models: image models (or analogic models) and symbolic
models. The elements and relationships are given explicitly for the symbolic
models, and implicitly for the image models.
Image models (analogic) can't be given in an explicit manner. They are given
as they are, as a whole. This is an intrinsic property of the image models.
To give a model in an explcit manner means to describe the elements and the
relationship between the elements, but this takes us outside the analogic
model. That means to translate the image model into a symbolic model (we need
to use words to describe the image model). Even if the translated model is
associated to the image model, it is a different model.
Example: given an image model of an airplane, its elements are the main body,
the wings etc. One of the wings could break in two, so it is made of two
pieces. Actually, it contains an infinity of elements, as it could break in
any way. In any real situation, it is by far easier to build an image model,
than explain what had been built. This is why we say that an image model is
just given as it is, and not defined explicitly. Anytime we refer to an image
model, we need to take into account this fundamental issue.
Application 1:
Image models in poetry and painting
A poet imagines something- there is an image model in his mind. The poet will
translate somehow this image model into several symbolic models (e.g.
statements), trying in fact to associate the image model from his mind to a
collection of symbolic models, materialised in the text of the poem. It is
assumed that the text of the poem, together with other image-type elements
(Rythm, rhyme, intonation etc) will be able to make the reader/listener to
reassemble somehow the initial image model from the poet's mind.
In the case of painting, the painter has in front of him a subject (e.g. a
person). This subject is perceived through all the senses the painter has.
What results is an image model of the subject based on this complex
interaction. This image model from the painter's mind will be translated into
another image model that will show on the canvas. The translation means only
to associate a model to another. The translated model can be built anyhow
within very large limits, based on the complex image model from the painter's
mind. It is supposed here as well, that the viewer will remake somehow as an
image model the initial model from the mind of the painter.
Application 2:
Image models from the external reality
Long time ago, when people needed to build some complex structures (e.g. a
fortress), in the first phase they had to make a sketch of what they intended
to build. This is valid only for less complex constructions. For more
complicated structures, the most used method was to build a 3D model. The
model can be easily analyzed and modified. With the model in sight, the brain
is able to simulate its behaviour for situations associated with the external
reality and to correct the discovered deficiencies, on the model. This model
can be used at the effective building of the external reality.
Nowadays, the image models are very highly developed. E.g. a model built based
on complex specs can be used to simulate its behaviour during an earthquake.
The data obtained can be used to predict the behaviour of the actual building.
The highly developed image models are used on large scale in technology
(skyscrapers, suspension bridges, airplanes, and actually in any complex
technological product). These image models can then be used to simulate
possible situations from external reality, including extreme situations,
before the actual construction of the technological product.
The symbolic models are built using GCL (General Communication Language). They
have explicit elements and relationships. They can be built only by humans.
The most important symbolic model is GCL itself. Its elements are in the first
place the nouns, as the relationship between elements are mainly the verbs.
Contrasting to image models, which evolve based on laws of harmony, symbolic
models evolve based on logic (see general theory). The presence of GCL in a
brain will define that brain as a human brain.
Important note:
GCL is not really a symbolic model. It contains only components (elements and
relationships). Whenever a symbolic model for communication is built (e.g. a
sentence), one needs to choose components from GCL. As any use of GCL is
materialised in a symbolic model and because there is no proper word for it,
GCL is considered by extension a symbolic model.
Technology uses models on a very large scale. Image models have initially been
used, but nowadays, due to the high costs of the image models and for other
reasons, symbolic models and the use of computers are favoured (e.g. symbolic
models are built currently for buildings, suspension bridges, airplanes and
spacecrafts, with the help of computers).
For training purposes, symbolic models are built and used for simulation of
nuclear plants, or flight behaviour, or anything, where it is necessary that
future crew/staff to gain experience beforehand. Present technology is based
in fact almost exclusively on symbolic models.
Application 3: From the iron to the space shuttle
Apparently an iron is too simple to require a design based on a symbolic
model. False.
Let's take a simple technological detail: the holes used for steam exhausts
for moisturising the tissue. Some questions are, e.g. how many holes it needs,
where, what shape and dimensions are needed for uniform moisturising of the
tissue with minimum water consumption and at lowest costs. Clearly, it is
possible to build analogic models, which can be tested experimentally. Based
on the analogic (image) models one can obtain certain results, but there is no
guarantee that the optimal solution was found. The existing image model cannot
be modified, as such. If we want to make any change in the image model we have
to rebuild it from scratch, as we already know, which implies time and money.
The vaporisation and dispersion process of the steam through a complex
structure as the surface of the iron, tissue and the support, is very complex.
Physicists, based on symbolic models, with help of computers, solve this type
of problem. The rebuilding of the model in order to find a better solution is
far simpler on a symbolic model, than on an image model.
If in the case of an iron, the highest risk is that the customers won't buy
the non-performing iron, in other cases the risks involved are unacceptable.
For instance, the space shuttle was 'verified' for reentering the atmosphere
on a symbolic model. This phase of the flight, by far the most dangerous,
would have been impossible to test before the actual flight. The crew was
trained on symbolic models in all the phases of the flight, and in all normal
and exceptional situations. The astronauts have learned to fly for reentering
the atmosphere, based mainly on training on symbolic models.
Given a model (image or symbolic), it can be used to predict its further
evolution. This is achieved by changing/ adding/ removing a parameter/
element/ relationship and following what happens. This process is called
simulation on the model. As we know, the results of the simulation on the
model are called truths associated to the model.
When a model is associated to external reality, by simulating on the model, we
can predict the evolution of the external reality. These operations are done
either by the human (image and symbolic) or the animal brains (image models
only).
We need to note here- it is as important, as it looks trivial: We extend to
the external reality the structure of symbolic and image models from our
brain. This extension is done not only in the domain of science and
technology, but also in all domains of life. For each of us, the world itself
is given as a sum of all the projections to external reality of all the active
models of the brain. This statement is true for animals as well.
Example: The laws voted in the parliament are long-range symbolic models; they
are an extension of the structure of models from the brains of the authors of
the laws.
The prediction of the evolution of external reality (see general theory) is
the main requirement of design for the human or animal brain. Thus, this
requirement is fulfilled by the facility of the brain to build and operate
models.
ETA 2: Truth, reality, and communication
Any result of the simulation on a model is a truth associated to that model.
As pointed out in the general theory, a truth is associated by us to a
symbolic message (generated by a symbolic model); however in order to keep the
terminology simple, in the case of image models, a result obtained by
simulation on the model is also called 'truth', in spite of the fact that it
is used 'as is', without the necessity to explain it.
Example: If an animal builds an image model of the external reality,
predicting a dangerous situation, it is possible to find the solution to the
problem by simulation on the model. This solution (the truth) might be, e.g.
to flee. The truth will activate directly the preexistent action model, which
is in this case to flee.
We'll refer from now on only to symbolic models. If no model is specified, any
truth is nonsense.
Example: The truth is ãa car crashed into a wall". This truth might be
generated by any of the following models:
-accident
-test
-movie/cartoon
-computer game
In any of the above models, the specified truth is interpreted differently (it
has a different meaning).
The theory underlines thus, that the model which generated a truth needs to be
specified and accepted before the presentation of the truth. This basic
requirement is always met in positive sciences.
In common life, the declaration of the model is not always done, and often the
model does not even exist in an elaborate and coherent form. Emerging from
here a long line of conflicts between individuals, groups or cultural zones,
which all have their own reality associated to the same external reality. This
can be interpreted as a design deficiency of the brain. Some can compensate
this hardware deficiency by software, e.g. the individuals situated on level 3
of consciousness (see the general theory).
There is a fairly common situation in external reality when a person states a
truth, and then builds the model to support it. This happens usually for
persons based on image models only, and when they interact with external
reality, they only translate the image truth to a symbolic truth. Such persons
are recognisable by their rudimentary logic and their tendency to fragment any
discussion to particular sections of the external reality. Such persons can't
discuss a single general subject.
Exercise: Verify yourself and others on the existence and status of the model,
which generated any stated truth.
It is known from the general theory that a basic problem in the construction
of a model associated to the external reality is that we do not know
beforehand the elements of the specific external reality. These elements need
to be discovered, and the discovered elements are the only ones we can operate
with.
Warning: The external reality, as defined in MDT, can't have elements and
relationships. The elements and relations appear only in the model associated
to the external reality. However, in many statements we will use notions like
elements and relationships of the external reality, but these need to be
understood as elements and relations of the model associated to the external
reality. For the external reality, one can use the term 'entity', which
identified by the model will become an element of it. However, we have no word
available to associate to external reality in the case of relations. By
perfectioning the language, such deficiencies will be solved.
A basic requirement for the existence of communication is the existence of a
single common model accepted by both parts who want to communicate. Without a
common symbolic model, there is no communication, as both sides will have
their own list of definition of the terms associated to the words.
Usually, communication is done only on symbolic models. However, there are
more primitive forms of communication using image models (between people,
between humans and animals, between animals).
The reality is defined in the general theory as the sum of all truths
generated, or possibly generated, by a model. As each person has his/her own
collection of models, the reality as understood by each person is different
from one person to another.
It is important to specify that in the domain of positive sciences,
fundamental models generally accepted do exist. One of these models is e.g.
Newton's Mechanics. As this model generates a reality, all physicists consider
that the 'reality' is the one generated by Newton's Mechanics, within its
limits of applicability.
Due to reasons associated to confusions of the science of knowledge, the
reality generated by Newton's model is considered as 'objective'. Thus,
"objective reality" is a term generated by a generally accepted model in
specified conditions. From this point of view, the fact that the Sun revolves
around the Earth is an "objective truth", at least at the level of the year
1500.
It needs to be stated by all means that without a model, the external reality
cannot be perceived. After building a model associated to the external
reality, what we perceive is what the model states as perception. If, e.g. we
say that 'snow is white', this is the result generated by a model associated
with external reality, external reality which contains the element 'snow'. One
of the properties of the element 'snow' is that it is white. Under the
microscope (another model) the same snow looks transparent.
As we already mentioned, reality is the one generated by the model associated
to a given external reality. Each time we state a truth, we have to specify
first the model.
Example: There are an A and a B person. A is taller than B, as it results from
measurement. The term 'length' is generated of the model 'space', as Euclid's
Geometry and Newton's Mechanics understand it. These fundamental models
characterize this truth as objective. If we say that "A is more attractive
than B", this is a subjective truth. However a model has also generated this
truth, more or less elaborate/ specified and more or less accepted by
different persons.
The conclusion is that the term 'subjective truth' is resulting from a model,
which is not unanimously accepted or insufficiently elaborated. In this case,
it is clear that people should avoid such truths or should declare the model.
With the evolution of thinking, the term 'subjective truth' will be removed
from the thinking system.
ETA 3: Fundamental problems associated to scientific knowledge
Computers are known as devices used to play complex games based on
intelligence, to write texts of different types, to make calculations, to
store and manage data, to send or receive information, to build and operate
symbolic models, etc.
A question occurs however: which is the principle of work of a computer?
If we do not interact with the computer via a primary programming language
(Assembler or machine language), I believe that it is impossible to find the
principle of work of the computer either from in- or outside of it.
The fundamental function of a computer is to do logical and arithmetical
operations with binary numbers with the help of an electronic device
(register) called 'accumulator'.
If we are in a text editor, for instance, and we press a key corresponding to
a letter, that letter will show on the screen. For the unaware, it is
difficult to imagine that by pressing a key associated with a letter, a
register-accumulator will make hundreds or thousands of logical and
arithmetical operations on binary numbers, only to have that letter shown on
the screen.
This example wants to illustrate that, based on the external analysis of what
is happening, it is impossible to figure out the principle of work of a
ridiculously simple device as a computer (ridiculously simple compared to the
brain of a dog, e.g.)
The method used in positive sciences is not the analysis of primary data. The
method of analysis works on extremely simple systems, which can be perceived
on image models as well. The method used in positive sciences is to guess a
symbolic model, based more or less on the interaction with external reality,
and to verify the model.
It results that the method of understanding the brain based on the analysis of
primary data is at least inefficient.
A fundamental problem of knowledge is that primary facts can be understood
only if a model to integrate them already exists. Without a model, we are
forced to build one on the spot. Thus, each fact of the external reality could
be understood based on a local model. The correlation between facts, each
understood in its local model is impossible. This is why a method of guessing
a fundamental model was imposed. Based on the single fundamental model the
facts are interpreted and reinterpreted. Such a method allows the correlation
of the primary facts.
If the model does not make good predictions, it will be modified and the
process restarted from scratch, until we find the model in which all the
primary facts can be understood. The process stops when the predictions are
true with an acceptable rate. In that phase we can talk about knowledge.
As a comment, we need to say that the analytical method is based on short-
range models (can be affected by schizophrenia and XSPC), while the synthetic
method is based on long-range models which allow not only correlation between
facts, but also a cross-check between the local models.
The need for a single fundamental model comes from the fact that any used word
needs to have a unique definition. This is true only in case of the existence
of a single fundamental model.
Example: what would happen if in common language everybody used different
definitions for the words used? The communication would not exist, everyone
talking his/her own language.
The conclusion is that any positive science is based on a single fundamental
model, stated from the very start. This symbolic model can be based on primary
facts, results of the interaction with external reality or on theoretical
principles (e.g. the principle of inertia in Newton's Mechanics cannot be
visibly connected by facts seen in the external reality).
However, as in the external reality there are a huge number of facts difficult
to correlate, the method to find the fundamental symbolic model is guessing.
Once the model built, this will order in a univoque manner all the primary
facts. Moreover, it will make predictions that will lead to new discoveries or
confirmations of itself.
As we have shown in the general theory, we reflect sections of the external
reality in models. The models make predictions. If the predictions are good,
we will use the model a next time too, as it proved to be useful.
Now we have the normal answer to a fundamental question asked for long time:
'why do the laws of nature exist?' or 'Why the world has an order?'
As it results from MDT, we reflect the external reality based on symbolic
models. These symbolic models need to be logical in order to be stable. If a
symbolic model associated to external reality will not reflect it correctly,
we will build a new model.
Example: The external reality can change due to the movement of some objects.
Then we will build a symbolic model containing the term 'velocity'. This
symbolic model will make good predictions provided the objects move at a
constant velocity. If the velocity is not constant, the model will not reflect
correctly the external reality. Then we will build a new symbolic model,
introducing a new element called 'acceleration'. This model will make correct
prediction for the objects that move at variable velocities as well. Thus, by
building of adequate models, the external reality is reflected by stable
models.
It is very easy to confuse the external reality with its 'image' generated by
a stable symbolic model.
As we know, we have no direct acces to external reality. We perceive it based
on some associated models. Thus, as a conclusion, the impresion that nature is
a structure based on stable laws and order comes from the fact that we reflect
the external reality based on logical and stable symbolic models.
ETA 4: General Communication Language (GCL), dictionary
GCL is the first symbolic model generated by the human brain. At the
beginning, only its spoken form existed, later it appeared as a written
language too.
As the purpose of the construction of models is to predict the evolution of
external reality, GCL was always associated directly or indirectly with
external reality.
GCL is a very special symbolic model. It is used both for general
communication and for building other more precise symbolic models.
Examples of developed languages included in GCL: diplomatic language, juridic
language, logical and mathematical language, languages based on gestures and
signs, computer languages.
GCL can be used to build symbolic models that are associated to external
reality, e.g. the positive sciences.
It is supposed that GCL occurs by spontaneous interaction between people but
this is an abnormal mode of occurence. It is not clear to me that a language
can start from scratch, but let's suppose so. The abnormal mode of occurence
is associated with another aspect. The language for any device used to process
information (as the brain is) is made of a collection of terms and relations.
Any element/relation of the symbolic model (language) must be associated with
a component/function of the hardware. That is, the hardware must be known
before the language is built. This is the normal situation, e.g. when a
computer, which has no associated programs, has to be used.
But, as it is believed, the language used by the brain appeared without
knowing the hardware. The main consequence is that all the words, which have
to be associated with the basic feature of the hardware, have no precise
definition.
Thus, we find in dictionaries what I call "external definition" of the words.
That is, such definitions are not based on the hardware. MDT as a theory
associated with the hardware, generates "internal definitions" of the words.
Some such definitions will be given below.
Dictionary of internal definitions for some words:
1. To believe: there is an incomplete (unstable) model. Such a model could
become stable (harmonic/logic) if some artificial elements/relations are
included (artificial means that something is not generated by the interaction
with the external reality). After such changes, the model becomes stable. Any
truth generated by such a model must be associated with the word "to believe".
Also, the artificial changes must be specified before.
2. To know: there is a stable model (harmonic/logic) which is integrated in a
stable structure of models. Any truth generated by such a model can be
associated with "to know". I want to emphasize that from this does not result
in any way that the truth is correct, when compared to the external reality.
"To know" means just that the whole structure of models of the brain supports
that truth, and nothing more! As one can see, "to know" is associated only to
the structure of models, and not to the external reality.
3. As I know: there are some models which support a truth but some other
related models are not good enough to support that truth.
4. Correct, to be correct: this term has at least two meanings.
4a. There is a model generating a prediction in association with the external
reality. This prediction is compared with IR. If the result is positive, then
the truth is correct.
4b. There is a stable structure of models. Such a structure has already
predicted a large number of correct (4a) truths. In such a situation, any
truth generated by the structure is considered to be correct (see also the
definition of the term "to know").
To be correct based on definition 4a means to make an experiment (any
comparison between a prediction and IR is called "experiment"). There are a
very limited situation when an experiment can or may be done (e.g. if the
problem is to verify if a bridge will survive or not in case of an earthquake,
then such a problem cannot be solved based on an experiment).
Let's analize now a little the word "wrong". If a model generates wrong
predictions based on IR, this does not mean usually that the model is wrong.
This word is usually associated to a model, which is not suitable to a
specific external reality.
For instance Newton's Mechanics is wrong for objects, which travel at a speed
comparable with the speed of light, but is correct at low speed.
5. To understand: there is an incomplete model and there is an IR (from
external reality or from other models). The model is selfimproving based on
that IR. The term "understand" is used when a model is improved in such a way.
6. To imagine: is the main term associated to any operation on image models.
7. To think: it is the main term associated to any operation on symbolic
models.
For human beings, usually, the symbolic models are mixed with image models but
when "to think" is used, the general frame continues to be a symbolic one.
8. Intelligence: is the facility to make and operate a long-range model. There
is a kind of intelligence based on image models (human and animal) and one
based on symbolic models (human only).
9. To represent: there is a complex model, which is too big to be used as a
whole. Such a model can be associated to a simplified model, which on its turn
is associated only to a section of the main model. Such a model represents the
main model on the restricted domain. We should never forget that a
representation model is based on the main model, and the main model only is
fully associated to the external reality.
10. Emotion: this is a temporary state which occurs when a new external
reality appears, and no suitable short-range model is available. Emotion is
associated ONLY to a lack of a suitable SHORT-RANGE model. In such a situation
the PSM is activate. But the activated PSM does not consider this external
reality as a dangerous situation. Even so, it builds a suitable element. Such
an element is self-developing to understand the new external reality. The
emotion starts when PSM is activated, and disappears when a new suitable
short-range model is activated. Because emotion is associated with the
activation of PSM, in an emotional status, the conciousness disappears or is
at least attenuated.
The brain can predict the possiblity that an emotional status occurs.
Sometimes such status can be prevented by a suitable WBAM, built in advance.
That is, a ZM will build a WBAM based on the available information about a
future new external reality. ZM will activate that WBAM when the new external
reality occurs (see also the general theory).
We already emphasized that emotions are associated to the lack of a short-
range model, when a new external reality occurs. The word "angry" can be
associated with the lack of a long-range model associated with a full section
of the external reality (for instance when a person lives in an environment,
which he/she doesn't fit in). In such a situation, the PSM is activated as
well, but it has no solution. In fact, PSM can't build a long-range model. A
long-range model is difficult to build, because it starts from a general model
which is not directly associated to a specified external reality. The lack of
a suitable long-range model means that many short-range models can become
unstable, due to a lack of correlation between them. Such a person has a
feeling that there is a problem, but he/she cannot identify it. Such a person
is in an angry-status. About the same considerations can be associated to the
word "anxiety". Here we can see a class of problems associated to the fact
that the words in common life are not associated to the hardware and so, the
external definitions are not precise enough. As the language will evolve based
on internal definitions, the quality of the language will improve.
MDT is able to generate a definition, and then a word has to be associated to
that definition. Unfortunately, the words have already an external definition.
Thus, there are two possibilities: to invent a new word, or to use an already
existing word. In the latter situation, two definitions associated to the same
word could exist: an internal one generated by MDT, and an external one, as we
can find in dictionaries. My decision was to use as much as possible the
already existing words, with the risk to have two different definitions
associated to the same word. As MDT will be accepted, all the words associated
to functions of the brain will be associated only to their internal
definitions.
11: To be irritated, to be under stress
Such a phrase is used when there is a temporary situation of instability of
the structure of models. Such a status can affect the short-range models (to
be irritated) or the long-range models (to be under stress).
In the following, we will describe some situations when such a temporary
instability can occur.
11a. There is a normal model associated to the actual external reality. The
problem occurs when such external reality evolves in a cyclical way, for very
long time. In such a situation, the prediction of the evolution of the
external reality is identical with IR, forever.
If the external reality is a sound, and if the sound contains a sequence which
is repeated on and on, this uses a lot of energy of the brain for a nonsense
activity (due to the hardware design, it is impossible not to hear a sound).
Because the activation of other models becomes difficult, there will be an
instability of the structure of models, and so there is an irritation-status.
Examples: the use as weapon of the rattlesnake's rattle and of the "Chinese
drop"
It is important to observe two parameters: the length of the sequence and the
repetition interval. The musical piece called "Bolero" by Maurice Ravel
contains a sequence, which is long enough to produce no irritation. In fact,
every time when the sequence is repeated, there are other musical instruments.
In this way, this musical piece is not too close to the irritation limit. Even
so, at the end of the piece, the repeated sequence ends, producing an instant
relaxation.
Let's see this problem in the case of visual arts. Let's suppose a large white
surface. Such a surface can produce irritation, because in any point of this
surface, the IR is identical with the prediction. There is a natural tendency
to put some elements on that surface, to reduce the irritation. But, if the
details are randomly spread, the prediction will be different of the IR in
most of the points. This also can produce some irritation. The solution found
in about all cultural zones and times was to have some sequence made of
identical elements, but every element has to be complicated enough so that
sometimes the IR is identical with the prediction, and sometimes not. When
such a surface is explored, the brain seems to have a pleasure. The pleasure
can be defined as a situation when the prediction is close to IR, but about
never the same. This can be seen mainly on cultural products of ancient
cultures, but also nowadays.
We can see this also on the shape of the Christian cross: a Christian-Orthodox
cross has more detail than a Christian-Catholic cross because the Orthodox
religion is mostly oriented to image models while the Catholic religion is
more oriented to symbolic models.
The modern cultural zones are based mainly on symbolic models. There is a
reduced tendency to see all the details in a symbolic environment. Thus a
perfectly plane surface, without details, will produce no irritation. This is
so because, in a symbolic environment, the interaction based on image models
is not important anymore.
11b. The lack of stability of the structure of models could occur when the
external reality is unchanging for a very long time. Here, the prediction is
also identical with IR, but there is an additional technological feature,
which will be described below.
As we know from the main theory, any active model will predict in a continuous
automatic way the possible evolution of the external reality (this is a basic
hardware feature). Now, the problem is how often this prediction is made. My
supposition is that the speed of this activity is variable, and depends on the
speed of changing of the external reality. That is, when the external reality
is changing very fast, the new predictions are made also very often.
Now, if the external reality is not changing anymore, there could be a
problem: the model has to make a new prediction, but there is no reason to do
this. Such a situation can also produce a temporary perturbation of the
stability of the structure of models, i.e. irritation.
In such a situation, the brain could activate other ZMs, (e.g. ZMs which are
not connected to the unchanging external reality) up to the moment when there
will be a change in the main external reality. This activity could be a source
of mistakes or even accidents, as the local-ZM becomes, temporarily, one,
which is not connected to the main external reality. The accidents can occur,
for instance, when the external reality is changing and the suitable local-ZM
has not enough time to reinitialize.
Example: a driver is in a hurry and stops at a stoplight. The external reality
is not changing for a while and so there could be an irritation. Under stress
conditions, the driver could activate another model (associated or not to the
external reality) and so, he/she is not properly prepared for the moment when
the traffic light changes to green. Because this is an important source of
irritation, in some cities there is an additional display, which counts the
time for red or green status, and so the irritation is diminished.
Thus, time flows with a variable speed, depending on the speed of change of
the external reality (see ETA about "time").
11c. The word "irritation" is used also when an external factor interferes
with the activity of a main model. This external factor could also activate
the PSM. Such a situation can also affect the stability of the structure of
models and so, produce irritation.
As we know, faced with a new external reality (for instance a strong noise),
the brain will switch from the actual-ZM to another model, which understands
the new situation. When such external perturbation occurs on and on, the brain
is forced to switch the ZMs very often. Such activity can be affected by
mistakes, because switching from a model to another is a very complex
activity. When a model is deactivated, some information has to be stored to be
used when the model will be reactivated. Sometimes, the external reality can
change so much that the stored information becomes of no use. But the brain
does not know easily if the stored information is good or not at the new
activation. So, there could be mistakes, and the stability of the structure of
models can also be affected (irritation occurs).
Because the activation and deactivation of a symbolic model is much more
complicated than for an image model, the switching between a symbolic model
and an image model, or even worse, between two symbolic models, is very
dangerous (don't use the mobile phone when you drive, e.g.)
12. Love, to love
The main model of any brain (human or animal) is the Protection and Survival
Model (PSM). If something (a person, an animal, an object, an idea...) is
included by a person in his/her PSM (as a model, of course), the relation
between that "something" and that person is a love relation. That is, e.g. a
person A includes a person B (as model) in his/her PSM. The person A will
treat person B in the same way as he/she treats his/her legs, hands, eyes etc.
Here we use the convention that A indicates the person who is in love and B is
the person included in the PSM as a model.
The most important love-relation seems to be between a mother and her
children.
As we defined the term "love" the fact that A loves B is totally independent
on the fact that B loves A.
We already described love based on PSM. There is another type of love, which
is not based on PSM. Thus, the person A makes a structure of models which
contains B in about all of them. If B disappears, the models would become
obsolete, which produces a large instability of the structure. The problem
could be solved by another "B" or by a shielding model or by suicide.
Because love is based mainly on image models, about all of the written above
is true for animals too.
13. Happiness, to be happy
MDT considers that there are two basic modes of interaction of the brain with
the external reality: to generate the reality based on the external reality
and to modify the external reality.
Continuous happiness is associated to the status of the brain which builds
action models (ZAMs) based on ZMs-only. That is, to do and want only what is
possible (as ZMs predict). So any activation of a ZAM is a success (ZAM is
able to reach its aims). The happy persons have a big contribution to the
stability of the society, but small contribution to its advance.
We already defined the disharmonic person as the person who builds and
activates ZAMs without taking in account too much the predictions of the ZMs.
Usually such persons are unhappy, but sometimes they are able to reach their
aims and so, at least for a short time, they are in a status of high level
happiness.
14. Intuition
Based on MDT, intuition is associated to the capacity to obtain image
information in a symbolic frame.
That is, when we are in the frame of a symbolic model and there is a problem
without a solution, an image model can be activated automatically on its own
(as we already know). Such image model is able to make a prediction but there
is no proof or reason for it (because an image model generates image-truths!).
There is just a feeling that such information is true. The symbolic model can
use this information to solve its problems. In this case, we speak about
intuition.
The intuition is similar to the extra-sensorial perceptions: we gain some
information without any explanation about the source of it and there is no
proof to support it. The difference is that an illegal model generates the
extra-sensorial information, and a normal image model, which is activated in a
normal symbolic frame, generates the intuition.
Note: everything which is associated to the consciousness is generated by the
local-ZM. In the case of intuition, the ZM is a symbolic one. When an image
model generates information, it is just transmitted to a symbolic local-ZM.
Because the consciousness is generated by the local-ZM, that ZM is not able to
find the source of the information, and the proof for it because it was not
generated by the ZM or by any normal model.
15. Consciousness
The consciousness is associated to the facility of a brain to make and operate
a model, which contains the being itself as an element.
Two types of consciousness exist: image consciousness and symbolic
consciousness. The absolute majority of the population has only image
consciousness. Also, on animal level, at least the mammals have some level of
image consciousness.
Level-1 of consciousness: on this level, the being is able to predict the
evolution of the external reality, based also on its activity in that external
reality. This facility ensures the success of the defense or attack activities
in interaction with the external reality.
Level-1 consciousness is generated by short-range models.
Level-2 of consciousness: this level occurs only in a group (some packs of
mammals, any human group...). To be accepted by that group, any being must
assimilate and operate a long-range model associated to that group. Such
beings must communicate with one another to meet the above requirements. For
humans only, long-range models generate the rules, the laws, the methods and
the aims of the group.
Level-3 of conciousness: on this level, a human being is able to predict the
evolution of the group, based on a model which contains the group as an
element, while he is a member of that group. The appartenence to the group is
a basic condition here.
There are few persons, which are able to reach this level. The effort of the
brain to stay on level-3 is huge. The persons who are able to stay on level 3
are the elite of the group. There are few direct personal advantages from
being on level-3, but without an elite, the group is a low quality group.
The advance of a society is given by the power given to the actual elite. It
is important to note that there are some positions in a society, which must
belong to the elite. Many times such positions are occupied by level-2
persons. This happens usually in a low quality group or society.
ETA 5: NULL model
Let's consider that an M-model transmits no information (e.g. our eyes are
closed). A local-ZM takes the information from that M-model. Because the M-
model transmits no information, the ZM must receive no information. What is
really received is called NULL-model. For a normal brain, in the above
condition, the local-ZM must receive a completely dark surface. What is really
received is an indication about the overall status of the brain.
For instance, in the above conditions, we can receive a dark surface with some
randomly moving points. That is, the local-ZM detects a bright point in a
place, but at the second scan the point is not there anymore. This means that
there is a noise, but no important hardware problems. A stable image is
generated by a hardware problem of M or ZM models.
Application: In the first seconds after wake up, with closed eyes, look
towards a moderately bright surface. Usually, one should perceive a dark
surface full of grey points moving randomly. After a few seconds, the surface
becomes a uniform dark-grey one. This is a typical situation for a brain in a
normal status.
It is also possible, in the first moments, to see big bright points or shapes,
moving randomly. They evolve to dark and small grey points, and then to a
uniform grey surface. In such a situation, the brain is not in a good shape
(maybe the person did not sleep enough...)
Anyways, if the final status of the NULL model is a uniform grey surface, the
brain is OK.
This case has been illustrated for the eyes, but NULL models exist for all
senses.
ETA 6: Time
Excepting when specified otherwise, the subject is the same for human and
animal beings.
Based on MDT, time is not a parameter for the functions of the brain. This is
a basic deficiency.
But there is a problem: as the brain predicts on and on the evolution of the
external reality, how often is this activity done?
Of course, this problem is associated to the technological implementation of
every type of brain, so it is outside the field covered by MDT. Even so, based
on MDT, we can make some assumptions.
Because the brain is an optimized device as to its energy consumption, we
assume that the predictions about the evolution of the external reality are
done at a speed which depends on the changing speed of the external reality.
That is, the brain time flows with variable speed. This is also our feeling
based on our own experience. For instance, when we are involved in a complex
activity, time seems to flow too fast and when we have nothing to do, time
seems to flow very slowly.
This is a big design drawback. Without time, the long-range models could be
inefficient or unusable. So, the brain is forced to compensate, somehow, this
drawback.
One method is to use story-type models. They are not able to keep the control
of time, but they are able to record the order of occurence of some
information. Even so, this method is not very efficient. A story-type model
could fragment. Once it is fragmented, the correlation between the primary
information is lost.
Note: when a story-type model is fragmented, there is the tendency to
reconnect the fragments, based on logic. Many times this reconstruction is
wrong, but the impression could be good.
The fragmentation of the story-type models can be seen when a person describes
a complex situation. During this activity, one could change the order of some
facts.
Another method, used by the brain to keep track of time, is to use some
rhythm-models. Such models are specialized models, which try to guess when
something will happen, based on what has already happened before.
For instance, if the brain receives a sequence of two sounds, a rhythm model
tries to guess when a third sound will occur. The supposition is that such
models try to find an algorithm, which will generate the sequence. Such
algorithm must be changed on and on, in a fast dynamical way, to predict
better and better when the next sound will occur.
Such rhythm-models can be used, e.g. to recognize the speech or to understand
music.
The rhythm-models are not able either to solve the time problem, but they are
able to solve some time-related problems associated to fast changing external
reality in the field of sounds.
Let's analyze a bit this problem. First of all, the rhythm-models are very
well developed for human beings, and they are of very low quality for animals.
One assumption would be that, compared to animals, the human brain has a very
high capacity to make and operate image models, and, due to this, the rhythm-
models are so good.
But, there are some other facts: the European civilization invented the
polyphonic music (the most advanced music). But the European civilization is
developing based on symbolic models. It is fair to suppose that symbolic
models support the rhythm image-models.
We can take into account another idea as well: as MDT considers that the
capacity to make and operate symbolic models is generated by a specialized
hardware (thus it cannot be produced by a normal evolution process), it is
possible that the capacity to make and operate rhythm models was added in the
same way. This supposition is supported by the fact that, while some animals
are able to make and operate some image models above the level of human
beings, their capacity to make rhythm models is unusually low.
The problem of the origin of the rhythm models is left open for the moment.
Another method to compensate for the time keeping deficiency is to record some
pattern-models of the external reality. That is, to record some information
based on many M-type models, to build a pattern-model at a specific moment of
time, and to recognize the pattern later.
Such a pattern could be associated with the function of different organs of
the being, or with some other information from outside the being.
The time problem is a big one for the brain. The brain will use any external
reference to keep the time as the day/night cycle, the movement of the sun and
moon and for humans only, clocks.
ETA 7: Music
Music is a long-range image model, which exists only for human beings. As a
newborn baby grows, firstly, speech appears (a symbolic model) and only later,
the qualities associated to understanding music. As music understanding
capabilities appear after the brain aquires the ability to build and operate
symbolic models, it is reasonable to suppose that the symbolic models support
the development of music. This idea is supported also by the fact that
European music (the most advanced in the construction of symbolic models) is
superior compared to any other music from the point of view of its complexity
(polyphonic music was invented in Europe).
Given a sequence of a few sounds, the brain will try to predict the occurence
of the next sounds. Sometimes the prediction is correct sometimes not. If the
prediction is good too often, the impression is described in words like:
boring, monotonous or upsetting. When the prediction is not correct(there is a
large discrepancy between the prediction and IR), the sounds are uncorellated.
If we have an acceptable difference (the sounds are considered corellated
after modifying slightly the algorithm of generation of the sequence), then we
can associate this to music.
The corellation is associated with the capacity of generation of a sequence
based on an algorithm.
This automatic activity of continuous modifying the generation algorithm can
produce a positive state of mind, which can be called pleasure. This means
that the predictions are correct constantly, with high probability, and that
the ones, which are not correct, are accepted, after an acceptable change of
the algorithm. This activity is called currently music.
The corellation can be supported implicitly, as it happens in classical music
or can be supported explicitly (e. g. by rhythm of drums).
If we accept the hypothesis of the existence of a facility associated with
image models (a hardware facility) to build an algorithm of generation of
corellated information, then we could try to see if this facilty evolved in
time or not.
Thus, in spite of the fact that the capacity of the brain to operate with
image models diminishes relatively in time, the development of the capacity to
operate with symbolic models generated new abilities of operation with image
models. In consequence, music evolves based on two somewhat contrary
tendencies. The capacity to build and operate image models decreases due to
the increase of the capacity to operate symbolic model, and, on the other
hand, the symbolic models support the image models in the domain of music.
The symbolic models, which were developed especially in Europe, determined the
high level of complexity of the music. The European polyphonic music is one of
the results of the "marriage" between image and symbolic models in music.
Other civilisations, which did not have an extensive development based on
symbolic models, have created in milleniums of evolution only a simple music.
Let's see in the following some elements of the evolution of music in Europe.
The symbolic 'recipes' appeared in music composition in the time of J.S. Bach.
The maximum complexity of the music was attained during the times of W.A.
Mozart. In that period, the music had several simultaneous musical lines,
which, according to possibilities, were followed by those who were able to do
it. E.g. in the "Great Messa", KV 427 by Mozart, several musical planes exist,
which have to be followed simultaneously. Even nowadays, just the recording of
this work poses technical problems. This musical work is one of the peak
complexity constructions in music.
Approximately after year 1800, due to the increased capacity to operate with
symbolic models, the capacity to operate image models decreased. Music
continued to be polyphonic, but became simpler, with a single melodic line (L.
van Beethoven, contemporary with Mozart).
This simplified music was called romantic music, and was a form of
fundamentalism. The majority of the population lost their capacity to operate
very complex image models, and so, such a simplified music was generated.
This tendency continued with the increase of the limits of predictions
acceptability, due the increase of the capability of construction and
operation with symbolic models. E.g. the music composed by Igor Stravinsky.
When his music appeared, it was rejected due to surpassing the limits of
acceptability. But, in a short time, other musicians and people accepted his
music, as a consequence of the increase of the acceptability limits.
It is reminded that the increase of the acceptability limits is due to the
increase of the capacity to build generation algorithms. An assumption is that
these algorithms are supported by symbolic models.
Nowadays, music is so "advanced" that it contains just a rudimentary rhythm,
and an endless text (hip-hop or rap music e.g.).
The children of our times have a reduced capacity to understand music. Around
the year 1800, some 4 years old children were able to play the piano or
violin, or even to compose music. In our days, this is not met anymore. But,
some children are able to build and operate computer-based symbolic models.
As it is shown also, in some other parts of the book, there is a new form of
fundamentalism nowadays: the rejection of the symbolic models by a fraction of
the population. That is, some people return to harmony (there are many who
prefer Mozart e.g.). The present music is balancing between symbolic-type
music (hip-hop or rap e.g.) and harmonic music. This tendency will continue
for a long time, because it is hard to believe that music will disappear (the
brain is based on image models forever), but returning to the year 1800 type
harmony is not possible anymore.
Music is defined as a special story-type model associated with sounds. This
story-type model has elements generated by an algorithm generator.
The generating algorithm is able to build in a dynamically way the elements
which will be recorded by this special type story-type model. Based on the
algorithm, the model is able to predict the future sounds based on the sounds
already received.
Sometimes the algorithm generator is able to make a correct prediction of the
sound which comes (a hit), sometimes not (a miss). If the prediction fails,
then the generator will modify the algorithm and continue to predict what
follows. When the number of misses is low, this could produce pleasure to the
brain. When the number of misses is zero, there is no pleasure (e.g. a boring
music). When the number of hits is zero, there is no music (no correlation
between the sounds).
As this special story-type model is an image-model, its power is decreasing as
the brain is evolving to symbolic models. On the other hand, it seems that the
symbolic models support the algorithm generator. That is, there are two
tendencies that act in contrary directions. One tendency is to make a
simplified music, based mainly on symbolic models (texts) in the frame of a
rudimentary rhythm (e.g. drums), as hip-hop and rap music and on the other
hand, to make music based on complex algorithms (to enlarge the limits of
acceptability). The present music is evolving between these two large limits.
The main tendencies of the present music are:
- The evolution based on symbolic models. This tendency increases the limits
of acceptability of what are and what are not correlated sounds.
- The rejection of the symbolic models by a fraction of the population, i.e.
people want harmonic music.
- The return to harmony is possible only partially because many abilities
associated with the main story-type model are lost, due to the general
tendency of conceptualization of the image models. That is, the algorithm
generator is better and better, but it acts on recorded data, which are a
simplified copy of the external reality.
Let's see what is the situation with other arts. Almost all classical arts are
in decline. Painting and sculpture are based on pure image models. The general
tendency is to make concept models, and so people are not able anymore to
perceive fine details. This tendency is very easily seen in contemporary arts.
The tendency in visual arts is to make works based on symbolic models, and to
increase the complexity. Some arts as poetry, painting and sculpture are on
the way to disappearance as stand-alone arts. Theatre, because it is based on
symbolic models, is surviving, as it tries to keep the contact with the
tendencies of the society. Music is still in a good shape, as we already saw.
The main ascending art is cinematography.
ETA 8: Cinematography
Let's make a symbolic model to understand the subject as follows:
- The importance of the symbolic models (thinking e.g.) increases
- A big fraction of the population has difficulties to evolve based on
symbolic models (fundamentalism)
- Fundamentalism means to return to image models
- This return is possible only partially.
Because returning to image models affects an important fraction of the
population, why is it not seen in painting and sculpture? The explanation is
that the brain has lost a lot of its capacity to make and operate pure image
models. The brain returns to image models, but it stops at the level of
concept models.
Cinematography is one of the responses suitable to this situation. Thus, there
are cartoons, based on concept image models. They are strongly attached to
symbolic models. There are cartoons, in which symbolic models are more
important than the concept image models.
Today's successful movies are image models, which try to develop and extend
some of the incipient image models preexisting in the mind of the viewer.
We remind here that people have the tendency to expand their structure of
models outside their mind. When the models can't be expanded to the external
reality, there is the tendency to expand these models into a virtual reality.
This is speculated by cinematography, depending on the profile of image models
in different cultural zones.
From this point of view, movies can be very dangerous. They make these
developments based on what people would like to happen and on the other hand,
they favorize the fundamental tendencies of various social groups.
However, as they are attached to symbolic models, some movies are used to
develop symbolic models and fight fundamentalist tendencies and as such, have
a positive impact on society.
A huge danger associated to art movies is blocking the capacity of people to
think independently (tendency towards induced schizophrenia XS1B). Each script
is a long-range symbolic model; thus, the movie as a whole is logical. This
long-range symbolic model is translated or associated to a long-range image
model. If the translation is correct, the image model will be harmonic as
well. Thus, an art movie is a logical and harmonical long-range image model.
The fundamental problem is that it is not enough for a model to be logical and
harmonical in order for it to have a good connection with the external
reality.
There are movies that try to reconstruct an external reality that no longer
exists, an 'external reality' which will never exist, or anything else in
between these very broad limits. The only condition is that the model is
harmonic and logical. We cannot see the degree of connection with external
reality from within the model. This is where the danger originates.
Independent thinking will be blocked by the large quantity of information
structured harmonically and logically.
Many art films contribute largely to the aggravation of the level of induced
schizophrenia (XS1B). At the same time, there are many movies which contribute
to the construction of long-range models that stabilize society.
ETA 9: The fundamentalisms of the world we live in
The main fundamentalism is the return to image models, and thus, the refusal
of symbolic models. Symbolic models are based on extremely complex functions,
which are not easily maintained operational. For a 'regular' brain, the energy
consumption is higher for symbolic models than for image models. However,
there is a fraction of the population of developed countries working more
easily with symbolic models than with image models.
Example: There was a time in the evolution of the brain, when extremely
complex image models were built and translated to a symbolic form. It was the
time of the great novels (Balzac, Dostoievski etc.). Reading such works was a
sign of cultural superiority. These books are not read nowadays. The main
reason is the evolution towards symbolic models. The effort of the brain to
understand and integrate the use of remote controls, cellphones or text
editors is perfectly comparable as intellectual effort with the understanding
of the great works of universal literature.
There are too many who have difficulties to operate symbolic models. There is
a fraction of the population who refuses symbolic models; this fraction seems
to be increasing.
Example: Microprocessors (the central part of a computer) have been invented
in USA. At that time there was a tendency all over the world to produce or
reproduce such microprocessors. The first microprocessor was called 8080. It
was upgraded to 80286. These microprocessors were reproduced in Europe, former
USSR and Japan. 80386 followed, which was reproduced with great difficulties,
but starting with 80486 the tendency to reproduce such devices was extremely
low. Presently there are two families of microprocessors, both designed and
produced in USA. This is interpreted by MDT as a danger of a break between the
most advanced in the domain of symbolic models, and the slighly less advanced
ones (make your own comparison with the automobile industry). Even the
advanced cultural zones (Europe, Russia, Japan) make big efforts to keep the
contact with the most advanced (USA), but the danger of a break exists here as
well.
The fundamentalist reactions of the individuals, nations or even cultural
zones are a great danger for human civilisation. If the fraction of
fundamentalists will increase too much, then, at the limit, two things might
happen:
1. The world will fragment into nations/ cultural regions which can maintain
the rhythm of assimilation and development of symbolic models, and
nations/cultural regions which will return to image models (fundamentalist
reaction)
2. The same type of break will appear inside a nation/ cultural region.
The evolution shown at no.1, pushed to extreme, could generate terrorism, and
the one at 2 already generates 'escape' movements towards religions,
antiglobalisation, ecology etc.
ETA 10: Terrorism
The evolution of society leads, for some nations, to an incapacity of further
development based on symbolic models. These nations feel that the world is
going towards something they can't follow and understand. The solution for
them is to adhere to an invariant or universally accepted model, like a
religion or a nature/tradition conservation movement, to orient their
activity, and to offer them an easily understandable and attainable goal in
predictible time (fundamentalist reaction).
Some individuals, who have strong fundamentalist reactions, could try to
modify the society by direct action. A class of such reactions is terrorism.
The definition for terrorism considered here is: terrorism is an antisocial
phenomenon, which implies attacking some persons without an explicit reason.
It also means destruction of material goods without explicit reasons, when
these goods do not belong to a state.
If the persons attacked are the representatives of a government and the goods
attacked belong to the government, then we have acts of war. A state can
defend itself from acts of war, but in front of a terror attack, the
protection offered by the state is limited. The main reason is that the
government officials accept the limitation of their rights, and they accept a
certain discipline. These persons are well enough informed to understand that
they could be the targets of an attack. The same is valid fo defending the
goods belonging to a state.
Many terrorist movements have tried to commit war acts and not terror acts.
Thus, they try to obtain a legitimity as liberation movements, who fight for
liberty or independence against a state.
Example: ETA in Spain tries to attack only the representatives of the state or
local administration, and the goods belonging to them. It is difficult however
for ETA to comply with these rules, all of the time. IRA acts the same way,
trying to delimit itself from terrorism. Both movements make notable efforts
to be considered liberation movements at war with an opressive state, and not
terrorist movements.
Al Quaida tried at some time to attack only American military targets (thus
delimiting itself from terrorism), but the attack on WTC in New York is
clearly a terror act. The people killed were not representatives of the state,
the planes used were not military, and the buildings did not belong to the
state). However the attack on the Pentagon was not a terror act, but a war
act.
A practical aspect should be noted connected to the tendencies of terrorism:
who has vocation to build, has no 'vocation' for terrorism. To build planes,
buildings and so many other material goods supposes an immense effort on
scientific and technological levels, in labour organisation, on the social and
cultural level. Those who know how difficult these things are done, and how
many causes can block easily this process, will not have the tendency to
destroy material goods.
We change now the discussion and will refer to the individual terrorists
existing in any society. Serial killers exist, and others, who kill randomly
innocent people. By definition, they are also terrorists, even if they act
alone, without any connection to a group.
It is clear that a society can't protect itself against terrorism through
stricter laws. The tougher laws will determine the disappearance of exactly
those facilities, which permitted the progress of the society. Multiple levels
of security will produce the fragmentation of the society. Thus, due to the
reduction of the capability to communicate, the level of generalised
schizophrenia increases. This could lead to a disaster on long-term.
Not any person who refuses symbolic models will have terrorist tendencies.
There are adaptation forms to a world that evolves in another direction than
the one desired by some. In the attempt to find the individuals with
tendencies towards terrorism, one can consider a few aspects:
1. Children who have been normal at birth, but have been abused during
childhood, are on the highest level of risk. Individuals aggressed
explicitly or implicitly by the environment, can build illegal models,
which enter their PSM; the ones with difficulties of communication have the
tendency to build too short-range models for understanding the world they
live in (schizophrenia XS 1 and 2).
2. The stresses generating shielding models and illegal models can affect any
person, as society is very complex. For persons from 'imagistic' countries,
an important source of stress is the assimilation and operation of advanced
symbolic models. Forcing them to evolve from an image platform to high
level symbolic models can destabilize the structure of models. For the
'symbolic' countries, the same can happen on a more reduced scale.
3. The isolation or elimination from society of the individuals with clear
tendencies towards the destruction of the democratic system.
4. Relaxation in the protection of privacy. The so-called right to privacy
hides important sources of stress both for the people protected by this
right, and the ones around him/her. If everybody would accept the opening
of their privacy, the society as a whole would have less real problems.
The working principle of democracy should be somewhat modified, i.e. a
democratic system protects only those who respect democracy. Thus, the
individuals who fight against democracy should not be protected by the
democratic system.
Conclusion: The evolution of society is based on symbolic models. Those who
have not the capacity to follow this trend will 'run for shelter' into image
models. Slowly a break will occur between 'symbolic' and 'image' people. The
'image' people, who are not those who push the society forward, will see that,
from their point of view, society goes into a wrong direction. One of the
extreme answers to this situation is terrorism.
Warning: The individuals based on image models do not accept logical
argumentation, because logic is an exclusive characteristic of symbolic
models.
ETA 11: Problems of human brain evolution
This problem is already developed in the general theory. A few additions will
be given here. As we know from the general theory, we have an ability to build
and operate image models [I], and one to build and operate symbolic models
[S]. Generally speaking, [I] increased up to about the year 1800. [S] had a
first increase with the spoken language. It increased further with the
emergence of the written language. An important step was the development of
geometry as a symbolic model by Euclid, about 2300 years ago. Then [S] stayed
unchanged about up to the year 1666, when Newton's Mechanics marked the
evolution of the brain, as the second important fundamental symbolic model
appeared. From that moment, [S] started an accelerated increase which
continues.
In spite of the fact that [I] decreased in percentage compared to [S], in an
absolute mode, it continued to increase due to the support of [S].
Unfortunately, this evolution, which is true e.g. for Europe, is not true for
some other cultural regions. Some nations refuse basically symbolic models,
but are forced to use them.
There is a risk of splitting the world, due to the more and more reduced
capacity of communication between the two parts of it. The same situation may
happen inside one country with groups of people.
The two parts are not symmetrical. The ones based on [S] are the vectors of
progress and power, in any sense. The others are unable to maintain a rhythm
of evolution, but are, however, helped by the [S] nations, for stability
reasons, and due to the lack of other solutions. The [I] nations accept this
help, especially for practical reasons and opportunism. On long range, this
problem has no solution within the frame of the generally accepted democratic
system.
Within the [S] countries, a structure exists as well. Thus, some persons have
a higher [S] than others.
In general, the [I]-type people in a structure of [S]-type detain the power.
The time when the [S] people would have control is not within view. ([S]-type
people are called technocrats).
Due to the large dispersion between [I] and [S] levels, there is no hope at
the moment that a unique symbolic model will ever exist to describe correctly
the whole social structure. As a consequence, the technocrats (the [S] people
in an [S] type society) are n
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