Chapter 1

Chapter 13,908 wordsPublic domain

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 [email protected]

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.