Chapter 7

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.