The Brain, A Decoded Enigma Part 12

The consciousness is a.s.sociated 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 a.s.similate and operate a long-range model a.s.sociated 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 ill.u.s.trated 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 a.s.sociated 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 a.s.sumptions.

Because the brain is an optimized device as to its energy consumption, we a.s.sume 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 a.s.sociated to fast changing external reality in the field of sounds.

Let's a.n.a.lyze 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 a.s.sumption 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 a.s.sociated 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 a.s.sociated 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 a.s.sociate this to music.

The corellation is a.s.sociated 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 cla.s.sical music or can be supported explicitly (e. g. by rhythm of drums).

If we accept the hypothesis of the existence of a facility a.s.sociated 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 surpa.s.sing 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.