Игорь Волков – Hardware and software of the brain (страница 12)

Let's look what happens when we read a text sentence by sentence. First of all, the content may be subdivided into semantically different pieces. These categories are also semantical elements, but they belong to higher levels of the hierarchy. The exact composition may be different for different genres, but the principle is the same everywhere. I will consider various scientific textbooks as the most meaningful literature. For other genres, you may try and produce a similar listing yourself. Only keep in mind that some books are not intended to be meaningful at all. The author may stimulate filters of your mind which have the task not to let things in. The only goal is your entertainment.

The most often categories of content are: definitions of new concepts, presentation of facts such as a value of some world constant, composition of a complicated object (anatomy), listing of events in some process (history), making a statement (theorem), formulating rules which link events (if – then), etc. All these semantical elements contained in some pieces of text are intended for retention in your long-term memory. The procedure is like installing a program or database on the hard drive of a computer. Albeit adding information into the knowledge base is more complicated. At least, it should be checked for consistency. The new data should not contradict what already exists. What to do if such contradiction does emerge? You may either reject the new portion, or update your previous knowledge.

The most interesting case is when acquisition of new knowledge happens as a side effect. For example, 'Yesterday, he met his friend Nick who lives in the nearby town.' Accepting this sentence, the program should make a current record about the meeting plus make a new entry. It will create the new object named Nick and add the property that Nick is 'his' friend.

This example also demonstrates another function. The pronoun 'he' is a placeholder. It stands for some man. An understanding program should replace it with the corresponding name. This approach shows that the resulting semantical representation will be even larger than the initial text while intuitive assessment is opposite. What's the matter?

First of all, we retain only the upper levels of the semantical pyramid. This is obvious if you compare an abstract with the full text of some article. The summary tells you only what to expect there. For details, browse the article itself. Next, the text itself also contains supplementary pieces which are not intended for retention. For example, a theorem may be a valuable instrument for everyday use while its proof is needed only if you want to check whether it is correct. The amount of such content sharply increases if you recall that most of our knowledge is probabilistic. An important fact may be short but doubtful. Accordingly, it will be accompanied by lengthy commentaries with the only function – convincing the reader to accept that fact. Further, an important piece of knowledge is an instrument and the text may contain hints on when and how to use it better. These passages create a sort of index in your mind. They link the instrument with the situation where it may be helpful.

Modern languages allow very complicated constructs. One compound sentence may contain several subordinate clauses and occupy the whole paragraph. Looks like, our mind dissects them into the simplest forms of the nucleus language. It creates separate representation for encountered objects and processes (actions), replaces placeholders (variables) and lengthy references with concrete names. Also, it links these objects and actions into a semantical network using relations. This job is comparable with what is performed by a compiler when it processes the text of a computer program.

Consciousness

This is a long-lasting area of research attracting specialists from philosophy, theology, psychology, neuroscience. In recent decades computer scientists joined. When it comes to reproduce human ability in a machine, Artificial Intelligence is usually recalled. Machine Consciousness is yet another key feature.

Definition

In [1] it is perfectly demonstrated that prolonged debates leave major questions unresolved. This includes definitions of the main concepts. The situation is very characteristic for any science on initial stages of development. People like to introduce some term, even put it into practice, then discuss what it means. How is it possible? Computer programming strictly prohibits such practices. First define a variable, assign some value, only then you can use it. Fuzzy logic employed by neurocomputing in live humans is different. The initial definitions, even the move to recognize this concept is sub-conscious. Neural processes which underpin it are image-based, nonverbal. Accordingly, the first cases of usage may be highly erroneous, but with practice quality gradually improves. Discussion helps to verbalize the matters and exchange ideas.

The state of the art is that on one hand neuroscience accumulated a vast corpus of data about the structure and functions of the nervous system. On the other, various methods of data processing offer ready solutions. The computational approach to consciousness is based on the statement that the brain is a live automatic control system. Such devices are perfectly explored mathematically and this science guarantees a complete representation. All the possible solutions are known. We need only to choose which one is implemented in our own head. Optimal definitions may be formulated taking into account previous attempts and keeping in mind future use.

Different people use this term in a different sense. In the most general case, it is just all the higher nervous functions. A more narrow meaning is that consciousness is just upper levels of the perception hierarchy related to abstract thinking and understanding. Where to draw the lower boundary – decide yourself. One solution – just above the secondary sensory fields. Consciousness begins where sensory modality ends up.

The most narrow definition comes from neurocomputing.

Consciousness is self-control.

The basic principle of life is regulation or stabilization, self-support. The brain maintains the internal environment of the body and generates behavior. Only neurons are live as well. The brain must also maintain its integrity. It monitors own operation and corrects it when necessary. That's consciousness.

Macro regulator

Homeostasis is a founding principle of living nature. It is implemented by different means such as biochemistry. The nervous system adds to this toolbox. A classical regulator is described by a standard scheme.

Fig. 16. The standard regulator.

A sensor reads current values of the regulated parameter. The comparator outputs its difference from the normal value. Then, this difference produces a regulatory reaction. A similar scheme may be implemented for the whole organism, only instead of scalar values, sets of parameters arranged in 1D vectors or 2D matrices (images) are used. For example, you may maintain order in your living room or in the kitchen.

In this case, you will have an image of the norm, knowledge as the image of current reality, emotion produced by comparator, and some motor image of the regulatory output. This principle may be especially efficiently implemented in hardware using 2D neural nets.

The macro regulator is especially efficient to implement elements of consciousness on the hardware level. Brain operation is sophisticated. It is difficult to represent this by a single scalar parameter, even by a set of them, that is by a vector. The matrix representation is much more suitable.

Principles of neuroprogramming

Ivan Pavlov spent 20 years searching for physiological foundations of psychology and could not discover anything substantially different from reflex. Neural processes on higher levels of the hierarchy are different only by the fact that both the stimulus and reaction remain inside the skull. A reflex is replaced by an association between images. Programmatically, an association is a rule so we have a powerful rule-based machine. A part of what we know as software is implemented materially by hardware. White matter of the brain represents links between various cortical fields and subcortical nuclei. Each such link can store many rules and these pairs operate simultaneously in parallel processing. This provides sufficient foundation for sophisticated software. An internal knowledge base is a picture of the world used by this software.

Reason

Newborn humans are rather helpless. Most of our abilities were learned, that is programmed. Like in computers, human software is a complicated hierarchy: low-level routines, system programs, and high-level applications such as professional skills. Reason is associated with the second group. Obviously, it may vary among individuals and cultures, but there is something in common. Let's consider how to implement the reasonable execution of algorithmic applications. Another example of system software is a program for automatic problem solving. You may also add what you prefer.