Neurocomputing may be studied by purely mathematical methods. We can take 2D (or 3D) image as a main data unit, take associative instead of linear memory, and design a completely different computational model. The Von Neumann processor retrieves data from memory by the address of a memory cell. Associative memory uses keys instead. Also, a single neural net usually keeps multiple images which are superimposed in distributed storage. There are 2 types of such memory: autoassociative and heteroassociative. In the first case, the goal is just to memorize many images, then to recall one of them using some hints. In the second – associations between images of different types are remembered. This may be used to implement stimulus – reaction or event – handler pairs.

Two types of continuous computation are visible right away. In the second case, the system is placed into real-world conditions where external events come permanently so some reactions will be generated permanently too. In the first, we can use an image retrieved from autoassociative memory as a key for the next operation. This implements "free thinking" or "flight of ideas".

The main approach to creativity remains ancient trials-and-errors method. For computers, more orderly variants such as full scan of possible solutions are used. In any case, the processor should prompt some actions, then assess their results. That's exactly what the limbic system does. Looks like the amygdala is a block of system-level memory similar to the basal ganglia. Only they keep elementary programs for sensorimotor coordination while the amygdala keeps genetically predetermined states of the brain itself such as fear or aggression. Human emotions correspond to processor instructions of computers, only the brain doesn't use the Von Neumann architecture. It uses a finite-state machine which has elementary states rather than actions. This approach may be very powerful. It is well known that the brain parts tend to have connections according to the principle of all-to-all. Not all of them are used at once. Instead, only a fraction is employed when necessary. This means that you can dynamically create different working machines for different circumstances.

On the other hand, the hippocampus has all the necessary means to assess the results. It receives input from major sensory channels and can generate sharp pulses of activation at the output. Again, this works differently. When you write a control program, you would create a variable to measure the assessment. Say, in the range [-1,1]. The program will input data, process it, set that variable, then use it for decision making. Looks like the brain has not such a separate variable. Instead, associative memory immediately links an input situation to the appropriate emotional reaction such as attraction or aversion. That's why negative emotions are harmful. You get tensed and if this tension has no exit, you must contain it. That leads to double tension and quick tiredness.

This scheme is compiled from the most reliably described links between various brain regions. How to understand its operation? The main problem here is multiple feedbacks. The common method in such cases is to break the loop. Then, operation of the open circuit will become obvious. So we need to remove some links from this scheme, but which specifically? The red nucleus is a clearly supplementary structure because the motor cortex already has direct output to motoneurons. So we will throw it out together with the cerebellum. Functions of the latter are well established. It provides muscular coordination and fine-tuning. If it is damaged, patients still cam move, but their movements become more primitive, rough, and non-coordinated. The cerebellum is a typical "improvement".

Fig. 8.

This picture still may be further simplified.

Fig. 9.

The upper link on the picture is a well known reflex. The link through the basal ganglia is a bit more complicated. It combines the previous principle of stimulus-reaction with sensorimotor coordination. The last detail comes from the fact that muscular actions change the environment and these changes will be perceived by external sensors.

Fig. 10.

This device is not so weird as it may seem at the first glance. For illustration, let's demonstrate how to implement common linear programming here. Suppose you have some algorithm, that is a definite sequence of actions. Just associate each one with the corresponding number in the sequence and remember these associations. By the way, memorizing may be performed in any order. Next, you will need a small system program. Namely, you should have a sensory image which keeps the number of the current operation. That is you emulate the register of a common processor. Increment it after each action. Now use this image as a key for sensorimotor associations and you will be able to run common programs on this computer.

Like a personal computer, the human brain also has memory and a processor, although they operate and interact quite differently. Neurocomputing does not use linear memory containing bytes or machine words which may be accessed one by one. Instead, it relies upon associative memory that keeps bytes in synapses, but they can't be immediately read out. Humans use a different principle. Memory bytes form a distributed hologram which is only an instrument to retrieve data. The output comes in the form of an image encoded by a current spike rate distributed over some neural net. Again, in contrast to a computer, each neuron outputs not binary data of 1 or 0, but a real value in some range, say [0, 1]. This principle is used both in memory and a processor; they are different only by the architecture. Human memory is located in the neocortex which is a large 2D structure packed into the skull. It has 6 layers of neurons of different types which are basically the same throughout the whole of its area, but this area is genetically partitioned according to the functional principle. The frontal half of the neocortex works mainly for output, the rear – for input. Many different cortical fields are interconnected by direct axonal projections. This system alone already can work like computer software. When some portion of data comes to a sensory input, this is 1:1 as an event in a computer. This event produces activation which spreads to a different field, undergoes various processing, and finally may generate a muscular action. The problem is that this flow is not synchronized, no single clock generator. Also, brain connections tend to be organized by the principle of all-to-all or one-to-many. The uncontrollable spread of activity will lead to informational overflow. Obviously, for a given event, only a fraction of all fields and their links should be used. All the rest need to be inactivated. This is the main function of the brain processor – the limbic system.

In a computer, the processor has a definite set of instructions and handles data loaded from memory. In the brain, data are processed immediately in memory. The processor only starts and stops this process. Nevertheless, it has some instruction set too. The limbic system generates emotions. Motions are activation of muscles, emotions – similar activation of internal brain structures. Like the neocortex, parts of the limbic system also keep various images, but these images encode patterns of activity for other parts of the brain. Some of them need to be boosted, others – suppressed. Such emotional patterns may be learned, but also may be inborn basic distributions of strong reactions.

Another important function of the limbic system is related to operative memory. Associative memory does not keep the image itself – only the ability to evoke it. Nevertheless, neural nets can retain images too. For this purpose, they build a sort of a trigger system using positive biofeedback. In this case, the output of some internal block is supplied to its input starting recirculation in the closed loop. As soon as some pattern gets into this system, it becomes locked and can exist for a prolonged time even if the source was turned off. The limbic system was initially called the Papez circuit. It and the adjacent basal ganglia have many such loops which may be employed in various cases. Usually, some cortical field sends output to the limbic system and also receives input from it. Obviously, when some image is reverberating through the limbic structures, they can control it. That's how this system manages operative memory.

A well known function of emotions is assessment. In fact, most of them are broadly divided into 2 categories – positive and negative. The strength of emotion provides a value for this sign. Suppose you need to write a program for monitoring of some object. How would you do that? Probably you will define an appropriate variable, write the evaluation there, and use it for decision making when necessary. Seemingly the limbic system operates differently. The assessment is not kept separately but appears immediately at the output as the aforementioned control signal. That is, if the results of some actions are negative, the aversive emotion will immediately suppress that activity.

2 key blocks of the limbic system are the amygdala and the hippocampus. They are very different and seemingly complement each other. The amygdala is a typical subcortical structure. It is linked to generation of very basic states of the organism as a whole – such as fear and aggression. The hippocampus is the archicortex. This is a small piece of cortical matter which emerged early in evolution and has just 3 layers. Thus it should perform some important functions. An interesting theory of the hippocampus is as follows. What you usually see in illustrations (CA1, CA3, etc.) is a cross-section. The hippocampus as a whole is a tube or more precisely – a long cone in correspondence to its name Cornu Ammonis. Functionally, the hippocampus generates a 1D image that is a vector. The index of this vector goes along the tube while its cross-section provides a pathway for data rotation. Input comes from the entorhinal cortex, output returns back to it. That is, the entorhinal cortex may be a memory buffer which can receive an image from a wide variety of cortical regions, then keep it for temporary dynamical storage via reverberation through the hippocampus. Thus, the hippocampus may work as famous operative memory. Note that it can't store data because it is 1D, while cortical images are usually 2D. Only plays some important role in this storage. In addition to that loop, another major output of the hippocampus goes via the fornix to several small (0D that is scalar) areas of the brain. Through the mammillary bodies, the hippocampus can control the thalamus. It also sends output to the septum (a pleasure zone). There are several such spots in the brain (the substantia nigra, ventral tegmental area). They use the neuromediator dopamine which can control formation of long-term memory.

At last, need to discuss the relation of the brain processor to such important psychological concepts as motivation and consciousness. For humans, motivation is more than just a Start button which sets the goal and launches processing. Human problem solving reduces the main task to subtasks. Accordingly, motivational structures will be activated in the process again and again. There are 2 different types of human motivation – biological needs and goals of behavior. They are generated in the hypothalamus and the prefrontal cortex respectively. The former is a standard part of the limbic system, while some authors include the prefrontal cortex too. In any case, it is linked to the limbic structures.

As to consciousness, this term may be used in different meanings. The most primitive is just the state of awakeness as opposed to sleeping. Accordingly, in the latter case, activational structures of the brain simply switch off perception and data input stops. In a more subtle meaning, consciousness is the ability of the brain to watch itself. This is usually linked to the TPO (Temporal-Parietal-Occipital) zone of the neocortex – an area where 3 main sensory analyzers come together and create a synthetical image of reality. The associative cortex is interlinked with the entorhinal cortex thus receiving information from other parts of the brain and we can look not only at the external world but also at our own internal activity.

Fig. 12.

This is a processor of the brain aka the limbic system. Emotions serve as processor instructions for an associative computer. How does it work? Let's formulate the answer in advance.

The amygdala and hippocampus complement each other. The first generates various states of the brain that are appropriate for a particular situation. The second outputs sharp bursts of activation to trigger these states, switch, or end them.

Theory of automatic regulation helps to decode this overcomplicated pile. According to this approach, the whole of the brain's computer is a supplement to the hypothalamus which in turn is the highest control center for internal organs. The first simplification is to remove the arrow from the amygdala to the hypothalamus. The link in this direction ensures that emotions produce reactions in the body so it is already beyond the psyche. Instead, the reverse link is a key because it conducts activated biological needs and launches generation of appropriate emotions.

Fig. 13.

All in all, the brain processor has 2 major functions: managing dynamic operative memory and suppressing unnecessary associations. The second function works as follows. When some event comes to sensory inputs, it is evaluated by the limbic system. If it is important – passed further, otherwise blocked. For the valuable events, the limbic system (amygdala) determines blocks of associative memory which should be used for processing. Others are inhibited. That is, for each event the amygdala outputs a pattern of active cortical regions. The principle of dynamic memory via recirculation may be used to store sensory images and these emotional patterns too. In this case, the loop is linked within limbic structures.

Both processes (selection of events and selection of associations) are modulated by the input from the hypothalamus and the prefrontal cortex, that is by primary needs and current goals.

Fig. 14. The functional scheme of the brain processor. Blue links represent static signals which provide information about context. They also may be quasistatic. That is, may change gradually so that at any moment some definite state is processed. Red – distinct pulses known in programming as events. Reciprocal connections at both sides of the entorhinal cortex represent dynamic (operative, working) memory. By this means, an image may be retained even when the initial sensory input disappears. Motivation comes to the amygdala from 2 sources – the hypothalamus and the output half of the neocortex.