Hardware and software of the brain. Igor Vladimirovitz Volkov
by the pulse activity averaged over a group of adjacent cells (called a cluster) and a certain period of time. The typical number of elements in such clusters is of the order of 1000. As to time parameters, the duration of one spike is approximately 1 millisecond so the firing rate of 1 neuron can't be more than 1 kilohertz. Multiplying it by the number of elements in the cluster, we get 1 megahertz, but keep in mind that the reaction time still can't be less than 1 millisecond because spikes are not rectangular.
At this time you might realize the shocking truth: our brain is so different from our computers that it is an analog (more exactly digital-analog) device at all. Meanwhile there is something that unites them. It is very symbolical that computer programs and musical records may be stored on the same type of media such as optical disks.
Anatomically, the brain consists of several parts which may be clearly distinguished and reproduce themselves in all humans. Their cell structure is different from the adjacent regions or they simply are visible from the surface. The inner space may be of two types – gray and white matter. The former is composed of cell bodies, the latter – of nerve fibers. Different parts of the brain are heavily interconnected. This supports the hypothesis that regions which look different are functionally different as well. All in all, anatomy distinguishes some couple of dozen different parts, but how to arrange them into a functionally meaningful construct?
Basic principles of a live neurocomputer are different from the Von Neumann architecture. Computer operative memory changes data by an instruction (the differential principle) and keeps data while power is on. Regeneration is a separate unconditional process. In live neural net, dynamic memory is a pattern of neural activity which should be explicitly supported by the system of nonspecific activation or by reverberation. In the second case, circulation of activity is also controlled by the nonspecific system. That is, in a computer, instructions are quick and their results remain forever. In a live neurocomputer actions are lengthy and continue while the activation signal remains. Retaining results also requires continuing activation.
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.
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