title: [Principles of signal coding by the discharge pattern of neural networks].
abstract: Neuronal populations are shown to form rings of stochastic dependence for optimal coding of information. Such a population can only exist in strictly defined stochastic states determined by the number of the stochastic dependence rings. A system consisting of a certain number of neurons, was shown to be able to code and transfer a number of messages equal to square of the number of stochastic states permitted for the given system. The number of messages differing from each other either by the number of characters or their order in the word, would be equal to the number of permitted stochastic states, whereas the number of messages containing the same number of characters in the word would be equal to the difference between the number of permitted stochastic states and the number of neurons in the system. The alphabet consists of two letters: "U" - determination of the stochastic dependence ring; "R" - disruption of this ring and punctuation marks - there are neither determination nor disruption of the stochastic dependence rings.
mesh_terms: D001921:Brain / Q000166:cytology*; D006801:Humans; D007257:Information Theory; D007395:Interneurons / Q000502:physiology*; D008433:Mathematics; D008959:Models, Neurological; D009434:Neural Pathways / Q000502:physiology; D013269:Stochastic Processes; D009435:Synaptic Transmission
vernacular_title: Printsipy kodirovaniia signala risunkom razriada sovokupnosti neĭronov.