S. K. Lisitsyn

       Up to recently data on the biopotentials of the brain have been utilized weakly in psychophysical research.  To a considerable degree this is explained by the difficulty of exposing on an electroencephelogram (EEG) the functional statistical and semantic regularities;  by the absence of information on the role of EEG-signals in the work of the brain; by inadequate knowledge of the nature of EEG-waves.

       It is possible to isolate the purely informational side of the question and to consider that EEG-signals will carry definite and varied information from one section of the brain to another according to the principle "to all! to all!".  The advantage of such a hypothetical circuit of information is the reliability of the connection under conditions of the absence of many relays over cellular paths, but the difficulties appear in the coding and decoding of independent signals on a number of channels.

       The statistical structure of EEG-signals has been traced by us during research on the time parameters of an EEG of a man normally and at rest on a modernized analyzer of the type AI-100-1 [1].  In this work it has been shown that clipped EEG-signals in their statistical structure are sharply distinguished from all known random processes and are in all probability a complex information function. The density of distribution of the amplitude of a nonclipped EEG is