Е.А. Umryukhin - Corresponding Member оf RAS, Dr.Sc. (Biol.), Ph.D. (Eng.), Р.K. Anokhin\'s Institute of Normal Physiology, Moscow, Russia. Е-mail: eaumin@mail.ru

In accordance with the principles of the P.K. Anokhin theory of functional systems we proposed a computer model of the brain, composed of the similar hierarchically connected units, built according to the functional system architectonic [1, 2]. This model differs from similar ones [3, 4], in particular, by the completion of its logical structure, breadth of simulated events and represented operational mechanisms [5]. Based on this model, we carried out an analysis of the electrical activity of the brain in the subjects challenged by certain tasks with specified parameters, characterizing the systemic aspects of a mental activity. Subjects were asked to remember and reproduce on the screen the sequence of the seven signals in the form of circles with a di-ameter of 1 cm, which was shown twice. Then subjects had to predict the place of next signal occurrence on the screen. The ul-timate objective of subjects was to achieve maximum accuracy in predicting the place of the next signal occurrence. As a result of the assignment we calculated the number of exact predictions, the number of errors, the total length of the path of the cursor, the total test time, the average time of place prediction of occurrence of the next signal. Statistical analysis was performed using the multivariate analysis of variance (MANOVA), Mann-Whitney criteria by the Statistica 6.0 software. The highest variation coefficient was found for decision-making time, so we divided subjects into the Group 1 with a short (25 people) and Group 2 with a long (17 people) duration of the decision making. Analysis revealed a negative correlation of the decision making time in the quest and the values of the spectral power of delta, theta and alpha EEG rhythms. Individuals with a short decision-making time have had significantly higher power of delta rhythm of EEG in right (p = 0,033) and left (p = 0,007) occipital, right (p = 0,043) and left (p = 0,029) parietal, left center (p = 0.030) areas of the cortex. At the same time in these subjects there was a higher power of theta rhythm in right (p = 0,015) and left (p = 0,032) central and right frontal (p = 0,023) and temporal (p = 0,008) cortical areas. In subjects of both groups during memorizing a reduction of alpha rhythm and beta-1 power was found in all areas of the cortex. In group 2 subjects performing the task theta rhythm power did not change and was significantly (p <0,05) lower than in Group 1 subjects in all cortical areas except the left temporal lobe. Thus the greatest differences between the test groups were observed in the power of theta rhythm in right center (p = 0,0007), frontal (p = 0,0005) and temporal (p = 0,0018) cortical areas. During playback, the power of the alpha rhythm remained below background levels (p < 0,03), being not different from the values observed during memorizing. Thus, individuals with a short decision-making time were characterized by higher theta rhythm power in right temporal region during memorization, as well as increased power of theta rhythm in the frontal cortex when reproducing the signals sequence. The results indicate that both the high activity of the right temporal and frontal cortical areas may account for the rapid decision making for implementation of specific motor programs. The work was supported financially by RFH in grants № 15-03-00519а «Post-non-classic paradigm of artificial in-tellect».

 

1. Sudakov K.V. Informacionnyjj fenomen zhiznedejatelnosti. M. 1999. 379 s.
2. Umrjukhin E.A. Model sistemnojj organizacii raboty mozga cheloveka. Saarbrücken: LAP LAMBERT Academic Publishing (Germany), 2014. 52 s.
3. Ivanickijj A.M. Fiziologija mozga o proiskhozhdenii subektivnogo mira cheloveka // ZHurnal vysshejj nervnojj dejatelnosti. 1999. T. 49. Vyp. 5. S. 707-713.
4. Clegg B.A., DiGirolamo G.J., Keele S.W. Sequence learning // Trends in cognitive sciences. 1998. V. 2. №. 8. P. 275-281.
5. Milner A.D. Streams and consciousness: visual awareness and the brain // Trends in cognitive sciences. 1998. V. 2. № 1. R. 25-30.