Criteria for the Synchronization between Neural Networks used in Diagnostics of Functional States of Athletes Bodies


Tatyana Vladimirovna Popova*, Koryukalov Yury Igorevich and Kourova Olga Germanovna

Background: It was the goal of this research to identify individual parameters of criteria for synchronization processes that occurred in various functional body states in athletes who played acyclic sports requiring strong capability for mobilizing body resource.

Materials and methods: 15 athletes have been examined, using Electroencephalography (EEG); 17 subjects of the same age, who practice psychophysical self-regulation relaxation and 19 controls.

Results: Regular synchronization periods have been found on EEG in all the subjects in more than 50% of the deflections, with a synchronization pattern similar to that of a neural network visually detectible. The synchronization periodicity ranged between 5 and 70 sec, varied between subjects belonging to specific groups and depended on their state (functional test results). The Athlete Group had the highest periodicity, while the Control Group had the lowest one. It is worth noting that accelerated synchronization was detected as subject were doing cognitive test (mental subtraction), with numbers of deflections involved being increased. Alpha-wave generalization that periodically occurred in the wake of a synchronization pattern at the same frequency was observed in all of the subjects when both open-eye and closed-eye EEGs were being recorded. The said generalization was most commonly found in the athletes: synchronization being predominant in the fronto-centro-temporal deflections; the shortest generalization pattern period, prolonged alpha-wave generalization after a pattern, both of the brain hemispheres being equally involved, etc. We have been first to demonstrate that most of the criteria found in the relaxation groups are parametrically similar to those found in the athletes.

Conclusion: We recommend using our research findings for functional diagnostics and performance prognostication in, e.g., sports. E.g., better resource mobilization found in the Athlete Group by EEG came hand in hand with improved performance in various activities.


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