Relationships between the entropies of EEG, HRV, immunocytogram and leukocytogram

Abstract

Background. In mathematics the entropy is a measure of uncertainty of a random function; in the theory of information entropy is a measure of uncertainty in a situation, any experience (test) that can have different consequences. The entropy is also a measure of disorder, the degree of chaos present in the system. CE Shannon linked the mathematical dependence of the concept of information and entropy, which characterizes the degree of ordering of the system. This estimate of the amount of information coincides with the estimation of the quantitative measure of elimination of uncertainty of entropy, the degree of organization of the system. It is well known about functional interactions between central and autonomic nervous and immune systems. In the context of this concept, we have prioritized research on the interconnections between the entropies of these systems. Material and methods. In basal conditions in 37 men and 14 women with chronic pyelonephritis and cholecystitis in remission as well as without clinical diagnose but with dysfunction of neuro-endocrine-immune complex and metabolism, we recorded twice, before and after balneotherapy at the spa Truskavets’, EEG (“NeuroCom Standard”) and HRV (“Cardiolab+VSR”). In blood we determined relative content of components (RCC) of Immunocytogram (ICG) (T helper, T cytolytic, B and NK lymphocytes) and Leukocytogram (LCG) (Eosinophils, Stub and Segmentonucleary Neutrophils, Lymphocytes and Monocytes). Than we calculated for each locus of EEG and HRV as well as for ICG and LCG the Entropy (h) of normalized spectral power density (SPD) or RCC using Shannon’s formula: Results. There was a complete absence of correlation between hHRV and hLCG (r=-0,03) as well as hICG (r=-0,03), whereas the relationship between hLCG and hICG is significant (r=-0,40; p<0,001). Accepting the entropy of EEG HRV as a factor, using the correlation analysis with step-by-step exclusion, we obtain the equations for dependent variables. Canonical correlation between hHRV&EEG, on the one hand, and hLCG&Immunity, on the other hand, is strong: R=0,814; R2=0,663; χ2(240)=296; p=0,008. Conclusion. The enropy of HRV and EEG significantly correlate with the entropy and parameters of immunity, which testifies to their modulating regulatory effects.