ENTROPY OF BEHAVIORAL REACTIONS AND FUNCTIONAL ORGANIZATION OF THE CENTRAL NERVOUS SYSTEM

Abstract

Introduction. Sensorimotor reactions to repeated stimuli are not independent; reaction time possesses an internal structure formed under the influence of attention, neurodynamic stability, and cognitive load. Therefore, time series can be viewed as dynamic systems where healthy physiological systems demonstrate "organized complexity". A decrease in complexity—moving toward excessive regularity or excessive chaos–is seen as a sign of reduced functional adaptability. In light of the theory of dissipative structures, entropy can be considered an indicator of the dynamic balance between stability and the adaptive restructuring of functional systems.
The purpose of the study was to investigate the possibility of using entropy analysis of simple sensorimotor reaction time to study the functional state of the central nervous system
Methods. The study was conducted at Bohdan Khmelnytsky National University of Cherkasy with 80 participants aged 17 to 75. Simple visual-motor reaction time was determined using the Makarenko method. Data preprocessing included removing reactions outside the 100–700 ms range and applying the Median Absolute Deviation (MAD) method to eliminate statistical outliers. Entropy was calculated based on discrete Shannon entropy applied to reaction time distribution histograms, with RT values grouped into intervals using Sturges' rule.
Results. It was found that as age increases, the average reaction time grows, but changes in variability are more significant. The coefficient of variation and interpercentile range (P90–P10) demonstrate an expansion of the value range and increased instability, especially in the 61–75 age group. Entropy values also increased with age, from 2.285 bits in the 17–18 group to 2.543 bits in the 61–75 group. Analysis revealed no functional dependence between entropy and mean reaction time or coefficient of variation, confirming that entropy reflects unique characteristics of distribution related to structural uncertainty. Generalized age dynamics show that while all metrics (Mean RT, CV, P90-P10, Entropy) increase with age, entropy demonstrates the most consistent and monotonic growth.
Originality. For the first time, an integral approach combining classical statistical metrics with Shannon entropy was applied to sensorimotor reaction time series across a wide age range to quantify the degree of organization of the central nervous system. The study demonstrates that entropy serves as an independent indicator of the "organized complexity" of behavioral responses that classical statistics cannot fully capture.
Conclusion. The introduction of entropy analysis allows for a deeper assessment of the functional state of the CNS beyond simple speed metrics. Age-related changes in sensorimotor reactions manifest not only as slowing but as a decrease in the stability and organization of the reaction process. Increased entropy in older age groups indicates higher uncertainty and reduced order in the functioning of the sensorimotor system, reflecting a decline in functional organization.