Synapses, Time, and the 200-Year Barrier: A Mathematical View of Human Longevity
Andrey Shcherbakov
Abstract
This article investigates age-related changes in synaptic density in the human brain as a quantitative basis for discussing the upper bound of human lifespan. Using published neurophysiological estimates, several approximation models are compared, including linear, quadratic, cubic, exponential, Gaussian, and logarithmic functions [1,4]. The analysis indicates that, for extrapolation beyond the observed range, the linear model is the most stable, whereas more complex functions describe the internal structure of the data within the observed interval more accurately. Based on the selected regression relationship, approximate age thresholds are estimated for successive levels of synaptic density decline, interpreted as a conditional boundary preserving the canonical organization of the human neural system. The study therefore integrates neuroscience, mathematical modeling, and philosophical anthropology, while recasting the discussion of the “200-year barrier” in a formal analytical framework.
