Continuous behavioral tracking of African killifish across their entire lifespan reveals that vertebrate aging follows distinct individual trajectories that diverge early in life based on future lifespan, with behavior alone accurately predicting both chronological age and remaining life, and demonstrates that aging proceeds through discrete, stable life stages with orderly forward transitions rather than gradual decline.

Mapping behavior of individual vertebrate animals across lifespan is challenging, but if achieved, could provide an unprecedented view into the life-long process of aging. We created the first platform for high-resolution continuous behavioral tracking of a vertebrate animal across natural lifespan from adolescence to death—here, of the African killifish. This behavioral screen revealed that animals follow distinct individual aging trajectories. The behaviors of long-lived animals differed markedly from those of short-lived animals, even relatively early in life, and were linked to organ-specific transcriptomic shifts. Machine learning models accurately predicted age and even forecasted an individual’s future lifespan, given only behavior at a young age. Finally, we found that animals progressed through adulthood in a sequence of stable and stereotyped behavioral stages with abrupt transitions suggesting a novel structure for the architecture of vertebrate aging.