Science is advancing towards accurately predicting lifespan based on daily habits, as highlighted in new research conducted by Stanford University.

The study observed the behavior of 81 African turquoise killifish in a camera-monitored aquarium throughout their lifespan, which ranges from four to eight months.

By analyzing billions of frames of video footage, scientists established a link between daily behavioral patterns and longevity.

Co-first author Dr. Claire Bedbrook, a bioengineer and neuroscientist, stated, “One of the main findings of this study is that behavior serves as a non-invasive indicator of the aging process.” BBC Science Focus.

She added, “By tracking simple metrics such as activity and sleep patterns over a 24-hour period, we gain insights into aging progression and potential lifespan predictions.”

With the rise of smartwatches, scientists anticipate a future where individual aging journeys can be quantified more effectively.

This research sheds light on the aging processes in animals with complex brains.

A key finding suggests that towards early middle age, when their lifespans reach approximately 70 to 100 days, fish destined for longer lives exhibit different behaviors compared to those that die earlier.

Co-first author Dr. Ravi Nath, also a neuroscientist and geneticist, remarked, “We could accurately estimate an animal’s age and whether it has a short or long lifespan based on its behavior at a relatively young age.” BBC Science Focus.

Notably, the research revealed variations in sleep patterns. Long-lived fish primarily sleep at night, while those with shorter lifespans increasingly sleep during the day as they mature.

Additionally, more active fish—those that swim more vigorously and spontaneously during the day—were found to have a higher likelihood of living longer.

The team identified a total of 100 distinct “action syllables,” representing short actions that form the foundational aspects of medaka behavior, many of which correlate with lifespan.

Utilizing machine learning models, researchers accurately predicted the lifespan of individual fish based on a few days of behavioral data during mid-life.

Furthermore, the study found that fish age in distinct stages rather than continuously, supporting similar findings in recent research on humans.

Dr. Bedbrook explained, “I initially believed aging to be a gradual process, but our behavioral tracking indicates long periods of stability followed by sudden aging phases where animals enter new life stages.”

Future studies will aim to analyze behaviors in more natural settings, potentially allowing fish to exhibit increased social interactions.

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