By the time animals reach midlife, their everyday habits can offer clues about how long they are likely to live. This groundbreaking conclusion emerges from a new study supported by the Knight Initiative for Brain Resilience at Stanford’s Wu Tsai Neurosciences Institute, which meticulously monitored dozens of short-lived fish throughout their entire lives to unravel the intricate connections between behavior and the aging process. Published on March 12, 2026, in the prestigious journal Science, the research provides compelling evidence that subtle shifts in daily routines can serve as remarkably accurate predictors of longevity, offering a potential paradigm shift in our understanding of aging across species, including humans.
The study, led by Wu Tsai Neuro postdoctoral scholars Claire Bedbrook and Ravi Nath, was a direct outgrowth of a collaborative effort supported by the Knight Initiative, uniting the expertise of Stanford’s renowned geneticist Anne Brunet and bioengineer Karl Deisseroth, who served as the study’s senior authors. Their ambitious project aimed to move beyond traditional aging research, which often relies on comparing vastly different age groups, and instead delve into the continuous, individual trajectory of aging from its onset.
The Case for Continuous Behavioral Monitoring
Traditional approaches to aging research typically involve comparing the physiology and behavior of young animals to their much older counterparts. While this comparative method has yielded valuable insights, it often overlooks the nuanced, day-to-day progression of aging within an individual and the significant variations that can emerge even among genetically similar subjects living in identical environments. The research team recognized this limitation and set out to capture the full spectrum of an organism’s lifespan, observing how individuals age and diverge over time.
Bedbrook and Nath specifically sought to determine if observable behaviors could reveal the earliest signs of divergent aging paths. To achieve this, they selected the African turquoise killifish (Nothobranchius furzeri), a species renowned for its remarkably short lifespan, typically ranging from four to eight months. Despite its brevity, the killifish possesses a complex brain and shares significant biological features with humans, making it an invaluable model organism for aging research. The Brunet lab has been instrumental in establishing the killifish as a powerful tool for such investigations, and this study marked a significant advancement by being the first to continuously track individual vertebrates, around the clock, throughout their entire adult lives.
A "Truman Show" for Fish: The Automated Monitoring System
To achieve their goal of continuous, high-resolution data collection, the researchers engineered an innovative automated system. Each fish was housed in an individual tank, equipped with constant camera surveillance. This setup, akin to a biological "Truman Show," allowed for the meticulous recording of every moment of each animal’s adult life. The team ultimately followed 81 fish, amassing a colossal dataset comprising billions of video frames.
This unprecedented volume of data enabled the researchers to analyze a wide array of behavioral metrics, including posture, swimming speed, resting patterns, and overall movement. Through sophisticated computational analysis, they identified approximately 100 distinct "behavioral syllables." These syllables represent fundamental, repeating actions that collectively form the basic building blocks of how the fish navigate their environment and engage in resting behaviors.
"Behavior is a wonderfully integrated readout, reflecting what’s happening across the brain and body," explained Anne Brunet, the Michele and Timothy Barakett Professor of Genetics at Stanford Medicine. "Molecular markers are essential, but they capture only slices of biology. With behavior, you see the whole organism, continuously and non-invasively." This holistic perspective was crucial for addressing their core questions: When do individuals begin aging differently? What early traits delineate these diverging paths? And can behavior alone serve as a reliable predictor of lifespan?
Early Behavioral Divergence: The Predictors of Longevity
One of the most compelling discoveries of the study was the remarkably early emergence of behavioral differences that foreshadowed an individual’s ultimate lifespan. After painstakingly tracking each fish for its entire life, the researchers grouped them based on their longevity and then retrospectively examined their behavioral data to pinpoint when these divergences first became apparent. They discovered that by early midlife—defined as approximately 70 to 100 days of age—fish destined for shorter or longer lives were already exhibiting distinct behavioral patterns.
Sleep patterns emerged as a particularly salient indicator. Fish that ultimately experienced shorter lifespans displayed a tendency to sleep not only during the night but also increasingly during daylight hours. In stark contrast, the longer-lived fish maintained a more typical nocturnal sleep schedule.
Activity levels also played a significant role. Individuals on trajectories toward longer lifespans tended to swim with greater vigor, achieving higher speeds when navigating their tanks. They were also observed to be more active during daylight hours. This type of spontaneous, self-initiated movement has been previously linked to longevity in various other species, reinforcing the universality of these behavioral markers.
Crucially, these observed behavioral differences were not merely descriptive; they were demonstrably predictive. Utilizing advanced machine learning models, the research team established that even a few days of behavioral data collected from middle-aged fish were sufficient to accurately estimate their remaining lifespan. "Behavioral changes pretty early on in life are telling us about future health and future lifespan," stated Bedbrook, underscoring the profound predictive power of these early behavioral signals.
Aging as a Staged Process, Not a Gradual Decline
Beyond predicting lifespan, the study also offered a novel perspective on the fundamental nature of aging itself. Rather than a slow, steady, and linear decline, the research revealed that aging in these fish occurs in distinct stages. Most individuals experienced between two and six rapid behavioral shifts, each lasting only a few days, interspersed with longer periods of relative behavioral stability that could extend for weeks. Importantly, these transitions generally occurred in a sequential manner, with fish moving from one stage to the next without significant back-and-forth fluctuation.
"We expected aging to be a slow, gradual process," Bedbrook admitted. "Instead, animals stay stable for long periods and then transition very quickly into a new stage. Seeing this staged architecture appear from continuous behavior alone was one of the most exciting discoveries."
This stepwise progression aligns with a growing body of evidence from human studies suggesting that molecular changes associated with aging also occur in waves, particularly during midlife and later years. The killifish findings provide a compelling behavioral correlate to these observed biological phenomena. The researchers propose a model where aging is characterized by extended periods of relative equilibrium punctuated by brief, rapid transformations, akin to a Jenga tower where many blocks can be removed with minimal impact until a critical piece is dislodged, triggering a sudden collapse.
Unraveling the Biological Underpinnings
To investigate the biological mechanisms driving these observed behavioral patterns, the researchers examined gene activity in eight key organs at a specific stage when behavior could reliably predict lifespan. Rather than focusing on individual genes, they analyzed coordinated changes across gene networks involved in shared biological processes. The most pronounced differences were observed in the liver, where genes associated with protein synthesis and cellular maintenance exhibited higher activity in fish with shorter lifespans. This finding suggests that internal biological shifts occur in parallel with behavioral changes as aging progresses, reinforcing the integrated nature of the aging process.
Behavior as a Sensitive Lens on Aging
"Behavior turns out to be an incredibly sensitive readout of aging," remarked Nath. "You can look at two animals of the same chronological age and see from their behavior alone that they’re aging very differently." This sensitivity is particularly evident in aspects of daily life such as sleep. In humans, age-related declines in sleep quality and disrupted sleep-wake cycles are frequently linked to cognitive impairment and neurodegenerative diseases. Nath plans to explore whether interventions aimed at improving sleep could promote healthier aging and potentially alter aging trajectories.
The research team also intends to investigate whether aging paths can be modulated through targeted strategies, including dietary interventions and genetic manipulations designed to influence the pace of aging. For Bedbrook, the findings raise fundamental questions about the drivers of transitions between aging stages and the potential for delaying or reversing these shifts. She is also keen to explore aging in more naturalistic settings, where animals can engage in social interactions and experience a wider range of realistic environmental conditions.
"We now have the tools to map aging continuously in a vertebrate," she stated. "With the rise of wearables and long-term tracking in humans, I’m excited to see whether the same principles—early predictors, staged aging, divergent trajectories—hold true in people."
Further research will focus on the brain’s role in aging. Deisseroth’s lab is actively developing advanced tools for long-term neural activity monitoring, which could shed light on how brain changes correlate with bodily aging and potentially influence its rate. Bedbrook and Nath are poised to continue this pioneering work as they establish their own independent laboratories at Princeton University, building upon the foundational tools and insights developed during their tenure at Stanford.
Ultimately, this multifaceted research endeavor aims to elucidate the reasons behind the wide variability observed in aging processes and to identify novel avenues for promoting healthier and longer lives.
Publication Details and Research Team
The comprehensive study, titled "Continuous behavioral monitoring reveals staged aging and predicts lifespan in the African turquoise killifish," was published in Science on March 12, 2026. The research team comprised Claire Bedbrook (Department of Bioengineering, Stanford Medicine and Stanford Engineering), Ravi Nath (Department of Genetics, Stanford Medicine), Libby Zhang (Department of Electrical Engineering, Stanford Engineering), Scott Linderman (Department of Statistics, Stanford Humanities and Sciences; Knight Initiative for Brain Resilience; Wu Tsai Neurosciences Institute), Anne Brunet (Department of Genetics, Stanford Medicine; Wu Tsai Neurosciences Institute; Knight Initiative for Brain Resilience; Glenn Center for Biology of Aging), and Karl Deisseroth (D.H. Chen Professor; Departments of Bioengineering, Psychiatry and Behavioral Sciences, Stanford Medicine and Stanford Engineering; Knight Initiative for Brain Resilience; Howard Hughes Medical Institute).
Research Support
This extensive research was made possible through significant funding from various institutions. Key supporters included the National Institutes of Health (grants R01AG063418 and K99AG07687901), a Knight Initiative for Brain Resilience Catalyst Award and Brain Resilience Scholar Award, the Keck Foundation, the ARIA Foundation, the Glenn Foundation for Medical Research, the Simons Foundation, the Chan Zuckerberg Biohub—San Francisco, a NOMIS Distinguished Scientist and Scholar Award, the Helen Hay Whitney Foundation, the Wu Tsai Neurosciences Institute Interdisciplinary Scholar Award, and the Iqbal Farrukh & Asad Jamal Center for Cognitive Health in Aging.
Competing Interests Disclosure
Karl Deisseroth holds positions as a cofounder and scientific advisory board member for Stellaromics and Maplight Therapeutics, and provides advisory services to RedTree and Modulight.bio. Anne Brunet serves on the scientific advisory board of Calico. All other authors declared no conflicts of interest.
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