{"id":534251,"date":"2026-03-13T18:46:29","date_gmt":"2026-03-13T18:46:29","guid":{"rendered":"https:\/\/www.newsbeep.com\/ca\/534251\/"},"modified":"2026-03-13T18:46:29","modified_gmt":"2026-03-13T18:46:29","slug":"lifelong-motion-patterns-predict-lifespan","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/ca\/534251\/","title":{"rendered":"Lifelong Motion Patterns Predict Lifespan"},"content":{"rendered":"<p>Summary: We often think of aging as a slow, steady decline, but new research suggests it is actually a series of rapid, discrete shifts. By monitoring African turquoise killifish 24\/7 across their entire adult lives, scientists discovered that behavior in early midlife can predict an individual\u2019s total lifespan.<\/p>\n<p>Despite shared genetics and environments, some fish began \u201cnapping\u201d during the day and swimming slower as young adults\u2014early signals that they were on a \u201cshort-lived\u201d trajectory. This study suggests that aging isn\u2019t a smooth slide but a \u201cstaged architecture\u201d where the body remains stable for weeks before transitioning into a new stage in just a few days.<\/p>\n<p>Key Facts<\/p>\n<p>The \u201cTruman Show\u201d for Fish: Researchers tracked 81 fish continuously, generating billions of video frames to identify 100 \u201cbehavioral syllables\u201d (basic building blocks of movement and rest).Early Predictors: By day 70\u2013100 (early adulthood for killifish), behavioral differences in sleep and swimming speed were strong enough for machine-learning models to forecast which fish would live the longest.Stepwise Aging: Aging progressed in 2\u20136 rapid transitions. Like a Jenga tower, the \u201cstructure\u201d of the animal\u2019s behavior stayed stable until a sudden shift forced a new, less-resilient stage.The Sleep Signal: Fish on shorter aging paths began sleeping significantly more during the day, while long-lived fish remained active during daylight and slumbered primarily at night.Molecular Mirror: At the point where behavior became predictive, the researchers found coordinated gene activity changes in the liver, specifically in processes related to protein production and cellular maintenance.<\/p>\n<p>Source: Stanford<\/p>\n<p>By midlife, an animal\u2019s everyday behaviors can signal how long it is likely to live.\u00a0\u00a0<\/p>\n<p>That is the striking conclusion of a new study supported by the Knight Initiative for Brain Resilience at Stanford\u2019s Wu Tsai Neurosciences Institute, in which researchers put scores of short-lived fish under continuous, lifelong surveillance to explore how behavior and aging are linked.<\/p>\n<p>  <img fetchpriority=\"high\" decoding=\"async\" width=\"1200\" height=\"800\" src=\"https:\/\/www.newsbeep.com\/ca\/wp-content\/uploads\/2026\/03\/longevity-motion-neuroscience.jpg\" alt=\"This shows an old man walking.\"  \/> Researchers have discovered that vertebrate aging proceeds in discrete, rapid transitions rather than a gradual decline, with early-life behavior serving as a sensitive predictor of total lifespan. Credit: Neuroscience News<\/p>\n<p>Individual fish aged in markedly different ways, despite having similar genetics and living in a carefully controlled environment. By early adulthood, those differences were already visible in how the animals swam and rested\u2014and were strong enough to predict whether a fish would ultimately live a long or short life.<\/p>\n<p>While the research was conducted in fish, the findings raise the possibility that tracking subtle, daily behaviors like movement and sleep, now routinely captured by wearable devices, may offer clues about how aging unfolds in people.\u00a0<\/p>\n<p>The findings were published in\u00a0Science\u00a0on March 12, 2016, in a study led by Wu Tsai Neuro postdoctoral scholars\u00a0Claire Bedbrook\u00a0and\u00a0Ravi Nath. The research grew out of a\u00a0Knight Initiative\u2013supported collaboration\u00a0between the Stanford labs of geneticist\u00a0Anne Brunet\u00a0and bioengineer\u00a0Karl Deisseroth, the study\u2019s senior authors.<\/p>\n<p>How to watch aging unfold in real time<\/p>\n<p>Most aging studies contrast groups of young animals with groups of old ones. While informative, those snapshots blur how aging unfolds within individuals over time, and how differences between individuals emerge.\u00a0<\/p>\n<p>Bedbrook and Nath wanted to know what might be revealed by watching aging continuously across an entire adult lifespan. Even animals of the same species, raised under similar conditions, can follow very different aging paths and live dramatically different lengths of time. The researchers asked whether natural behavior could reveal when and how those individual trajectories begin to diverge.<\/p>\n<p>The African turquoise killifish made that question experimentally possible. With a typical lifespan of just four to eight months, it is one of the shortest-lived vertebrates studied in the lab, yet it shares key biological features with longer-lived species like humans, including a complex brain.<\/p>\n<p>The Brunet lab has been at the forefront of\u00a0developing the killifish as a model for studying aging, laying the foundation for this study, the first to follow individual vertebrates continuously, day and night, across their entire adult lives.\u00a0<\/p>\n<p>Bedbrook, Nath, and their colleagues built an automated system in which individual fish lived in separate, camera-monitored tanks. Like a scientific version of\u00a0The Truman Show, the 1998 film in which a man\u2019s entire life is recorded continuously, the setup captured every moment of the animals\u2019 lives. In total, they tracked 81 fish and generated billions of video frames.\u00a0<\/p>\n<p>From those recordings, the researchers extracted detailed information about the animals\u2019 posture, speed, rest, and movement, identifying 100 distinct \u201cbehavioral syllables\u201d\u2014short, recurrent actions that represent the basic building blocks of how a fish moves and rests.<\/p>\n<p>\u201cBehavior is a wonderfully integrated readout, reflecting what\u2019s happening across the brain and body,\u201d said Brunet, the Michele and Timothy Barakett Professor of Genetics at Stanford Medicine. \u201cMolecular markers are essential, but they capture only slices of biology. With behavior, you see the whole organism, continuously and non-invasively.\u201d<\/p>\n<p>With this life-long behavioral record in hand, the researchers could begin asking a new set of questions: When do animals start to age differently? What distinguishes those paths early on? And, can behavior alone predict whether an individual will live to a ripe old age?<\/p>\n<p>Early signals of an animal\u2019s lifespan\u00a0<\/p>\n<p>One of the team\u2019s most surprising findings was how early individual aging paths begin to diverge. After following each fish through its entire lifespan, the researchers grouped animals based on how long they ultimately lived and then looked back to see when behavioral differences first emerged.<\/p>\n<p>They found by early midlife (70 to 100 days of age), fish that would go on to live shorter or longer lives were already behaving differently.<\/p>\n<p>Some of the clearest differences involved sleep. As young adults, fish that went on to have shorter lives tended to sleep not only at night but increasingly during the day. In contrast, fish that went on to longer lives mainly slumbered at night.<\/p>\n<p>But sleep was not the only signal. Fish on paths to a longer life also swam with greater vigor and reached higher speeds when darting around the tank\u2014a measure of spontaneous movement that has been linked to longevity in other species as well. They also tended to be far more active during daylight hours.<\/p>\n<p>Crucially, those behavioral differences were not just descriptive but predictive. Using machine-learning models, the researchers showed that just a few days of behavioral data from middle-aged fish were enough to forecast lifespan. \u201cBehavioral changes pretty early on in life are telling us about future health and future lifespan,\u201d said Bedbrook.<\/p>\n<p>Aging unfolds in steps<\/p>\n<p>The team\u2019s observations also revealed that aging\u2014in killifish, at least\u2014does not progress as a smooth, gradual drift. Most of the fish underwent two to six rapid behavioral transitions, each lasting just a few days, followed by longer, stable stages that lasted weeks. Importantly, fish tended to progress through these stages in sequence, rather than switching back and forth between them.<\/p>\n<p>\u201cWe expected aging to be a slow, gradual process,\u201d said Bedbrook. \u201cInstead, 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.\u201d<\/p>\n<p>This stepwise pattern echoes emerging evidence from\u00a0human studies, including research showing that molecular features of aging\u00a0change in waves, especially during midlife and older adulthood. The killifish results offer a behavioral view of the same phenomenon.<\/p>\n<p>The researchers suggest that aging may involve long stretches of relative stability punctuated by brief periods of rapid change. This process is more like a Jenga tower, in which many blocks can be removed with little effect, until one change forces a sudden restructuring, than a smooth downhill slide.<\/p>\n<p>The researchers also examined gene activity across eight organs in adult fish at a stage when behavior could reliably predict future lifespan. Rather than focusing on individual genes, they looked for coordinated changes across groups of genes that work together in shared biological processes.<\/p>\n<p>The clearest differences appeared in the liver, where genes involved in protein production and cellular maintenance were more active in fish on shorter aging paths. These findings offered a molecular hint that the animals\u2019 internal biology is changing alongside the behavioral patterns as they age.<\/p>\n<p>Behavior as a new window into aging<\/p>\n<p>\u201cBehavior turns out to be an incredibly sensitive readout of aging,\u201d said Nath. \u201cYou can look at two animals of the same chronological age and see from their behavior alone that they\u2019re aging very differently.\u201d<\/p>\n<p>That sensitivity shows up across many aspects of daily life, including sleep, which emerged as an important signal of how aging was unfolding. In humans, sleep quality and sleep-wake cycles often deteriorate with age, and these changes have been linked to cognitive decline and neurodegenerative disease.<\/p>\n<p>Nath aims to explore whether sleep itself can be manipulated to promote healthier aging, and whether intervening early, before decline sets in, can alter an individual\u2019s aging path.<\/p>\n<p>The team also plans to test whether aging paths can be modified through targeted interventions, including changes to diet as well as to genes that may help influence the pace of aging.<\/p>\n<p>For Bedbrook, the killifish study opens the door to deeper questions about what drives aging transitions and whether those transitions can be delayed, prevented, or reversed. She is also interested in pushing the experimental system toward more naturalistic settings, allowing animals to interact socially and experience richer environments that more closely resemble real life.\u00a0<\/p>\n<p>\u201cWe now have the tools to map aging continuously in a vertebrate,\u201d she said. \u201cWith the rise of wearables and long-term tracking in humans, I\u2019m excited to see whether the same principles\u2014early predictors, staged aging, divergent trajectories\u2014hold true in people.\u201d<\/p>\n<p>Another major frontier lies in the brain itself. Deisseroth\u2019s lab develops tools to monitor neural activity continuously over long periods of time, making it possible to follow changes in brain activity alongside the same animals\u2019 aging paths. Those experiments could reveal whether the brain mirrors aging in the rest of the body or plays a more active role in setting its pace.<\/p>\n<p>Both Bedbrook and Nath will continue pursuing these questions as they open their own laboratories at Princeton University this July, bringing the tools and ideas developed at Stanford into the next phase of their research.<\/p>\n<p>Ultimately, the hope is that mapping aging at this resolution will clarify why aging varies so widely, and point toward new ways of promoting healthy aging.<\/p>\n<p>Funding: The research was funded by the National Institutes of Health (R01AG063418 and\u00a0K99AG07687901), a\u00a0Knight Initiative for Brain Resilience Catalyst Award\u00a0and\u00a0Brain Resilience Scholar Award,\u00a0the Keck Foundation, the ARIA Foundation, the Glenn Foundation for Medical Research, the Simons Foundation, the Chan Zuckerberg Biohub \u2013 San Francisco, a NOMIS Distinguished Scientist and Scholar Award, the Helen Hay Whitney Foundation, the\u00a0Wu Tsai Neurosciences Institute Interdisciplinary Scholar Award, and the Iqbal Farrukh &amp; Asad Jamal Center for Cognitive Health in Aging.<\/p>\n<p>Competing Interests<\/p>\n<p>Karl Diesseroth is a cofounder and a scientific advisory board member of Stellaromics and Maplight Therapeutics, and advises RedTree and Modulight.bio. Anne Brunet is a scientific advisory board member of Calico. All other authors declare no conflicts of interest.<\/p>\n<p>Key Questions Answered:Q: Does \u201cnapping\u201d mean I\u2019m aging faster?<\/p>\n<p class=\"schema-faq-answer\">A: In killifish, daytime napping was a major red flag for a shorter lifespan. It suggests that the internal biological clock or energy levels are starting to falter. While humans are different, this study aligns with data showing that disrupted sleep-wake cycles in people are often early precursors to cognitive decline.<\/p>\n<p>Q: Why use fish to study human aging?<\/p>\n<p class=\"schema-faq-answer\">A: The African turquoise killifish is a \u201cbiological shortcut.\u201d It lives only 4\u20138 months but has a complex vertebrate brain and shares many aging markers with humans. This allows scientists to watch a \u201clifetime\u201d in months rather than decades.<\/p>\n<p>Q: Can I change my \u201caging trajectory\u201d?<\/p>\n<p class=\"schema-faq-answer\">A: That\u2019s the million-dollar question. Now that we can identify these \u201cstages\u201d of aging, the Stanford team wants to see if interventions (like diet or light therapy) can stall or even reverse a transition before it becomes permanent. If we can spot the \u201cJenga block\u201d before it falls, we might be able to stabilize the tower.<\/p>\n<p>Editorial Notes:This article was edited by a Neuroscience News editor.Journal paper reviewed in full.Additional context added by our staff.About this aging and longevity research news<\/p>\n<p class=\"has-background\" style=\"background-color:#ffffe8\">Author: <a href=\"http:\/\/neurosciencenews.com\/cdn-cgi\/l\/email-protection#016f7664686d6473417275606f676e73652f646574\" type=\"mailto\" id=\"mailto:nweiler@stanford.edu\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Nicholas Weiler<\/a><br \/>Source: <a href=\"https:\/\/stanford.edu\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Stanford<\/a><br \/>Contact: Nicholas Weiler \u2013 Stanford<br \/>Image: The image is credited to Neuroscience News<\/p>\n<p class=\"has-background\" style=\"background-color:#ffffe8\">Original Research: Closed access.<br \/>\u201c<a href=\"https:\/\/dx.doi.org\/10.1126\/science.aea9795\" type=\"link\" id=\"http:\/\/dx.doi.org\/10.1126\/science.aea9795\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Lifelong behavioral screen reveals an architecture of vertebrate aging<\/a>\u201d by Claire N. Bedbrook, Ravi D. Nath, Libby Zhang, Scott W. Linderman, Anne Brunet, and Karl Deisseroth. Science<br \/>DOI:10.1126\/science.aea9795<\/p>\n<p>Abstract<\/p>\n<p>Lifelong behavioral screen reveals an architecture of vertebrate aging<\/p>\n<p>Mapping behavior of individual vertebrate animals across lifespan could provide an unprecedented view into the lifelong process of aging. We created a platform for high-resolution continuous behavioral tracking of the African killifish across natural lifespan from adolescence to death.<\/p>\n<p>We found 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 inferred age and even forecasted an individual\u2019s future lifespan, given only behavior at a young age.<\/p>\n<p>Finally, we found that animals progressed through adulthood in a sequence of stable and stereotyped behavioral stages with abrupt transitions, revealing precise structure for an architecture of aging.<\/p>\n","protected":false},"excerpt":{"rendered":"Summary: We often think of aging as a slow, steady decline, but new research suggests it is actually&hellip;\n","protected":false},"author":2,"featured_media":534252,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7],"tags":[128,62,276,209223,49,48,209224,8624,796,9078,66,53505,10532],"class_list":["post-534251","post","type-post","status-publish","format-standard","has-post-thumbnail","category-science","tag-aging","tag-ai","tag-artificial-intelligence","tag-behavioral-syllables","tag-ca","tag-canada","tag-lifespan-prediction","tag-longevity","tag-machine-learning","tag-neuroscience","tag-science","tag-sleep-patterns","tag-stanford-university"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/posts\/534251","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/comments?post=534251"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/posts\/534251\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/media\/534252"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/media?parent=534251"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/categories?post=534251"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/tags?post=534251"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}