{"id":41534,"date":"2023-09-26T08:05:39","date_gmt":"2023-09-26T15:05:39","guid":{"rendered":"https:\/\/vermont.salk.edu\/?post_type=disclosure&#038;p=41534"},"modified":"2024-01-30T14:09:14","modified_gmt":"2024-01-30T22:09:14","slug":"unleashing-the-power-of-ai-to-track-animal-behavior","status":"publish","type":"disclosure","link":"https:\/\/www.salk.edu\/zh\/news-release\/unleashing-the-power-of-ai-to-track-animal-behavior\/","title":{"rendered":"\u91ca\u653e\u4eba\u5de5\u667a\u80fd\u7684\u529b\u91cf\uff0c\u8ffd\u8e2a\u52a8\u7269\u884c\u4e3a"},"content":{"rendered":"<p>LA JOLLA\u2014Movement offers a window into how the brain operates and controls the body. From clipboard-and-pen observation to modern artificial intelligence-based techniques, tracking human and animal movement has come a long way. Current cutting-edge methods utilize artificial intelligence to automatically track parts of the body as they move. However, training these models is still time-intensive and limited by the need for researchers to manually mark each body part hundreds to thousands of times. <\/p>\n<p>Now, Associate Professor <a href=\"https:\/\/www.salk.edu\/zh\/scientist\/eiman-azim\/\">Eiman Azim<\/a> and team have created GlowTrack, a non-invasive movement tracking method that uses fluorescent dye markers to train artificial intelligence. GlowTrack is robust, time-efficient, and high definition\u2014capable of tracking a single digit on a mouse\u2019s paw or hundreds of landmarks on a human hand.<\/p>\n<figure id=\"attachment_42126\"  class=\"wp-caption alignright\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"282\" class=\"img-responsive wp-image-42126 size-medium\" src=\"https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/colorized-hand-hr-300x282.jpg\" alt=\"Human hand marked with GlowTrack fluorescent tags.\" srcset=\"https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/colorized-hand-hr-300x282.jpg 300w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/colorized-hand-hr-147x138.jpg 147w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/colorized-hand-hr-458x430.jpg 458w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/colorized-hand-hr-585x550.jpg 585w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/colorized-hand-hr-553x520.jpg 553w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/colorized-hand-hr-400x376.jpg 400w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/colorized-hand-hr.jpg 615w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><figcaption class=\"wp-caption-text\">Human hand marked with GlowTrack fluorescent tags.<br \/><a href=\"https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/colorized-hand-hr.jpg\">Click here<\/a> for a high-resolution image.<br \/>Credit: Salk Institute<\/figcaption><\/figure>\n<p>The technique, published in <em><a href=\"https:\/\/www.nature.com\/articles\/s41467-023-41565-3\">Nature Communications<\/a><\/em>on September 26, 2023, has applications spanning from biology to robotics to medicine and beyond.<\/p>\n<p>\u201cOver the last several years, there has been a revolution in tracking behavior as powerful artificial intelligence tools have been brought into the laboratory,\u201d says Azim, senior author and holder of the William Scandling Developmental Chair. \u201cOur approach makes these tools more versatile, improving the ways we capture diverse movements in the laboratory. Better quantification of movement gives us better insight into how the brain controls behavior and could aid in the study of movement disorders like amyotrophic lateral sclerosis (ALS) and Parkinson\u2019s disease.\u201d<\/p>\n<p>Current methods to capture animal movement often require researchers to manually and repeatedly mark body parts on a computer screen\u2014a time-consuming process subject to human error and time constraints. Human annotation means that these methods can usually only be used in a narrow testing environment, since artificial intelligence models specialize to the limited amount of training data they receive. For example, if the light, orientation of the animal\u2019s body, camera angle, or any number of other factors were to change, the model would no longer recognize the tracked body part.<\/p>\n<p>To address these limitations, the researchers used fluorescent dye to label parts of the animal or human body. With these \u201cinvisible\u201d fluorescent dye markers, an enormous amount of visually diverse data can be created quickly and fed into the artificial intelligence models without the need for human annotation. Once fed this robust data, these models can be used to track movements across a much more diverse set of environments and at a resolution that would be far more difficult to achieve with manual human labeling.<\/p>\n<figure id=\"attachment_42127\"  class=\"wp-caption alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"458\" height=\"305\" class=\"img-responsive wp-image-42127 size-col-md-5\" src=\"https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/Azim-PR-20230628-1500-458x305.jpg\" alt=\"From left: Daniel Butler and Eiman Azim\" srcset=\"https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/Azim-PR-20230628-1500-458x305.jpg 458w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/Azim-PR-20230628-1500-300x200.jpg 300w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/Azim-PR-20230628-1500-1024x683.jpg 1024w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/Azim-PR-20230628-1500-768x512.jpg 768w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/Azim-PR-20230628-1500-147x98.jpg 147w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/Azim-PR-20230628-1500-585x390.jpg 585w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/Azim-PR-20230628-1500-553x369.jpg 553w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/Azim-PR-20230628-1500-750x500.jpg 750w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/Azim-PR-20230628-1500-767x511.jpg 767w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/Azim-PR-20230628-1500-945x630.jpg 945w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/Azim-PR-20230628-1500-1250x833.jpg 1250w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/Azim-PR-20230628-1500-400x267.jpg 400w, https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/Azim-PR-20230628-1500.jpg 1500w\" sizes=\"auto, (max-width: 458px) 100vw, 458px\" \/><figcaption class=\"wp-caption-text\">From left: Daniel Butler and Eiman Azim.<br \/><a href=\"https:\/\/www.salk.edu\/wp-content\/uploads\/2023\/07\/Azim-PR-20230628-1500.jpg\">Click here<\/a> for a high-resolution image.<br \/>Credit: Salk Institute<\/figcaption><\/figure>\n<p>This opens the door for easier comparison of movement data between studies, as different laboratories can use the same models to track body movement across a variety of situations. According to Azim, comparison and reproducibility of experiments are essential in the process of scientific discovery.<\/p>\n<p>\u201cFluorescent dye markers were the perfect solution,\u201d says first author Daniel Butler, a Salk bioinformatics analyst. Like the invisible ink on a dollar bill that lights up only when you want it to, our fluorescent dye markers can be turned on and off in the blink of an eye, allowing us to generate a massive amount of training data.\u201d<\/p>\n<p>In the future, the team is excited to support diverse applications of GlowTrack and pair its capabilities with other tracking tools that reconstruct movements in three dimensions, and with analysis approaches that can probe these vast movement datasets for patterns.<\/p>\n<p>\u201cOur approach can benefit a host of fields that need more sensitive, reliable, and comprehensive tools to capture and quantify movement,\u201d says Azim. \u201cI am eager to see how other scientists and non-scientists adopt these methods, and what unique, unforeseen applications might arise.\u201d<\/p>\n<p>Other authors include Alexander Keim and Shantanu Ray of Salk.<\/p>\n<p>The work was supported by the UC San Diego CMG Training Program, a Jesse and Caryl Philips Foundation Award, the National Institutes of Health (R00NS088193, DP2NS105555, R01NS111479, RF1NS128898, and U19NS112959), the Searle Scholars Program, the Pew Charitable Trusts, and the McKnight Foundation.<\/p>","protected":false},"featured_media":42126,"template":"","faculty":[291],"disease-research":[448,332],"class_list":["post-41534","disclosure","type-disclosure","status-publish","has-post-thumbnail","hentry","faculty-eiman-azim","disease-research-artificial-intelligence","disease-research-computational-biology"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Unleashing the power of AI to track animal behavior - Salk Institute for Biological Studies<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.salk.edu\/zh\/news-release\/unleashing-the-power-of-ai-to-track-animal-behavior\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Unleashing the power of AI to track animal behavior - Salk Institute for Biological Studies\" \/>\n<meta property=\"og:description\" content=\"LA JOLLA\u2014Movement offers a window into how the brain operates and controls the body. 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