{"id":127947,"date":"2024-11-20T07:36:04","date_gmt":"2024-11-20T00:36:04","guid":{"rendered":"https:\/\/hotvideos24.online\/?p=127947"},"modified":"2024-11-20T07:36:04","modified_gmt":"2024-11-20T00:36:04","slug":"brain-models-reveal-how-we-process-lifes-small-surprises","status":"publish","type":"post","link":"https:\/\/hotvideos24.online\/?p=127947","title":{"rendered":"Brain Models Reveal How We Process Life\u2019s Small Surprises"},"content":{"rendered":"<p> <script async src=\"https:\/\/pagead2.googlesyndication.com\/pagead\/js\/adsbygoogle.js?client=ca-pub-3711241968723425\"\r\n     crossorigin=\"anonymous\"><\/script>\r\n<ins class=\"adsbygoogle\"\r\n     style=\"display:block\"\r\n     data-ad-format=\"fluid\"\r\n     data-ad-layout-key=\"-fb+5w+4e-db+86\"\r\n     data-ad-client=\"ca-pub-3711241968723425\"\r\n     data-ad-slot=\"7910942971\"><\/ins>\r\n<script>\r\n     (adsbygoogle = window.adsbygoogle || []).push({});\r\n<\/script><br \/>\n<\/p>\n<div>\n<p><strong>Summary: <\/strong>Researchers trained computer models to predict everyday events, revealing that responding to uncertainty, rather than just prediction errors, improved understanding. This challenges the idea that surprises alone drive event comprehension and suggests the brain may use dual mechanisms. Meanwhile, studies on memory show identifying event boundaries predicts better recall, especially for older adults.<\/p>\n<p>Ongoing research aims to improve memory by helping people recognize these boundaries more effectively. Findings may lead to interventions for age-related memory loss and enhance our understanding of cognitive processes. This work highlights the intricate ties between event segmentation and memory storage.<\/p>\n<p><strong>Key Facts:<\/strong><\/p>\n<ul class=\"wp-block-list\">\n<li>Computer models show uncertainty improves comprehension of everyday events.<\/li>\n<li>Identifying event boundaries strongly predicts memory retention.<\/li>\n<li>Older adults often struggle with event processing, linked to memory decline.<\/li>\n<\/ul>\n<p><strong>Source: <\/strong>WUSTL<\/p>\n<p><strong>Life is a series of small events: making morning coffee, letting the dog out, opening a laptop, letting the dog back in. Add them all up and you have a full day.<\/strong><\/p>\n<p>Our brains are committed to observing and processing the events that make up our daily lives, said\u00a0Jeff Zacks, the Edgar James Swift Professor in Arts &amp; Sciences and chair of the Department of Psychological &amp; Brain Sciences.<\/p>\n<p> \u201cKnowing where events begin and where they end is crucial to understanding the world,\u201d Zacks said.<\/p>\n<figure class=\"wp-block-image size-full\"><picture fetchpriority=\"high\" decoding=\"async\" class=\"wp-image-106341\"><source type=\"image\/webp\" srcset=\"https:\/\/neurosciencenews.com\/files\/2024\/11\/surprises-memory-neurosceince.jpg.webp 1200w, https:\/\/neurosciencenews.com\/files\/2024\/11\/surprises-memory-neurosceince-300x200.jpg.webp 300w, https:\/\/neurosciencenews.com\/files\/2024\/11\/surprises-memory-neurosceince-770x513.jpg.webp 770w, https:\/\/neurosciencenews.com\/files\/2024\/11\/surprises-memory-neurosceince-1155x770.jpg.webp 1155w, https:\/\/neurosciencenews.com\/files\/2024\/11\/surprises-memory-neurosceince-370x247.jpg.webp 370w, https:\/\/neurosciencenews.com\/files\/2024\/11\/surprises-memory-neurosceince-293x195.jpg.webp 293w, https:\/\/neurosciencenews.com\/files\/2024\/11\/surprises-memory-neurosceince-150x100.jpg.webp 150w\" sizes=\"(max-width: 1200px) 100vw, 1200px\"\/><img fetchpriority=\"high\" decoding=\"async\" width=\"1200\" height=\"800\" src=\"https:\/\/neurosciencenews.com\/files\/2024\/11\/surprises-memory-neurosceince.jpg\" alt=\"This shows two brains.\" srcset=\"https:\/\/neurosciencenews.com\/files\/2024\/11\/surprises-memory-neurosceince.jpg 1200w, https:\/\/neurosciencenews.com\/files\/2024\/11\/surprises-memory-neurosceince-300x200.jpg 300w, https:\/\/neurosciencenews.com\/files\/2024\/11\/surprises-memory-neurosceince-770x513.jpg 770w, https:\/\/neurosciencenews.com\/files\/2024\/11\/surprises-memory-neurosceince-1155x770.jpg 1155w, https:\/\/neurosciencenews.com\/files\/2024\/11\/surprises-memory-neurosceince-370x247.jpg 370w, https:\/\/neurosciencenews.com\/files\/2024\/11\/surprises-memory-neurosceince-293x195.jpg 293w, https:\/\/neurosciencenews.com\/files\/2024\/11\/surprises-memory-neurosceince-150x100.jpg 150w\" sizes=\"(max-width: 1200px) 100vw, 1200px\"\/> <\/picture><figcaption class=\"wp-element-caption\">Surprises still matter, and there\u2019s no need to completely throw out the concept of prediction error, Nguyen said. Credit: Neuroscience News<\/figcaption><\/figure>\n<p>In a pair of new papers, Zacks and other researchers in Arts &amp; Sciences and the McKelvey School of Engineering explore this key process of human cognition.\u00a0<\/p>\n<p>Zacks led a study that trained computer models to observe more than 25 hours of video of people performing simple, everyday tasks such as cleaning a kitchen or cooking a meal before making predictions about what happens next.<\/p>\n<p>The study came to a surprising conclusion: The computer models were most accurate when they responded to uncertainty. When the model was especially unsure about what would happen next, it would reset and reassess the scene, an approach that improved its overall comprehension.<\/p>\n<p>Co-authors of the study, which will be published in an upcoming edition of\u00a0<em>PNAS Nexus<\/em>,\u00a0include Tan Nguyen, a graduate student in Zacks\u2019s Dynamic Cognition Laboratory; Matt Bezdek, a senior scientist in the lab; Aaron Bobick, the James M. McKelvey Professor and dean of the McKelvey School of Engineering; Todd Braver, the William R. Stuckenberg Professor in Human Values and Moral Development; and Samuel Gershman, a Harvard neuroscientist.<\/p>\n<p>Zacks had previously theorized that the human brain was especially tuned to the small surprises that fill our lives. He proposed that people would reassess a scene every time they registered something they didn\u2019t expect, a phenomenon known as \u201cprediction error.\u201d<\/p>\n<p> The finding that the successful computer model paid more attention to uncertainty than to prediction errors threw the prior theory into doubt. \u201cWe\u2019re doing science here,\u201d Zacks said. \u201cWe revise theories when faced with new data.\u201d<\/p>\n<p>Surprises still matter, and there\u2019s no need to completely throw out the concept of prediction error, Nguyen said. \u201cWe\u2019re starting to think that the brain uses both mechanisms,\u201d he said. \u201cIt\u2019s not a case of either\/or. Each model can make unique contributions to our understanding of human cognition.\u201d<\/p>\n<p>Maverick Smith, a postdoctoral researcher in the\u00a0Dynamic Cognition Lab, is also taking a deeper look at the interplay between event comprehension and memory. Working with Heather Bailey, a former WashU postdoc who is now an associate professor at Kansas State University, Smith co-authored a review article in\u00a0<em>Nature Reviews Psychology<\/em>\u00a0gathering the growing evidence that long-term memory is intricately tied to the ability to logically and accurately discern where one event ends and another begins.<\/p>\n<p>\u201cThere are a lot of individual differences in the ability to identify when events start and stop, and those differences can strongly predict how much people remember later on,\u201d Smith said.<\/p>\n<p>\u201cWe hope to be able to create an intervention that could improve memory by helping people segment events.\u201d<\/p>\n<p>Like Zacks, Smith relies on video clips to better understand how the brain processes events. Instead of a person cooking and cleaning, his videos show a person shopping in a store, setting up a printer, or doing other mundane tasks.<\/p>\n<p>In various experiments, viewers push buttons whenever they discern the beginning or end of a particular event. Smith then tests the participant\u2019s memory of the videos with a series of written questions.<\/p>\n<p>Smith found that older people tend to have more difficulty processing events, a deficit that could play a role in age-related memory loss. \u201cMaybe there\u2019s a way we can intervene to help them better remember the events in their lives,\u201d he said.<\/p>\n<p>Zacks, Nguyen, Smith, and other members of the Department of Psychological &amp; Brain Sciences have ambitious plans to further their understanding of the brain\u2019s ability to process and remember events.<\/p>\n<p>Zacks\u2019 team is working to use fMRI brain imaging to track how 45 study participants respond to videos of everyday events in real time. \u201cWe\u2019re studying the actual neural dynamics of these cognitive processes,\u201d Zacks said.<\/p>\n<p>Another ongoing study tracks eye movements, providing new insight into how we see the world. \u201cWhen people watch an everyday activity, they spend a lot of time looking at and thinking about people\u2019s hands,\u201d Zacks explained.<\/p>\n<p>Smith is currently using video-based experiments to see if he can improve the memory of study subjects \u2014 including older people and those with Alzheimer\u2019s disease \u2014 by making the boundaries between events easier to identify. Ultimately, he would like to understand how event observations are stored and maintained in long-term memory.<\/p>\n<p>\u201cSome people are definitely better than others at segmenting events into meaningful chunks,\u201d Smith said. \u201cCan that ability be improved, and can that lead to improvements in memory? Those are the questions we\u2019re still asking.\u201d<\/p>\n<h2 class=\"wp-block-heading\">About this memory and neuroscience research news<\/h2>\n<p class=\"has-background\" style=\"background-color:#ffffe8\"><strong>Author:<\/strong><a href=\"http:\/\/neurosciencenews.com\/cdn-cgi\/l\/email-protection#d8b4abb0b9bebebdaa98afadabacb4f6bdbcad\" target=\"_blank\" rel=\"noreferrer noopener\"><strong> <\/strong>Leah Shaffer<\/a><br \/><strong>Source: <\/strong><a href=\"https:\/\/wustl.edu\" target=\"_blank\" rel=\"noreferrer noopener\">WUSTL<\/a><br \/><strong>Contact: <\/strong>Leah Shaffer \u2013 WUSTL<br \/><strong>Image: <\/strong>The image is credited to Neuroscience News<\/p>\n<p class=\"has-background\" style=\"background-color:#ffffe8\"><strong>Original Research:<\/strong> Open access.<br \/>\u201c<a href=\"https:\/\/doi.org\/10.1093\/pnasnexus\/pgae459\" target=\"_blank\" rel=\"noreferrer noopener\">Modeling human activity comprehension at human scale: Prediction, segmentation, and categorization<\/a>\u201d by Jeff Zacks et al. <em>PNAS Nexus<\/em><\/p>\n<hr class=\"wp-block-separator has-text-color has-pale-cyan-blue-color has-alpha-channel-opacity has-pale-cyan-blue-background-color has-background\"\/>\n<p><strong>Abstract<\/strong><\/p>\n<p><strong><strong>Modeling human activity comprehension at human scale: Prediction, segmentation, and categorization<\/strong><\/strong><\/p>\n<p>Humans form sequences of\u00a0<em>event models<\/em>\u2014representations of the current situation\u2014to predict how activity will unfold. Multiple mechanisms have been proposed for how the cognitive system determines when to segment the stream of behavior and switch from one active event model to another.<\/p>\n<p>Here, we constructed a computational model that learns knowledge about event classes (event schemas), by combining recurrent neural networks for short-term dynamics with Bayesian inference over event classes for event-to-event transitions.<\/p>\n<p>This architecture represents event schemas and uses them to construct a series of event models. This architecture was trained on one pass through 18\u2005h of naturalistic human activities. Another 3.5\u2005h of activities were used to test each variant for agreement with human segmentation and categorization.<\/p>\n<p>The architecture was able to learn to predict human activity, and it developed segmentation and categorization approaching human-like performance.<\/p>\n<p>We then compared two variants of this architecture designed to better emulate human event segmentation: one transitioned when the active event model produced high uncertainty in its prediction and the other transitioned when the active event model produced a large prediction error.<\/p>\n<p>The two variants learned to segment and categorize events, and the prediction uncertainty variant provided a somewhat closer match to human segmentation and categorization\u2014despite being given no feedback about segmentation or categorization.<\/p>\n<p>These results suggest that event model transitioning based on prediction uncertainty or prediction error can reproduce two important features of human event comprehension.<\/p>\n<p> <!-- Form created by Optin Forms plugin by WPKube: create beautiful optin forms with ease! --> <!-- https:\/\/wpkube.com\/ --><!--optinforms-form5-container--> <!-- \/ Optin Forms --> <\/div>\n<p><script async src=\"https:\/\/pagead2.googlesyndication.com\/pagead\/js\/adsbygoogle.js?client=ca-pub-3711241968723425\"\r\n     crossorigin=\"anonymous\"><\/script>\r\n<ins class=\"adsbygoogle\"\r\n     style=\"display:block\"\r\n     data-ad-format=\"fluid\"\r\n     data-ad-layout-key=\"-fb+5w+4e-db+86\"\r\n     data-ad-client=\"ca-pub-3711241968723425\"\r\n     data-ad-slot=\"7910942971\"><\/ins>\r\n<script>\r\n     (adsbygoogle = window.adsbygoogle || []).push({});\r\n<\/script><br \/>\n<br \/><div data-type=\"_mgwidget\" data-widget-id=\"1660802\">\r\n<\/div>\r\n<script>(function(w,q){w[q]=w[q]||[];w[q].push([\"_mgc.load\"])})(window,\"_mgq\");\r\n<\/script>\r\n<br \/>\n<br \/><a href=\"https:\/\/neurosciencenews.com\/neuroscience-memory-surprises-28084\/\">Source link <\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Summary: Researchers trained computer models to predict everyday events, revealing that responding to uncertainty, rather than just prediction errors, improved understanding. 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