Matthew Smart, Stanislav Y. Shvartsman, Martin Mönnigmann
{"title":"习惯化系统的最小图案","authors":"Matthew Smart, Stanislav Y. Shvartsman, Martin Mönnigmann","doi":"arxiv-2407.18204","DOIUrl":null,"url":null,"abstract":"Habituation - a phenomenon in which a dynamical system exhibits a diminishing\nresponse to repeated stimulations that eventually recovers when the stimulus is\nwithheld - is universally observed in living systems from animals to\nunicellular organisms. Despite its prevalence, generic mechanisms for this\nfundamental form of learning remain poorly defined. Drawing inspiration from\nprior work on systems that respond adaptively to step inputs, we study\nhabituation from a nonlinear dynamics perspective. This approach enables us to\nformalize classical hallmarks of habituation that have been experimentally\nidentified in diverse organisms and stimulus scenarios. We use this framework\nto investigate distinct dynamical circuits capable of habituation. In\nparticular, we show that driven linear dynamics of a memory variable with\nstatic nonlinearities acting at the input and output can implement numerous\nhallmarks in a mathematically interpretable manner. This work establishes a\nfoundation for understanding the dynamical substrates of this primitive\nlearning behavior and offers a blueprint for the identification of habituating\ncircuits in biological systems.","PeriodicalId":501517,"journal":{"name":"arXiv - QuanBio - Neurons and Cognition","volume":"19 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Minimal motifs for habituating systems\",\"authors\":\"Matthew Smart, Stanislav Y. Shvartsman, Martin Mönnigmann\",\"doi\":\"arxiv-2407.18204\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Habituation - a phenomenon in which a dynamical system exhibits a diminishing\\nresponse to repeated stimulations that eventually recovers when the stimulus is\\nwithheld - is universally observed in living systems from animals to\\nunicellular organisms. Despite its prevalence, generic mechanisms for this\\nfundamental form of learning remain poorly defined. Drawing inspiration from\\nprior work on systems that respond adaptively to step inputs, we study\\nhabituation from a nonlinear dynamics perspective. This approach enables us to\\nformalize classical hallmarks of habituation that have been experimentally\\nidentified in diverse organisms and stimulus scenarios. We use this framework\\nto investigate distinct dynamical circuits capable of habituation. In\\nparticular, we show that driven linear dynamics of a memory variable with\\nstatic nonlinearities acting at the input and output can implement numerous\\nhallmarks in a mathematically interpretable manner. This work establishes a\\nfoundation for understanding the dynamical substrates of this primitive\\nlearning behavior and offers a blueprint for the identification of habituating\\ncircuits in biological systems.\",\"PeriodicalId\":501517,\"journal\":{\"name\":\"arXiv - QuanBio - Neurons and Cognition\",\"volume\":\"19 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuanBio - Neurons and Cognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2407.18204\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Neurons and Cognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2407.18204","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Habituation - a phenomenon in which a dynamical system exhibits a diminishing
response to repeated stimulations that eventually recovers when the stimulus is
withheld - is universally observed in living systems from animals to
unicellular organisms. Despite its prevalence, generic mechanisms for this
fundamental form of learning remain poorly defined. Drawing inspiration from
prior work on systems that respond adaptively to step inputs, we study
habituation from a nonlinear dynamics perspective. This approach enables us to
formalize classical hallmarks of habituation that have been experimentally
identified in diverse organisms and stimulus scenarios. We use this framework
to investigate distinct dynamical circuits capable of habituation. In
particular, we show that driven linear dynamics of a memory variable with
static nonlinearities acting at the input and output can implement numerous
hallmarks in a mathematically interpretable manner. This work establishes a
foundation for understanding the dynamical substrates of this primitive
learning behavior and offers a blueprint for the identification of habituating
circuits in biological systems.