Kumaresh Krishnan, Akila Muthukumar, Scott Sterrett, Paula Pflitsch, Adrienne L. Fairhall, Mark Fishman, Armin Bahl, Hanna Zwaka, Florian Engert
{"title":"斑马鱼幼体的注意力转换","authors":"Kumaresh Krishnan, Akila Muthukumar, Scott Sterrett, Paula Pflitsch, Adrienne L. Fairhall, Mark Fishman, Armin Bahl, Hanna Zwaka, Florian Engert","doi":"10.1126/sciadv.ads4994","DOIUrl":null,"url":null,"abstract":"<div >Decision-making strategies in the face of conflicting or uncertain sensory input have been successfully described in many species. We analyze large behavioral datasets of larval zebrafish engaged in a “coherent dot” optomotor assay and find that animal performance is bimodal. Performance can be separated into two “states”—an engaged (attentive) state with high performance, where fish consistently turn in the direction of coherent motion, and a second, disengaged (inattentive) state, where performance drops to chance. A hidden Markov model is sufficient to model these transitions and can be incorporated into a drift-diffusion model framework that has previously been used to model perceptual decision-making in larval zebrafish. Furthermore, we fit a mixture model of performance distributions and extract two latent variables termed “focus” and “competence” that are largely influenced by parents and environmental context, respectively. This quantitative framework can potentially help to identify a genetic basis and a neural mechanism for attention that extends across organisms.</div>","PeriodicalId":21609,"journal":{"name":"Science Advances","volume":"11 40","pages":""},"PeriodicalIF":12.5000,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.science.org/doi/reader/10.1126/sciadv.ads4994","citationCount":"0","resultStr":"{\"title\":\"Attentional switching in larval zebrafish\",\"authors\":\"Kumaresh Krishnan, Akila Muthukumar, Scott Sterrett, Paula Pflitsch, Adrienne L. Fairhall, Mark Fishman, Armin Bahl, Hanna Zwaka, Florian Engert\",\"doi\":\"10.1126/sciadv.ads4994\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div >Decision-making strategies in the face of conflicting or uncertain sensory input have been successfully described in many species. We analyze large behavioral datasets of larval zebrafish engaged in a “coherent dot” optomotor assay and find that animal performance is bimodal. Performance can be separated into two “states”—an engaged (attentive) state with high performance, where fish consistently turn in the direction of coherent motion, and a second, disengaged (inattentive) state, where performance drops to chance. A hidden Markov model is sufficient to model these transitions and can be incorporated into a drift-diffusion model framework that has previously been used to model perceptual decision-making in larval zebrafish. Furthermore, we fit a mixture model of performance distributions and extract two latent variables termed “focus” and “competence” that are largely influenced by parents and environmental context, respectively. This quantitative framework can potentially help to identify a genetic basis and a neural mechanism for attention that extends across organisms.</div>\",\"PeriodicalId\":21609,\"journal\":{\"name\":\"Science Advances\",\"volume\":\"11 40\",\"pages\":\"\"},\"PeriodicalIF\":12.5000,\"publicationDate\":\"2025-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.science.org/doi/reader/10.1126/sciadv.ads4994\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science Advances\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://www.science.org/doi/10.1126/sciadv.ads4994\",\"RegionNum\":1,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science Advances","FirstCategoryId":"103","ListUrlMain":"https://www.science.org/doi/10.1126/sciadv.ads4994","RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Decision-making strategies in the face of conflicting or uncertain sensory input have been successfully described in many species. We analyze large behavioral datasets of larval zebrafish engaged in a “coherent dot” optomotor assay and find that animal performance is bimodal. Performance can be separated into two “states”—an engaged (attentive) state with high performance, where fish consistently turn in the direction of coherent motion, and a second, disengaged (inattentive) state, where performance drops to chance. A hidden Markov model is sufficient to model these transitions and can be incorporated into a drift-diffusion model framework that has previously been used to model perceptual decision-making in larval zebrafish. Furthermore, we fit a mixture model of performance distributions and extract two latent variables termed “focus” and “competence” that are largely influenced by parents and environmental context, respectively. This quantitative framework can potentially help to identify a genetic basis and a neural mechanism for attention that extends across organisms.
期刊介绍:
Science Advances, an open-access journal by AAAS, publishes impactful research in diverse scientific areas. It aims for fair, fast, and expert peer review, providing freely accessible research to readers. Led by distinguished scientists, the journal supports AAAS's mission by extending Science magazine's capacity to identify and promote significant advances. Evolving digital publishing technologies play a crucial role in advancing AAAS's global mission for science communication and benefitting humankind.