Marta Russo, Antonella Maselli, Dagmar Sternad, Giovanni Pezzulo
{"title":"Predictive Strategies for the Control of Complex Motor Skills: Recent Insights into Individual and Joint Actions.","authors":"Marta Russo, Antonella Maselli, Dagmar Sternad, Giovanni Pezzulo","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Humans can perform exquisite sensorimotor skills, both individually and in teams, from athletes performing rhythmic gymnastics to everyday tasks like carrying a cup of coffee. The \"predictive brain\" framework suggests that mastering these tasks relies on predictive mechanisms, raising the question of how we deploy such predictions for real-time control and coordination. This review highlights two lines of research: one showing that during the control of complex objects people make the interaction with 'tools' predictable; the second one examines dyadic coordination showing that people make their behavior predictable for their partners. These studies demonstrate that to achieve sophisticated motor skills, we play \"prediction tricks\": we select subspaces of predictable solutions and make sensorimotor interactions more predictable and legible by and for others. This synthesis underscores the critical role of predictability in optimizing control strategies across various contexts and establishes a link between predictive processing and closed-loop control theories of behavior.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11643226/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ArXiv","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Humans can perform exquisite sensorimotor skills, both individually and in teams, from athletes performing rhythmic gymnastics to everyday tasks like carrying a cup of coffee. The "predictive brain" framework suggests that mastering these tasks relies on predictive mechanisms, raising the question of how we deploy such predictions for real-time control and coordination. This review highlights two lines of research: one showing that during the control of complex objects people make the interaction with 'tools' predictable; the second one examines dyadic coordination showing that people make their behavior predictable for their partners. These studies demonstrate that to achieve sophisticated motor skills, we play "prediction tricks": we select subspaces of predictable solutions and make sensorimotor interactions more predictable and legible by and for others. This synthesis underscores the critical role of predictability in optimizing control strategies across various contexts and establishes a link between predictive processing and closed-loop control theories of behavior.