{"title":"在自然感知过程中,人们可以可靠地检测到动作变化和目标变化。","authors":"Xing Su, Khena M Swallow","doi":"10.3758/s13421-024-01525-8","DOIUrl":null,"url":null,"abstract":"<p><p>As a part of ongoing perception, the human cognitive system segments others' activities into discrete episodes (event segmentation). Although prior research has shown that this process is likely related to changes in an actor's actions and goals, it has not yet been determined whether untrained observers can reliably identify action and goal changes as naturalistic activities unfold, or whether the changes they identify are tied to visual features of the activity (e.g., the beginnings and ends of object interactions). This study addressed these questions by examining untrained participants' identification of action changes, goal changes, and event boundaries while watching videos of everyday activities that were presented in both first-person and third-person perspectives. We found that untrained observers can identify goal changes and action changes consistently, and these changes are not explained by visual change and the onsets or offsets of contact with objects. Moreover, the action and goal changes identified by untrained observers were associated with event boundaries, even after accounting for objective visual features of the videos. These findings suggest that people can identify action and goal changes consistently and with high agreement, that they do so by using sensory information flexibly, and that the action and goal changes they identify may contribute to event segmentation.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"People can reliably detect action changes and goal changes during naturalistic perception.\",\"authors\":\"Xing Su, Khena M Swallow\",\"doi\":\"10.3758/s13421-024-01525-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>As a part of ongoing perception, the human cognitive system segments others' activities into discrete episodes (event segmentation). Although prior research has shown that this process is likely related to changes in an actor's actions and goals, it has not yet been determined whether untrained observers can reliably identify action and goal changes as naturalistic activities unfold, or whether the changes they identify are tied to visual features of the activity (e.g., the beginnings and ends of object interactions). This study addressed these questions by examining untrained participants' identification of action changes, goal changes, and event boundaries while watching videos of everyday activities that were presented in both first-person and third-person perspectives. We found that untrained observers can identify goal changes and action changes consistently, and these changes are not explained by visual change and the onsets or offsets of contact with objects. Moreover, the action and goal changes identified by untrained observers were associated with event boundaries, even after accounting for objective visual features of the videos. These findings suggest that people can identify action and goal changes consistently and with high agreement, that they do so by using sensory information flexibly, and that the action and goal changes they identify may contribute to event segmentation.</p>\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.3758/s13421-024-01525-8\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/2/5 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.3758/s13421-024-01525-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/2/5 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
People can reliably detect action changes and goal changes during naturalistic perception.
As a part of ongoing perception, the human cognitive system segments others' activities into discrete episodes (event segmentation). Although prior research has shown that this process is likely related to changes in an actor's actions and goals, it has not yet been determined whether untrained observers can reliably identify action and goal changes as naturalistic activities unfold, or whether the changes they identify are tied to visual features of the activity (e.g., the beginnings and ends of object interactions). This study addressed these questions by examining untrained participants' identification of action changes, goal changes, and event boundaries while watching videos of everyday activities that were presented in both first-person and third-person perspectives. We found that untrained observers can identify goal changes and action changes consistently, and these changes are not explained by visual change and the onsets or offsets of contact with objects. Moreover, the action and goal changes identified by untrained observers were associated with event boundaries, even after accounting for objective visual features of the videos. These findings suggest that people can identify action and goal changes consistently and with high agreement, that they do so by using sensory information flexibly, and that the action and goal changes they identify may contribute to event segmentation.