{"title":"Pupil Size Variations Reveal Information About Hierarchical Decision-Making Processes","authors":"Leyla Yahyaie, Reza Ebrahimpour, Abbas Koochari","doi":"10.1007/s12559-024-10246-8","DOIUrl":null,"url":null,"abstract":"<p><b>Introduction</b>: Pupil size is a well-known indicator of low-level decision-making processes. However, it is unclear whether these involuntary eye data can represent information about the interwoven processes of hierarchical decision-making. In hierarchical decisions, high-level decision-making depends on the process of making low-level decisions, and the result of these interwoven processes is determined by feedback. Therefore, the exact cause of negative feedback is unclear, as it may be the result of low-level, high-level, or both low- and high-level incorrect decisions. In this study, we investigated the characteristics of eye data (pupil diameter) in the interwoven processes of hierarchical decision-making. <b>Methods</b>: We designed a hierarchical psychophysical experiment in which participants were asked to report their low- and high-level decisions and their confidence simultaneously on one of the colored bars. Participants received correct feedback in a trial when reporting both decisions correctly. During the experiment, the eye data of the participants were recorded by an eye-tracking device. <b>Results</b>: Our findings suggest that pupil size conveys information about high-level decisions as well. Furthermore, this study shows that three parameters (introduced in previous studies), negative feedback in successive trials, stimulus strength (uniformity with confidence), and decision urgency, are all represented in pupil size. <b>Conclusion</b>: The findings support the idea that involuntary eye data are influenced by decision-making-related brain activity in decision-making processes and not just visual stimulus features.</p>","PeriodicalId":51243,"journal":{"name":"Cognitive Computation","volume":"33 1","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Computation","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s12559-024-10246-8","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Pupil size is a well-known indicator of low-level decision-making processes. However, it is unclear whether these involuntary eye data can represent information about the interwoven processes of hierarchical decision-making. In hierarchical decisions, high-level decision-making depends on the process of making low-level decisions, and the result of these interwoven processes is determined by feedback. Therefore, the exact cause of negative feedback is unclear, as it may be the result of low-level, high-level, or both low- and high-level incorrect decisions. In this study, we investigated the characteristics of eye data (pupil diameter) in the interwoven processes of hierarchical decision-making. Methods: We designed a hierarchical psychophysical experiment in which participants were asked to report their low- and high-level decisions and their confidence simultaneously on one of the colored bars. Participants received correct feedback in a trial when reporting both decisions correctly. During the experiment, the eye data of the participants were recorded by an eye-tracking device. Results: Our findings suggest that pupil size conveys information about high-level decisions as well. Furthermore, this study shows that three parameters (introduced in previous studies), negative feedback in successive trials, stimulus strength (uniformity with confidence), and decision urgency, are all represented in pupil size. Conclusion: The findings support the idea that involuntary eye data are influenced by decision-making-related brain activity in decision-making processes and not just visual stimulus features.
期刊介绍:
Cognitive Computation is an international, peer-reviewed, interdisciplinary journal that publishes cutting-edge articles describing original basic and applied work involving biologically-inspired computational accounts of all aspects of natural and artificial cognitive systems. It provides a new platform for the dissemination of research, current practices and future trends in the emerging discipline of cognitive computation that bridges the gap between life sciences, social sciences, engineering, physical and mathematical sciences, and humanities.