Katherine Boere , Francesca Anderson , Kent G. Hecker , Olav E. Krigolson
{"title":"利用移动 fNIRS 测量多任务处理中的认知负荷","authors":"Katherine Boere , Francesca Anderson , Kent G. Hecker , Olav E. Krigolson","doi":"10.1016/j.ynirp.2024.100228","DOIUrl":null,"url":null,"abstract":"<div><div>Cognitive load, or the mental effort required to process and retain information, is a critical factor in high-stakes environments where task demands often exceed working memory capacity, leading to performance declines and errors. However, most cognitive load research has relied on controlled, single-task paradigms, limiting its applicability to real-world multitasking situations. Addressing this gap, we used a mobile, two-channel functional near-infrared spectroscopy (fNIRS) device to measure cognitive load in a complex multitasking environment, simulating real-world cognitive demands. Thirty-one undergraduate participants engaged in single-task and multitask conditions to simulate real-world cognitive demands. Results showed that subjective cognitive load ratings were higher, performance scores were lower, and error rates increased in the multitask condition compared to the single-task condition. However, contrary to expectations, prefrontal cortex activation did not increase in the multitask condition, suggesting a \"cognitive disengagement\" effect, where the brain limits engagement to manage overload. This finding challenges the traditional one-to-one association between cognitive load and prefrontal activation, as seen in simpler validation studies. Our study highlights the value of mobile fNIRS for assessing cognitive load in ecologically valid settings and provides insights that could inform strategies for optimizing performance in high-stakes environments like aviation and healthcare.</div></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":"4 4","pages":"Article 100228"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Measuring cognitive load in multitasking using mobile fNIRS\",\"authors\":\"Katherine Boere , Francesca Anderson , Kent G. Hecker , Olav E. Krigolson\",\"doi\":\"10.1016/j.ynirp.2024.100228\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Cognitive load, or the mental effort required to process and retain information, is a critical factor in high-stakes environments where task demands often exceed working memory capacity, leading to performance declines and errors. However, most cognitive load research has relied on controlled, single-task paradigms, limiting its applicability to real-world multitasking situations. Addressing this gap, we used a mobile, two-channel functional near-infrared spectroscopy (fNIRS) device to measure cognitive load in a complex multitasking environment, simulating real-world cognitive demands. Thirty-one undergraduate participants engaged in single-task and multitask conditions to simulate real-world cognitive demands. Results showed that subjective cognitive load ratings were higher, performance scores were lower, and error rates increased in the multitask condition compared to the single-task condition. However, contrary to expectations, prefrontal cortex activation did not increase in the multitask condition, suggesting a \\\"cognitive disengagement\\\" effect, where the brain limits engagement to manage overload. This finding challenges the traditional one-to-one association between cognitive load and prefrontal activation, as seen in simpler validation studies. Our study highlights the value of mobile fNIRS for assessing cognitive load in ecologically valid settings and provides insights that could inform strategies for optimizing performance in high-stakes environments like aviation and healthcare.</div></div>\",\"PeriodicalId\":74277,\"journal\":{\"name\":\"Neuroimage. Reports\",\"volume\":\"4 4\",\"pages\":\"Article 100228\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-11-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neuroimage. Reports\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666956024000345\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Neuroscience\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuroimage. Reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666956024000345","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Neuroscience","Score":null,"Total":0}
Measuring cognitive load in multitasking using mobile fNIRS
Cognitive load, or the mental effort required to process and retain information, is a critical factor in high-stakes environments where task demands often exceed working memory capacity, leading to performance declines and errors. However, most cognitive load research has relied on controlled, single-task paradigms, limiting its applicability to real-world multitasking situations. Addressing this gap, we used a mobile, two-channel functional near-infrared spectroscopy (fNIRS) device to measure cognitive load in a complex multitasking environment, simulating real-world cognitive demands. Thirty-one undergraduate participants engaged in single-task and multitask conditions to simulate real-world cognitive demands. Results showed that subjective cognitive load ratings were higher, performance scores were lower, and error rates increased in the multitask condition compared to the single-task condition. However, contrary to expectations, prefrontal cortex activation did not increase in the multitask condition, suggesting a "cognitive disengagement" effect, where the brain limits engagement to manage overload. This finding challenges the traditional one-to-one association between cognitive load and prefrontal activation, as seen in simpler validation studies. Our study highlights the value of mobile fNIRS for assessing cognitive load in ecologically valid settings and provides insights that could inform strategies for optimizing performance in high-stakes environments like aviation and healthcare.