Yu Pi, Jimin Yan, Charlotte Pscherer, Shudan Gao, Moritz Mückschel, Lorenza Colzato, Bernhard Hommel, Christian Beste
{"title":"个体间非周期性静息态脑电图活动可预测认知控制风格。","authors":"Yu Pi, Jimin Yan, Charlotte Pscherer, Shudan Gao, Moritz Mückschel, Lorenza Colzato, Bernhard Hommel, Christian Beste","doi":"10.1111/psyp.14576","DOIUrl":null,"url":null,"abstract":"<p><p>The ability to find the right balance between more persistent and more flexible cognitive-control styles is known as \"metacontrol.\" Recent findings suggest a relevance of aperiodic EEG activity and task conditions that are likely to elicit a specific metacontrol style. Here we investigated whether individual differences in aperiodic EEG activity obtained off-task (during resting state) predict individual cognitive-control styles under task conditions that pose different demands on metacontrol. We analyzed EEG resting-state data, task-EEG, and behavioral outcomes from a sample of N = 65 healthy participants performing a Go/Nogo task. We examined aperiodic activity as indicator of \"neural noise\" in the EEG power spectrum, and participants were assigned to a high-noise or low-noise group according to a median split of the exponents obtained for resting state. We found that off-task aperiodic exponents predicted different cognitive-control styles in Go and Nogo conditions: Overall, aperiodic exponents were higher (i.e., noise was lower) in the low-noise group, who however showed no difference between Go and Nogo trials, whereas the high-noise group exhibited significant noise reduction in the more persistence-heavy Nogo condition. This suggests that trait-like biases determine the default cognitive-control style, which however can be overwritten or compensated for under challenging task demands. We suggest that aperiodic activity in EEG signals represents valid indicators of highly dynamic arbitration between metacontrol styles, representing the brain's capability to reorganize itself and adapt its neural activity patterns to changing environmental conditions.</p>","PeriodicalId":20913,"journal":{"name":"Psychophysiology","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Interindividual aperiodic resting-state EEG activity predicts cognitive-control styles.\",\"authors\":\"Yu Pi, Jimin Yan, Charlotte Pscherer, Shudan Gao, Moritz Mückschel, Lorenza Colzato, Bernhard Hommel, Christian Beste\",\"doi\":\"10.1111/psyp.14576\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The ability to find the right balance between more persistent and more flexible cognitive-control styles is known as \\\"metacontrol.\\\" Recent findings suggest a relevance of aperiodic EEG activity and task conditions that are likely to elicit a specific metacontrol style. Here we investigated whether individual differences in aperiodic EEG activity obtained off-task (during resting state) predict individual cognitive-control styles under task conditions that pose different demands on metacontrol. We analyzed EEG resting-state data, task-EEG, and behavioral outcomes from a sample of N = 65 healthy participants performing a Go/Nogo task. We examined aperiodic activity as indicator of \\\"neural noise\\\" in the EEG power spectrum, and participants were assigned to a high-noise or low-noise group according to a median split of the exponents obtained for resting state. We found that off-task aperiodic exponents predicted different cognitive-control styles in Go and Nogo conditions: Overall, aperiodic exponents were higher (i.e., noise was lower) in the low-noise group, who however showed no difference between Go and Nogo trials, whereas the high-noise group exhibited significant noise reduction in the more persistence-heavy Nogo condition. This suggests that trait-like biases determine the default cognitive-control style, which however can be overwritten or compensated for under challenging task demands. We suggest that aperiodic activity in EEG signals represents valid indicators of highly dynamic arbitration between metacontrol styles, representing the brain's capability to reorganize itself and adapt its neural activity patterns to changing environmental conditions.</p>\",\"PeriodicalId\":20913,\"journal\":{\"name\":\"Psychophysiology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Psychophysiology\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1111/psyp.14576\",\"RegionNum\":2,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/3/31 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Psychophysiology","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1111/psyp.14576","RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/3/31 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
The ability to find the right balance between more persistent and more flexible cognitive-control styles is known as "metacontrol." Recent findings suggest a relevance of aperiodic EEG activity and task conditions that are likely to elicit a specific metacontrol style. Here we investigated whether individual differences in aperiodic EEG activity obtained off-task (during resting state) predict individual cognitive-control styles under task conditions that pose different demands on metacontrol. We analyzed EEG resting-state data, task-EEG, and behavioral outcomes from a sample of N = 65 healthy participants performing a Go/Nogo task. We examined aperiodic activity as indicator of "neural noise" in the EEG power spectrum, and participants were assigned to a high-noise or low-noise group according to a median split of the exponents obtained for resting state. We found that off-task aperiodic exponents predicted different cognitive-control styles in Go and Nogo conditions: Overall, aperiodic exponents were higher (i.e., noise was lower) in the low-noise group, who however showed no difference between Go and Nogo trials, whereas the high-noise group exhibited significant noise reduction in the more persistence-heavy Nogo condition. This suggests that trait-like biases determine the default cognitive-control style, which however can be overwritten or compensated for under challenging task demands. We suggest that aperiodic activity in EEG signals represents valid indicators of highly dynamic arbitration between metacontrol styles, representing the brain's capability to reorganize itself and adapt its neural activity patterns to changing environmental conditions.
期刊介绍:
Founded in 1964, Psychophysiology is the most established journal in the world specifically dedicated to the dissemination of psychophysiological science. The journal continues to play a key role in advancing human neuroscience in its many forms and methodologies (including central and peripheral measures), covering research on the interrelationships between the physiological and psychological aspects of brain and behavior. Typically, studies published in Psychophysiology include psychological independent variables and noninvasive physiological dependent variables (hemodynamic, optical, and electromagnetic brain imaging and/or peripheral measures such as respiratory sinus arrhythmia, electromyography, pupillography, and many others). The majority of studies published in the journal involve human participants, but work using animal models of such phenomena is occasionally published. Psychophysiology welcomes submissions on new theoretical, empirical, and methodological advances in: cognitive, affective, clinical and social neuroscience, psychopathology and psychiatry, health science and behavioral medicine, and biomedical engineering. The journal publishes theoretical papers, evaluative reviews of literature, empirical papers, and methodological papers, with submissions welcome from scientists in any fields mentioned above.