Linling Li, Xueying Gui, Gan Huang, Li Zhang, Feng Wan, Xue Han, Jianhong Wang, Dong Ni, Zhen Liang, Zhiguo Zhang
{"title":"解码脑电图神经反馈引导的情绪调节认知重评训练","authors":"Linling Li, Xueying Gui, Gan Huang, Li Zhang, Feng Wan, Xue Han, Jianhong Wang, Dong Ni, Zhen Liang, Zhiguo Zhang","doi":"10.1007/s11571-024-10108-x","DOIUrl":null,"url":null,"abstract":"<p>Neurofeedback, when combined with cognitive reappraisal, offers promising potential for emotion regulation training. However, prior studies have predominantly relied on functional magnetic resonance imaging, which could impede its clinical feasibility. Furthermore, these studies have primarily focused on reducing negative emotions while overlooking the importance of enhancing positive emotions. In our current study, we developed a novel electroencephalogram (EEG) neurofeedback-guided cognitive reappraisal training protocol for emotion regulation. We recruited forty-two healthy subjects (20 females; 22.4 ± 2.2 years old) who were randomly assigned to either the neurofeedback group or the control group. We evaluated the efficacy of this newly proposed neurofeedback training approach in regulating emotions evoked by pictures with different valence levels (low positive and high negative). Initially, we trained an EEG-based emotion decoding model for each individual using offline data. During the training process, we calculated the subjects’ real-time self-regulation performance based on the decoded emotional states and fed it back to the subjects as feedback signals. Our results indicate that the proposed decoded EEG neurofeedback-guided cognitive reappraisal training protocol significantly enhanced emotion regulation performance for stimuli with low positive valence. Additionally, wavelet energy and differential entropy features in the high-frequency band played a crucial role in emotion classification and were associated with neural plasticity changes induced by emotion regulation. These findings validate the beneficial effects of the proposed EEG neurofeedback protocol and offer insights into the neural mechanisms underlying its training effects. This novel decoded neurofeedback training protocol presents a promising cost-effective and non-invasive treatment technique for emotion-related mental disorders.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"114 1","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Decoded EEG neurofeedback-guided cognitive reappraisal training for emotion regulation\",\"authors\":\"Linling Li, Xueying Gui, Gan Huang, Li Zhang, Feng Wan, Xue Han, Jianhong Wang, Dong Ni, Zhen Liang, Zhiguo Zhang\",\"doi\":\"10.1007/s11571-024-10108-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Neurofeedback, when combined with cognitive reappraisal, offers promising potential for emotion regulation training. However, prior studies have predominantly relied on functional magnetic resonance imaging, which could impede its clinical feasibility. Furthermore, these studies have primarily focused on reducing negative emotions while overlooking the importance of enhancing positive emotions. In our current study, we developed a novel electroencephalogram (EEG) neurofeedback-guided cognitive reappraisal training protocol for emotion regulation. We recruited forty-two healthy subjects (20 females; 22.4 ± 2.2 years old) who were randomly assigned to either the neurofeedback group or the control group. We evaluated the efficacy of this newly proposed neurofeedback training approach in regulating emotions evoked by pictures with different valence levels (low positive and high negative). Initially, we trained an EEG-based emotion decoding model for each individual using offline data. During the training process, we calculated the subjects’ real-time self-regulation performance based on the decoded emotional states and fed it back to the subjects as feedback signals. Our results indicate that the proposed decoded EEG neurofeedback-guided cognitive reappraisal training protocol significantly enhanced emotion regulation performance for stimuli with low positive valence. Additionally, wavelet energy and differential entropy features in the high-frequency band played a crucial role in emotion classification and were associated with neural plasticity changes induced by emotion regulation. These findings validate the beneficial effects of the proposed EEG neurofeedback protocol and offer insights into the neural mechanisms underlying its training effects. This novel decoded neurofeedback training protocol presents a promising cost-effective and non-invasive treatment technique for emotion-related mental disorders.</p>\",\"PeriodicalId\":10500,\"journal\":{\"name\":\"Cognitive Neurodynamics\",\"volume\":\"114 1\",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-05-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cognitive Neurodynamics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1007/s11571-024-10108-x\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Neurodynamics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s11571-024-10108-x","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Decoded EEG neurofeedback-guided cognitive reappraisal training for emotion regulation
Neurofeedback, when combined with cognitive reappraisal, offers promising potential for emotion regulation training. However, prior studies have predominantly relied on functional magnetic resonance imaging, which could impede its clinical feasibility. Furthermore, these studies have primarily focused on reducing negative emotions while overlooking the importance of enhancing positive emotions. In our current study, we developed a novel electroencephalogram (EEG) neurofeedback-guided cognitive reappraisal training protocol for emotion regulation. We recruited forty-two healthy subjects (20 females; 22.4 ± 2.2 years old) who were randomly assigned to either the neurofeedback group or the control group. We evaluated the efficacy of this newly proposed neurofeedback training approach in regulating emotions evoked by pictures with different valence levels (low positive and high negative). Initially, we trained an EEG-based emotion decoding model for each individual using offline data. During the training process, we calculated the subjects’ real-time self-regulation performance based on the decoded emotional states and fed it back to the subjects as feedback signals. Our results indicate that the proposed decoded EEG neurofeedback-guided cognitive reappraisal training protocol significantly enhanced emotion regulation performance for stimuli with low positive valence. Additionally, wavelet energy and differential entropy features in the high-frequency band played a crucial role in emotion classification and were associated with neural plasticity changes induced by emotion regulation. These findings validate the beneficial effects of the proposed EEG neurofeedback protocol and offer insights into the neural mechanisms underlying its training effects. This novel decoded neurofeedback training protocol presents a promising cost-effective and non-invasive treatment technique for emotion-related mental disorders.
期刊介绍:
Cognitive Neurodynamics provides a unique forum of communication and cooperation for scientists and engineers working in the field of cognitive neurodynamics, intelligent science and applications, bridging the gap between theory and application, without any preference for pure theoretical, experimental or computational models.
The emphasis is to publish original models of cognitive neurodynamics, novel computational theories and experimental results. In particular, intelligent science inspired by cognitive neuroscience and neurodynamics is also very welcome.
The scope of Cognitive Neurodynamics covers cognitive neuroscience, neural computation based on dynamics, computer science, intelligent science as well as their interdisciplinary applications in the natural and engineering sciences. Papers that are appropriate for non-specialist readers are encouraged.
1. There is no page limit for manuscripts submitted to Cognitive Neurodynamics. Research papers should clearly represent an important advance of especially broad interest to researchers and technologists in neuroscience, biophysics, BCI, neural computer and intelligent robotics.
2. Cognitive Neurodynamics also welcomes brief communications: short papers reporting results that are of genuinely broad interest but that for one reason and another do not make a sufficiently complete story to justify a full article publication. Brief Communications should consist of approximately four manuscript pages.
3. Cognitive Neurodynamics publishes review articles in which a specific field is reviewed through an exhaustive literature survey. There are no restrictions on the number of pages. Review articles are usually invited, but submitted reviews will also be considered.