Li Linling, Gui Xueying, Huang Gan, Zhang Li, Wan Feng, Han Xue, Wang Jianhong, Ni Dong, Liang Zhen, Zhang Zhiguo
School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, 518060 China.
International Health Science Innovation Center, Medical School, Shenzhen University, Shenzhen, 518060 China.
Cogn Neurodyn. 2024 Oct;18(5):2659-2673. doi: 10.1007/s11571-024-10108-x. Epub 2024 May 3.
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.
神经反馈与认知重评相结合时，在情绪调节训练方面具有广阔的潜力。然而，先前的研究主要依赖功能磁共振成像，这可能会阻碍其临床可行性。此外，这些研究主要侧重于减少负面情绪，而忽视了增强正面情绪的重要性。在我们当前的研究中，我们开发了一种用于情绪调节的新型脑电图（EEG）神经反馈引导的认知重评训练方案。我们招募了42名健康受试者（20名女性；22.4±2.2岁），他们被随机分配到神经反馈组或对照组。我们评估了这种新提出的神经反馈训练方法在调节由不同效价水平（低正性和高负性）图片引发的情绪方面的效果。最初，我们使用离线数据为每个个体训练了一个基于脑电图的情绪解码模型。在训练过程中，我们根据解码的情绪状态计算受试者的实时自我调节表现，并将其作为反馈信号反馈给受试者。我们的结果表明，所提出的解码脑电图神经反馈引导的认知重评训练方案显著提高了对低正性效价刺激的情绪调节表现。此外，高频带中的小波能量和微分熵特征在情绪分类中起着关键作用，并且与情绪调节引起的神经可塑性变化相关。这些发现验证了所提出的脑电图神经反馈方案的有益效果，并为其训练效果背后的神经机制提供了见解。这种新型的解码神经反馈训练方案为与情绪相关的精神障碍提供了一种有前景的经济有效且非侵入性的治疗技术。
