Progressive modulation of resting-state brain activity during neurofeedback of positive-social emotion regulation networks.
Progressive modulation of resting-state brain activity during neurofeedback of positive-social emotion regulation networks.
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DOI：
10.1038/s41598-021-02079-4
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发表时间：
2021-12-03
影响因子：
4.6
通讯作者：
Koush Y
中科院分区：
文献类型：
--
作者：
Krylova M;Skouras S;Razi A;Nicholson AA;Karner A;Steyrl D;Boukrina O;Rees G;Scharnowski F;Koush Y
神经反馈可以对涉及特定适应不良行为的大脑回路进行自我调节，从而导致大脑活动和连接性的持续变化。积极的社会情绪调节神经反馈可以增强情绪调节能力，这对于减轻各种精神疾病的严重程度至关重要。训练背内侧前额叶皮层 (dmPFC)，在积极的社会情绪调节过程中对双侧杏仁核施加自上而下的影响，逐步（线性）调节训练网络内的连接性并诱发积极情绪。然而，人们对休息期间与神经反馈训练交织的过程仍然知之甚少。我们假设，积极社会情绪调节神经反馈训练课程结束时的短暂休息会显示情绪调节和神经反馈学习网络的变化。我们使用基于模型和数据驱动的互补方法来评估静息态连接与训练课程结束时神经反馈变化的关系。在实验组中，我们发现进行性 dmPFC 自我抑制较低，并且参与情绪调节、神经反馈学习、视觉空间处理和记忆的网络连接性增加。我们的研究结果强调了神经反馈与静息态大脑活动以及目标网络内外的连接变化之间的大规模协同作用。这项工作有助于我们理解培训后的伴随学习机制，并促进高效神经反馈培训的发展。
Neurofeedback allows for the self-regulation of brain circuits implicated in specific maladaptive behaviors, leading to persistent changes in brain activity and connectivity. Positive-social emotion regulation neurofeedback enhances emotion regulation capabilities, which is critical for reducing the severity of various psychiatric disorders. Training dorsomedial prefrontal cortex (dmPFC) to exert a top-down influence on bilateral amygdala during positive-social emotion regulation progressively (linearly) modulates connectivity within the trained network and induces positive mood. However, the processes during rest that interleave the neurofeedback training remain poorly understood. We hypothesized that short resting periods at the end of training sessions of positive-social emotion regulation neurofeedback would show alterations within emotion regulation and neurofeedback learning networks. We used complementary model-based and data-driven approaches to assess how resting-state connectivity relates to neurofeedback changes at the end of training sessions. In the experimental group, we found lower progressive dmPFC self-inhibition and an increase of connectivity in networks engaged in emotion regulation, neurofeedback learning, visuospatial processing, and memory. Our findings highlight a large-scale synergy between neurofeedback and resting-state brain activity and connectivity changes within the target network and beyond. This work contributes to our understanding of concomitant learning mechanisms post training and facilitates development of efficient neurofeedback training.
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