Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, Maastricht 6229 EV, The Netherlands.
Research Department, Brain Innovation BV, Oxfordlaan 55, Maastricht 6229 EV, The Netherlands.
Philos Trans R Soc Lond B Biol Sci. 2024 Dec 2;379(1915):20230084. doi: 10.1098/rstb.2023.0084. Epub 2024 Oct 21.
During fMRI neurofeedback participants learn to self-regulate activity in relevant brain areas and networks based on ongoing feedback extracted from measured responses in those regions. This closed-loop approach has been successfully applied to reduce symptoms in mood disorders such as depression by showing participants a thermometer-like display indicating the strength of activity in emotion-related brain areas. The hitherto employed conventional neurofeedback is, however, 'blind' with respect to emotional content, i.e. patients instructed to engage in a specific positive emotion could drive the neurofeedback signal by engaging in a different (positive or negative) emotion. In this future perspective, we present a new form of neurofeedback that displays semantic information of emotions to the participant. Semantic information is extracted online using real-time representational similarity analysis of emotion-specific activity patterns. The extracted semantic information can be provided to participants in a two-dimensional semantic map depicting the current mental state as a point reflecting its distance to pre-measured emotional mental states (e.g. 'happy', 'content', 'sad', 'angry'). This new approach provides transparent feedback during self-regulation training, and it has the potential to enable more specific training effects for future therapeutic applications such as clinical interventions in mood disorders.This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.
在 fMRI 神经反馈中，参与者根据从这些区域的测量反应中提取的实时反馈，学习自我调节相关大脑区域和网络的活动。这种闭环方法已成功应用于通过向参与者显示类似于温度计的显示，指示与情绪相关的大脑区域的活动强度，来减轻情绪障碍（如抑郁症）的症状。然而，迄今为止所采用的常规神经反馈对于情绪内容是“盲目”的，即指示患者参与特定的积极情绪的指令可能会通过参与不同的（积极或消极）情绪来驱动神经反馈信号。在这个未来视角中，我们提出了一种新的神经反馈形式，它向参与者显示情绪的语义信息。语义信息使用实时情感特异性活动模式的代表性相似性分析在线提取。提取的语义信息可以以二维语义图的形式提供给参与者，该图将当前的心理状态表示为反映其与预先测量的情绪心理状态（例如“快乐”、“满足”、“悲伤”、“愤怒”）之间距离的点。这种新方法在自我调节训练期间提供了透明的反馈，并且有可能为未来的治疗应用（例如情绪障碍的临床干预）实现更具体的训练效果。本文是主题为“神经反馈：内源性神经调节的新领域和神经认知机制”的一部分。
