Brain-electrical and cardiovascular indicators of emotion regulation as predictors of treatment (non)-response to CBT in internalizing disorders

情绪调节在精神障碍模型和心理治疗中起着核心作用。内隐自动情绪反应和情绪的外显控制调节的重新评估将在这个子项目的研究单位验证的心理生理指标进行评估，并检查其预测价值的（非）-响应认知行为治疗（CBT）的患者内化障碍。脑电图（EEG）变量包括晚正电位（LPP）的振幅和额叶α-波段功率的不对称性，以不同的情绪内容的图片。同步记录心电图测量值（ECG：心率和心率变异性，HRV）。所有测量将在以下条件下获得：（a）静息条件，（B）被动观察条件（情绪反应性），和（c）使用重新评价的指导情绪调节。较高的LPP幅度，额叶脑活动相对转移到右半球，以及对负价图片的较低HRV将被认为是情绪调节和适应能力降低的迹象，假设预测患者对CBT的反应更差。该子项目中评估的变量补充了本研究单元其他子项目（基于MRI：SP 5和SP 6，生态瞬时评估，EMA：SP 6，基于fMRI：SP3，SP 7和SP 8）从患者中收集的有关情绪调节的信息。情绪调节水平对CBT（无）反应的预测能力将直接通过测量指标进行检验，并在结构水平上通过衍生的潜变量进行检验。这将通过使用线性模型（回归）以及机器学习算法（SP2）来实现。心理生理测量水平（EEG和ECG）提供了一个相对容易和非侵入性的访问情绪调节的生物心理机制，因此，治疗变化的核心方面。因此，在本研究单位的其他子项目的背景下，该子项目承诺为基础研究转化为临床实践做出实质性贡献。

Emotion regulation has a central role in models of mental disorders and of their cure by psychotherapy. Implicit-automatic emotional reactivity and explicit-controlled regulation of emotions by reappraisal will be assessed in this subproject of the Research Unit by validated psychophysiological indicators, and examined for their predictive value for (non)-response to cognitive behavioral therapy (CBT) in patients with internalizing disorders. Electroencephalographic (EEG) variables include amplitudes of the late positive potential (LPP) and asymmetry of frontal alpha-band power to pictures with different emotional content. Synchronously, electrocardiographic measures (ECG: heart rate and heart rate variability, HRV) will be recorded. All measures will be obtained under (a) resting conditions, (b) passive viewing conditions (emotional reactivity), and (c) instructed emotion regulation using reappraisal. Higher LPP amplitudes, relative shifting of frontal brain activity to the right hemisphere, and lower HRV to negatively valenced pictures will be considered as signs of reduced emotion regulation and adaptive capacity, hypothesized to predict worse response of patients to CBT. The variables assessed in this subproject complement information regarding emotion regulation gathered from patients by other subprojects of this Research Unit (questionnaire-based: SP5 and SP6, ecological momentary assessments, EMA: SP6, fMRI-based: SP3, SP7 and SP8). The predictive power of the level of emotion regulation for (non)-response to CBT will be examined directly by measured indicators, and also at construct level by derived latent variables. This will be implemented by using linear models (regression), but also by machine-learning algorithms (SP2). The psychophysiological measurement level (EEG and ECG) provides a relatively easy and noninvasive access to biopsychological mechanisms of emotion regulation, and, consequently, to core aspects of therapeutic change. Therefore, this subproject promises, in the context of other subprojects of this Research Unit, a substantial contribution to translation of basic research into clinical practice.