Project Details
Projekt
Brain-electrical and cardiovascular indicators of emotion regulation as predictors of treatment (non)-response to CBT in internalizing disorders
Applicant
Professor Dr. Norbert Kathmann
Subject Area
Personality Psychology, Clinical and Medical Psychology, Methodology
Biological Psychology and Cognitive Neuroscience
Biological Psychology and Cognitive Neuroscience
Term
since 2022
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 442075332
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.
DFG Programme
Research Units
