Research Projects

A-BEAM, a clinical trial in patients with alcohol use disorders, specifically focuses on impairments in alcohol-specific inhibition—the ability to suppress automatic responses to alcohol-related cues—and the role of individual brain plasticity.

The project primarily develops an app-based, scalable version of alcohol-specific inhibition training and evaluates its effectiveness using an adaptive Bayesian design. In an embedded neurophysiological study, A-BEAM investigates whether the training induces neurophysiological changes. This sub-study also explores whether neurophysiological markers of control processes can indicate treatment progress and predict relapse risk, potentially serving as biomarkers. Finally, the project examines how individual differences in brain plasticity, estimated through changes in visually evoked potentials, influence treatment outcomes.

The primary aim of WAIT-AYA is to evaluate a newly developed app-based version of an alcohol-specific or cocaine-specific inhibition training (IT). The project WAIT-AYA administers this substance-specific inhibition training for the first time as an internet-based intervention, thereby increasing its availability and flexible implementation. This double-blind, multicentric clinical pilot RCT I) tests the acceptability, usability, and feasibility of iAlc-IT, II) gathers preliminary insight about its effects on drinking behavior, and III) examines its neurophysiological effects.

To this end, young patients in ambulatory treatment or counseling for alcohol or cocaine use disorder are recruited and randomly assigned to receive either substance-specific-IT or an internet-based active control condition (iCON) in addition to treatment at usual. The project seeks to inform a future implementation of this training as a blended treatment component into routine care for adolescents and young adults with substance use disorders as well as to guide the development of future full-scale RCTs on that subject. Furthermore, the neurophysiological knowledge gathered provides preliminary insights into working mechanisms, which adds to the scientific anchorage of this intervention.

INTRA investigates the effects of a computerized inhibition training in currently abstinent patients with alcohol use disorder. It examines effects on subjective, behavioral, experimental and neurophysiological level.

Predicting post-treatment symptom trajectories is crucial in order to inform decisions concerning type, intensity, and duration of treatment. A large body of research shows associations between predictors and post-treatment outcomes in samples with alcohol use disorder (AUD), but these models do not provide adequate predictions for an individual patient.

Recently, machine learning algorithms have been used to establish predictive models in substance use disorder research. MLAUD aims to expand this research and to investigate how machine learning algorithms can be used to improve individual, post-treatment outcome predictions for patients with AUD.

EMOPRO traces the neurophysiological correlates of emotional processing before and after a psychotherapeutic intervention targeting the processing of interpersonal pain.

NECAAD investigates neurophysiological correlates of inhibition and cue reactivity with multi-channel EEG and fMRI in patients with alcohol addiction.

The concept of motivational incongruence, as incorporated in Grawes consistency theory, refers to the fact that the experiences we make do not always match our needs and motives. The amount of motivational inconsistency is highly linked to psychological wellbeing and psychopathological symptoms. MINK traces the neurophysiological correlates of this important transdiagnostical concept with multi-channel EEG.