Our research deals with theory-driven modeling of basic neurobiological mechanisms of action control including their disorders. Our goal is to transfer findings from basic research into innovative treatments using model-based, translational approaches.
To this end, we are researching prediction models to recommend people the most promising therapy based on individual factors, such as the functional architecture of their brain. The goal of individualized prediction is to substantially improve future clinical decision-making. To understand motivated behavior, my group uses functional imaging in combination with high-resolution behavioral, physiological, and psychological assessments. We develop statistical and mathematical models that combine a wide range of data levels and sources in a theory-led and theory-building manner to decode central mechanisms of behavioral control.
One focus of our work is the interaction between the body’s own signals and the control of goal-directed behavior in the brain. Thus, we investigate the influence of different homeostatic stressors on reward-related behavior and learning in healthy individuals and across different disorders. The vagus nerve plays an important role in relaying bodily signals and we can acutely emulate such signals via non-invasive stimulation to modulate behavior in accordance with feedback as it would be provided by bodily signals. Therefore, we can investigate how the body’s own signals can be used to tune reward function and guide behavior.
Disorders in the communication between the brain and the body are associated with a number of mental illnesses such as depression, eating disorders, but also metabolic disorders. In several pioneering publications, we have demonstrated the considerable clinical potential of combining theory-driven and data-driven approaches with non-invasive neuromodulation techniques in recent years.
Disorders of motivation and reward processing are central features of a wide range of mental disorders. Since these changes in motivation are often accompanied by changes in energy metabolism and in mood, understanding the intriguing mechanistic links may result in new opportunities for the rapid treatment of symptoms that otherwise only respond insufficiently or with a substantial delay to conventional methods. To achieve this overarching translational goal, we define three content-related research domains that are intended to channel our scientific work toward the translational goals (see projects).
Energy Metabolism & Interoception
The first research domain deals with energy metabolism and the perception of the body’s own signals (i.e., interoception). Since a fundamental motive is to ensure long-term energy homeostasis, the body’s metabolic state plays an important role in controlling goal-directed behavior. Disturbances in energy metabolism and interoception do not only occur in metabolic disorders but also characterize numerous mental disorders such as depression and eating disorders.
In our work, we focus on the interface between the digestive tract and the brain, including signal transmission via hormone release and the vagus nerve. To this end, we draw on our well-established knowledge of the adaptive regulation of reward processing by internal signals, which is reflected in several current projects funded by the DFG. Our goal is to develop innovative treatment options, for example, by targeting the stomach-brain axis. We anticipate a better understanding of the metabolic processes in the context of mental disorders will also contribute to a holistic understanding of their etiology.
The second research domain deals with non-invasive methods for changing the function of the brain in a hypothesis-driven manner. We focus on pharmacological interventions and non-invasive brain stimulation (i.e., vagus nerve stimulation), which are intended to improve motivation and energy metabolism.
The combination of neuromodulation techniques with other domains of our research provides a rather unique perspective on the regulation of motivation. We are one of the pioneering groups in the field of non-invasive vagus nerve stimulation for acute modulation of motivational symptoms in people. Furthermore, our expertise in the field of computational psychiatry helps us advance neuromodulation techniques toward personalized medicine, where we have obtained encouraging evidence supporting the potential of individualized prediction of acute behavioral effects via stimulation-induced changes in the brain. Accordingly, our goal is to develop techniques that help us reap the therapeutic benefits of neuromodulation methods quickly and robustly.
Our experimenter Monja Neuser is placing the electrode for non-invasive stimulation of the vagus nerve.
Computational Psychiatry & Neuroimaging
The third research domain deals with the statistical and mathematical modeling of behavioral and neuroimaging data. Computational Psychiatry is a comparatively young field of research that can be roughly divided into theory-guided and data-driven methods.
In our group, theory-driven methods include, for example, reinforcement learning, hierarchical (Bayesian) statistical models, and simulations of time series and their interactions. Data-driven methods include machine learning and dimensionality reduction techniques (t-SNE, UMAP, hierarchical clustering). Our goal is to integrate both theory-guided and data-driven approaches to better address clinically-relevant questions with quantitative methods. We also use model-based neuroimaging, where individual decision parameters are used to mechanistically examine value-related calculations in the brain. It further includes innovative tools for biomarker research, such as our toolbox fmreli, which simplifies the calculation of the reliability of individual activation maps.