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Central Institute of Mental Health

The Central Institute of Mental Health (Zentralinstitut für Seelische Gesundheit) in Mannheim, Germany, is a leading psychiatric research institution affiliated with Heidelberg University. It specializes in research, treatment, and education related to mental health disorders, neuroscience, and psychosocial factors influencing mental well-being. The institute plays a crucial role in advancing psychiatric knowledge and developing innovative therapies through interdisciplinary collaboration and state-of-the-art facilities.

ZI Innengarten
Building of the Central Institute of Mental Health(ZI) in Mannheim ©ZI

Contributors


Gabriele Ende

Gabriele Ende is a researcher associated with the Central Institute of Mental Health (ZI) in Mannheim, Germany. Her work primarily focuses on neuroimaging and the application of magnetic resonance spectroscopy (MRS) in psychiatric and neurological disorders.

Andreas Meyer-Lindenberg

Andreas Meyer-Lindenberg is a distinguished psychiatrist and neuroscientist based in Germany, renowned for his groundbreaking research on the neurobiological underpinnings of psychiatric disorders. He serves as the Director of the Central Institute of Mental Health (ZI) in Mannheim and is a professor at the University of Heidelberg.

Projects


A05: Peripersonal space violations and social threat: daily-life psychological and neural mechanisms of environmental risk for reactive aggression

Peripersonal space, the representation of the space immediately surrounding the body, will be studied as an underlying factor for threat experience. Early-life stressors and daily-life stressors will be tested as factors influencing PPS processing and associated specific brain activation patterns.

A06: Decoding dynamic reciprocal neural mechanism underlying reactive aggression: Insights from fMRI and fNIRS hyperscanning

The project employs fMRI and functional near-infrared spectroscopy (fNIRS) hyperscanning techniques to explore how brain-to-brain synchrony and dynamic processes within peer dyads facilitate or inhibit aggressive behavior under diverse levels of provocation in adolescent patients and controls.

A08: The metabolic lung-brain axis in aggressive behavior in patients with AMD

Beta-hydroxy-butyrate (BHB), a ketone body, is negatively associated with aggressive behavior. BHB is a metabolite and an active signaling substrate involved in epigenetic regulation of e.g., neurotrophic factor genes in the brain.

B04: Investigating psychological and neural correlates of intimate partner violence

Focus on the neural correlates of characterizing cognitive control deficits during conflict situations. The project will investigate patients with varying levels of cognitive control along with their close partners (sibling or intimate partner) to identify the dynamics of self-regulation and co-regulation in provoked conflict situations in patients with control deficits.

B05: Predictors and (neuro-)biological correlates of (cyber-)bullying and victimization in real-life contexts

Focus on the investigation of a lack of cognitive control in bullies and victims that contributes to the risk of developing mental health problems. Therefore, the project will assess bullies and their victims in real-life and digital social interactions to investigate how aberrant cognitive and affective prefrontal control and sensitivity to peer rejection with accompanied alterations in autonomic arousal may increase externalizing and internalizing behavior.

C03: Distributed network control and interventions to frustrative non-reward and threat triggered aggressions

Investigate context-dependent aggression triggered by frustrative non-reward or acute social threats. Using newly developed approaches, multiple behavioral domains will be assessed in a semi-naturalistic, autonomous mouse habitat. Specifically, the habitat assesses the inter-individual dynamics of social interactions, aggressions, and hierarchy and the individual reward learning and impulsivity through different integrated modules.

Q02: Data management for computational modelling

Data management and training platform. A decentralized data management infrastructure will help focus on developmental and therapeutic longitudinal data, training all participating researchers in the necessary skills for future use.