Head senior physician
Head of the group "Systems neuroscience and mental health"
Specialist in psychiatry and psychotherapy
+49 6131 17-7336 (Management Secretariat)
+49 6131 17-477336Researchers
Dr. Sven Berberich
PhD students
Independent Fellow, P.I., Complex Systems Group (Boehringer Ingelheim Foundation)
Dr. Jonathan Reinwald
Lab Homepage: www. synapticwiring.com
Social stress is one of the main risk factors for depressive episodes. However, people react very differently to stressors. The underlying mechanisms that lead to individual resilience to social stress are not well understood. The subjective evaluation of rewards appears to play a decisive role in these processes.
These mechanisms can only be investigated in a social context and in longitudinal studies. We therefore developed a sensor-rich, non-invasive habitat to monitor individual social behavior and reinforcement learning in mouse colonies with high-dimensional measures and minimal experimenter interference, as originally proposed in the 3R principles. Causal interactions are be uncovered using computational modeling and deep learning tools. In particular, we aim to determine the influence of genetic polymorphisms and identify possible interventions that modulate the individual resilience.
We are investigating the fundamental question of how we remember others and assign positive or negative memories. We aim to reveal the mechanism by which the neurohormone oxytocin increases signal extraction in neuronal networks and thereby promotes the formation of memories of others. To answer these and related questions, we are using large-scale single-unit recordings in transgenic mice and a functional MRI during behavior to capture the dynamics of brain activity and discover new targets for the development of better therapies.
In order to make meaningful decisions, events in the environment must be assigned a value. The formation of such predictions and their outcome-based evaluation are impaired in severe mental disorders. We use high-dimensional network recordings, functional MRI, computational modeling, and genetics in mice to investigate how distributed but tightly interacting brain networks assign value to environmental stimuli through reinforcement learning. Using this approach, we recently identified a distributed reinforcing network loop that generates reward prediction and elucidated the underlying mechanisms. These findings feed into our general question of shaping behavior and stress resilience in complex social environments.
Winkelmeier L, Filosa C, Hartig R, Scheller M, Sack M, Reinwald JR, Becker R, Wolf D, Gerchen MF, Sartorius A, Meyer-Lindenberg A, Weber-Fahr W, Clemm von Hohenberg C*, Russo E*, Kelsch W* (2022) Striatal hub of dynamic and stabilized prediction coding in forebrain networks for olfactory reinforcement learning. Nature Communications 13:3305 *shared
Clemm von Hohenberg C, Weber-Fahr W, Lebhardt P, Ravi N, Braun U, Gass N, Becker R, Sack M, Cosa Linan A, Gerchen MF, Reinwald JR, Oettl LL, Meyer-Lindenberg A, Vollmayr B, Kelsch W*, Sartorius A* (2018). Lateral habenula perturbation reduces default-mode network connectivity in a rat model of depression. Transl. Psychiatry 8, 68, * shared