Research at the Max Planck Institute for Brain Research focuses on the operation of brain circuits. It is carried out in two scientific departments (Schuman and Laurent) and in several research units. 

Circuit Function
Brain circuits can be considered at many different levels. These levels span the interests of the MPI for Brain Research. 

For example, the intracellular protein network present in synapses includes all essential features of circuits including connected elements, communication, regulation and feedback. In response to signals from other neurons in a circuit, synapses interpret their inputs and transform them into outputs.  Some inputs modify the intracellular network by modifying the local ionic and protein environment, resulting in a change in the synaptic response.

Neural networks are another fundamental unit of brain function: the brain computes (transforms) inputs (external, via senses, or internal, such as thoughts, memories etc) into adaptive outputs (motor behaviors, percepts etc), according to some rules, or families of rules, that most often emerge from its components and their interactions; interestingly, those rules can change with time, experience, or context. 

Our common goal is a mechanistic understanding of the components of these networks, of the structural and functional circuits which they form, of the computational rules which describe their operations, and ultimately, of their roles in driving perception and behavior. Our experimental focus is on all scales (in space and time) required to achieve this understanding. That is, some of our work focuses on networks of molecules in dendritic compartments, while other focuses on networks of interacting brain areas. This requires analyses at the molecular, cellular, multi-cellular, network and behavioral levels, with the full understanding that macroscopic phenomena (spatial patterns, dynamics) can be scale-dependent; thus, while essential, reductionist approaches are not always sufficient, emphasizing also the need for theory.

Interdisciplinarity
Neuroscience is an archetype of interdisciplinary science: a typical project may require a good level of understanding of electronics, molecular biology, optics, computer science and informatics, expertise with matrix algebra or image processing. Neuroscience is indeed a science of systems and increasingly defined not by its tools but by questions. Today already, a typical study in the neuroscience of circuits may combine approaches such optics and molecular biology, electrophysiological recordings, analysis of terabyte-sized datasets and large numerical simulations. Our institutes thus offers an interdisciplinary environment for graduate and postgraduate education, such that every student should become an expert in some areas and knowledgeable in most others. Our institute provides a training with both breadth and depth components, in an environment where interactions between labs, faculty, scientists are the norm and where science is generally multidisciplinary. In this regard, the positioning of our new institute building at the nexus of the natural sciences of the Goethe University, the presence of Frankfurt Institute for Advanced Studies and Max Planck Institute of Biophysics next door, and the already established research links between some of our labs with the Math Department and Center for Scientific Computing, as well as the neuroscience faculty at the medical school, place us in a rare position to offer this kind of interdisciplinary training.