The Initiative for Systems Analysis in Neuroscience (ISyN) at the LIR is intended to provide a focal point for cross-scale systems theoretical and data-driven concepts in the neurosciences in Mainz and beyond.
For this purpose, three methodological pillars that penetrate the scales will be established: The first pillar is systems theory. The stability of dynamic functional states will be investigated at all levels of observation (genes, cells, networks, behaviour) as well as between the levels of observation. The second pillar consists of data-driven “machine learning” approaches. Using an appropriate algorithm, condition-determining variables are extracted from the flood of multidimensional data sets, which elude conventional hypothesis-driven approaches, also vertically through all levels. The third pillar represents the real-time intervention. Data-driven classifiers are used to reduce the complexity of data flows, which then allow for a real-time recording of the neural functional state. This in turn enables causal intervention, which has an effect on the neuronal system in the sense of a “closed loop”.
At ISyN, the individual expertise of the research groups of the Mainz area should be combined, and new concepts of method training and interaction of neuroscientists at all levels of education should be achieved.