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Institute of Neuroscience and Medicine

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Statistical Neuroscience

Group Leader: Prof. Dr. Sonja Grün

Statistical Neuroscience teamTeam members from left to right: Dr. Michael Denker, Carlos Canova, Dr. Mehmet Süzen, Emanuele Lucrezia, Dr. Vahid Rostami, Prof. Dr. Günther Palm, Jeyathevy Sukiban, Paulina Dabrowska, Julia Sprenger, Dr. Junji Ito, Prof. Dr. Sonja Grün, Dr. Michael von Papen, Dr. Fred Barthelemy, Alper Yegenoglu, Alessandra Stella, Cristian Joana, Robin Gutzen, Pietro Quaglio, Dr. Nicole Voges
Copyright: Grafische Medien, Forschungszentrum Jülich

Development and application of methods to analyze multi-channel activity data (see our Analysis of Parallel Spike Trains webpage and the webpage highlighting our corresponding activities). A focus is the connection between neural data recorded on different temporal and spatial scales and the structure of correlations of spiking activity. The lab realizes the research goals in close cooperation with experimental groups (Scientific Cooperations)

Statistical NeuroscienceStatistical Neuroscience Lab

Higher brain functions are attributed to the cortex, a brain structure composed of a large number of neurons which are highly interconnected. A potential mechanism for neuronal information processing is the coordinated activity of populations of neurons. To approach this level of processing and to study the spatial and temporal scales of neuronal interaction requires to observe large portions of the network simultaneously. The group of Sonja Grün in the Institute for Computational and Systems Neuroscience focuses on the development of analysis strategies that detect the concerted activity in the brain and enable us to explore the relevance of the observed activity for behavior and cognition. A theoretical understanding of the interrelation of signals recorded on different temporal and spatial scales is a crucial point of focus in this group.

Our research goal is to gain an understanding of the relevant spatio-temporal scale(s) at which the cortex effectively interacts, and to contribute to the uncovering of its function. This requires:

  1. Combination of advanced experimental techniques with theoretical work on data analysis and modeling
  2. Development of statistical tools for data from awake behaving animals
  3. Data analysis to extract and condense the relevant characteristics of the system
  4. Interpretation of the system dynamics by construction of theoretical (biophysical and functional models
  5. Intense interaction with experimenters, who provide us with their experimental data and valuable insights from the experimental perspective.