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 the observation of large portions of the network simultaneously. The research group of Sonja Grün at the Institute for Computational and Systems Neuroscience (INM-6) focuses on the development of analysis strategies and tools that uncover concerted activity in electrophysiological signals (such as massively parallel spike trains and local field potential recordings) from the brain. This enables the exploration of the relevance of the observed activity for behavior and cognition. The research goal is to gain an understanding of the spatio-temporal scales at which the cortex operates, and to contribute to uncovering its function.
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- Analysis methods for higher-order correlation in massively parallel data
- Development of statististical tools for correlation analysis
- Research data management: metadata annotation, pipelines for data analysis
- Software for data analytics of high-dimensional population data (Elephant: https://github.com/NeuralEnsemble/elephant)
5 selected publications
- Dąbrowska P. A., Voges N., von Papen M., Ito J., Dahmen D., Riehle A., Brochier T., Grün S. (2021) On the Complexity of Resting State Spiking Activity in Monkey Motor Cortex.
Cerebral Cortex Communications: Volume 2, Issue 3, 2021, tgab033.
- Dahmen D., Grün S., Diesmann M., Helias M. (2019) Second type of criticality in the brain uncovers rich multiple-neuron dynamics Proceedings of the National Academy of Sciences of the United States of America 116 (26):13051-13060 DOI:10.1073/pnas.1818972116
- Brochier T., Zehl L., Hao Y., Duret M., Sprenger J., Denker M., Grün S., Riehle A. (2018) Massively parallel recordings in macaque motor cortex during an instructed delayed reach-to-grasp task. (Data publication) Scientific Data 5:180055 DOI:10.1038/sdata.2018.55. Data available at https://web.gin.g-node.org/INT/multielectrode_grasp
- Denker M., Roux S., Lindén H., Diesmann M., Riehle A., Grün S. (2011). The local field potential reflects surplus spike synchrony. Cerebral Cortex 21:2681–2695. DOI: 10.1093/cercor/bhr040.
- Riehle A., Grün S., Diesmann M., Aertsen A. (1997). Spike synchronization and rate modulation differentially involved in motor cortical function. Science 278:1950–1953. DOI: 10.1126/science.278.5345.1950.