Data Analytics in Neuroscience

Many neuroscience laboratories are faced with ever-increasing amounts of experimental data. Processing these large datasets with conventional analysis tools is often inefficient. To address these challenges efficiently, ZNZ researchers can rely on excellent cluster computing infrastructures available at ETH and University of Zurich. Furthermore, state-of-the-art scientific computing support is provided by the relevant support units at ETH and UZH.

The last decade has seen massive increases in the amounts and complexity of experimental data produced in many areas of neuroscience. Examples include electron microscopy (“connectomics”), fluorescence microscopy, next-generation sequencing or high-speed video recordings. Managing and processing these large datasets has become a major challenge for neuroscientists. Conventional analysis approaches, based on local workstations, frequently do not scale well to larger datasets, so that data analysis becomes both time and cost inefficient. In some cases, data analysis can even become the bottleneck in the entire scientific workflow. Fortunately, ZNZ researchers at ETH and the University of Zürich have access to world-class scientific computing infrastructures that allow highly scalable processing of large to massive datasets. At ETH, the Scientific IT Services (SIS) group maintains the Euler High Performance Computing cluster with more than 34’000 CPU cores. In addition, SIS is setting up a dedicated ‘Big data’ cluster with 3.5 PB of usable storage for processing of very large biomedical datasets. At the University of Zürich, the ScienceCloud infrastructure with over 12’000 CPU cores and more than 5 PB of available storage, is already serving a large user base from more than 30 different institutes. Furthermore, state-of-the-art support for using the scientific computing infrastructure efficiently is available from dedicated support teams at ETH and UZH. ZNZ researchers at all levels (Students, Postdocs, PIs) are invited to contact the relevant support teams to discuss how their specific analysis requirements can be met with the available computing infrastructure.

For more information, contact Dr. Henry Lütcke, Scientific IT Services, ETH Zurich or


Image: The ETH Euler cluster currently offers more than 34’000 CPU cores for scientific computing. It is located in the Swiss National Supercomputing Center (CSCS) in Lugano. 

Sejnowski, T. J., Churchland, P. S. & Movshon, J. A. Putting big data to good use in neuroscience. Nat Neurosci 17, 1440–1441 (2014) pdf