Acknowledgments

This project has been partially funded through the BMBF Grant 01IS19077A (Juelich).

The project is funded by the Helmholtz Association Initiative and Networking Fund under project number ZT-I-0003.

This project has received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under Specific Grant Agreement No. 720270 (Human Brain Project SGA1).

This project has received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under Specific Grant Agreement No. 785907 (Human Brain Project SGA2).

This work was performed as part of the Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE).

This project has received funding from the German Research Foundation (DFG; grant DI 1721/3-1 [KFO219-TP9]).

This work was partly supported by the Exploratory Research Space seed funds MSCALE and G:(DE-82)ZUK2-SF-CLS002 (partly financed by Hans Herrmann Voss Stiftung) of the RWTH university.

This project has been partially funded through the Helmholtz young investigator’s group VH-NG-1028 “Theory of multi-scale neuronal networks”.

This project has been partially funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 368482240/GRK2416.

This project has received funding from the Helmholtz Association through the Helmholtz Portfolio Theme “Supercomputing and Modeling for the Human Brain.

This project has been partially funded by the Deutsche Forschungsgemeinschaft Grant DE 2175/2-1 Priority Program (SPP 1665).

This project has been partially funded by the Deutsche Forschungsgemeinschaft Grant GR 1753/4-2 Priority Program (SPP 1665).

This project has been partially funded through the Priority Program (SPP 2041 ″Computational Connectomics”) of the Deutsche Forschungsgemeinschaft [S.J. van Albada: AL 2041/1-1].