Multiscale co-simulation design pattern for neuroscience applications

Frontiers in Neuroinformatics, vol. 18, pp. 1156683

Abstract

Integration of information across heterogeneous sources creates added scientific value. Interoperability of data, tools and models is, however, difficult to accomplish across spatial and temporal scales. Here we introduce the toolbox Parallel Co-Simulation, which enables the interoperation of simulators operating at different scales. We provide a software science co-design pattern and illustrate its functioning along a neuroscience example, in which individual regions of interest are simulated on the cellular level allowing us to study detailed mechanisms, while the remaining network is efficiently simulated on the population level. A workflow is illustrated for the use case of The Virtual Brain and NEST, in which the CA1 region of the cellular-level hippocampus of the mouse is embedded into a full brain network involving micro and macro electrode recordings. This new tool allows integrating knowledge across scales in the same simulation framework and validating them against multiscale experiments, thereby largely widening the explanatory power of computational models.

Authors 7

1. Lionel Kusch corresponding

   Aix-Marseille Université · Institut de Neurosciences des Systèmes

   Affiliation as printed

   Institut de Neurosciences des Systèmes (INS), UMR1106, Aix-Marseille Université, Marseilles, France

2. Sandra Diaz-Pier

   Forschungszentrum Jülich · Jülich Aachen Research Alliance · Jülich Supercomputing Centre

   Affiliation as printed

   Simulation and Data Lab Neuroscience, Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation, JARA, Forschungszentrum Jülich GmbH, Jülich, Germany

3. Wouter Klijn

   Forschungszentrum Jülich · Jülich Aachen Research Alliance · Jülich Supercomputing Centre

   Affiliation as printed

   Simulation and Data Lab Neuroscience, Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation, JARA, Forschungszentrum Jülich GmbH, Jülich, Germany

4. Kim Sontheimer

   Forschungszentrum Jülich · Jülich Aachen Research Alliance · Jülich Supercomputing Centre

   Affiliation as printed

   Simulation and Data Lab Neuroscience, Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation, JARA, Forschungszentrum Jülich GmbH, Jülich, Germany

5. Christophe Bernard

   Aix-Marseille Université · Institut de Neurosciences des Systèmes

   Affiliation as printed

   Institut de Neurosciences des Systèmes (INS), UMR1106, Aix-Marseille Université, Marseilles, France

6. Abigail Morrison Aachen Computer Science 3 - Software Engineering

   Forschungszentrum Jülich · Jülich Aachen Research Alliance · Jülich Supercomputing Centre · RWTH Aachen University

   Affiliation as printed

   Computer Science 3 - Software Engineering, RWTH Aachen University, Aachen, Germany

   Forschungszentrum Jülich GmbH, IAS-6/INM-6, JARA, Jülich, Germany

   Simulation and Data Lab Neuroscience, Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation, JARA, Forschungszentrum Jülich GmbH, Jülich, Germany

7. Viktor Jirsa corresponding

   Aix-Marseille Université · Institut de Neurosciences des Systèmes

   Affiliation as printed

   Institut de Neurosciences des Systèmes (INS), UMR1106, Aix-Marseille Université, Marseilles, France