Teams
The SimLab Neuroscience is organised into five teams:
Table of Contents
Large Scale Simulation and Neuromorphic Systems
As neuronal simulations become ever more complex, innovations are required in software and hardware. We are key contributors to the neural network simulators NEST and Arbor. Execution performance and maintainability are our primary concerns. Simultaneously, we enhance usability by eliciting user requirements and developing domain specific languages to express neural models, for example the NEST modelling language NESTML.
On the hardware side, we are investigating novel neuromorphic architectures and are a partner in the Jülich Neuromorphic Computing Alliance (JUNCA). Modular hardware approaches combining traditional and non-von Neumann architectures promise accelerated simulations of neural networks and new computational paradigms. Examples of such systems investigated by our team include the SpiNNaker neuromorphic system and novel FPGA System-On-Chip-based architectures.
https://apt.cs.manchester.ac.uk/projects/SpiNNaker/
https://www.fz-juelich.de/en/aca
Team members: Guido Trensch (lead), Pooja Babu, Charl Linssen, Dr.-Ing. Georgia Psychou
Research and Software:
- Neuromorphic Architectures for Accelerated Neural Network Simulations
- Validation of Spiking Neural Network Simulations
- NEST Simulator
- NESTML
- SpiNNaker Support for the neural simulator NEST
Machine Learning and Data Analytics for Neuroimaging
The team focuses on the development and optimisation of image analysis methods and comprehensive neuroimaging pipelines dedicated to high-performance computing (HPC) systems.
The amount of neuroimaging data to be analysed has increased over the years, pushing traditional workflows to their limits. These workflows include classical image processing methods, complex modelling steps such as diffusion tensor reconstruction, and modern machine learning techniques such as deep learning models. To account for this development, the team develops and optimizes image analysis methods and pipelines for neuroimaging, focusing on scaling these processes to high-performance computing (HPC) systems to accommodate the growing volume of neuroimaging data. The key methods involve machine learning for MRI-based microstructural imaging, diffusion MRI, and segmentation across various modalities, including diffusion MRI and fMRI. Additionally, the team develops machine learning tools designed for HPC systems, including frameworks such as Heat and AdjointMPI.
Team members: Dr. Kai Krajsek (lead), Rajalekshmi Deepu, Andreas Müller, Matteo Westerwinter
Research and Software:
- Data analytics for high-throughput image-based cohort phenotyping
- Analysis of sub-millimetre resolution fMRI for laminar dissection of the brain function
- VIGAN: Visualization-guided Interactive Graph Analysis
- Deep Learning for segmentation of 3D-PLI images
- PLI-workflow
- EBRAINS software distribution on HPC
Meta-optimization for bio-inspired networks
Our team develops high-throughput software tools and innovative methods for the optimization of neuroscience simulations with particular focus on high-dimensional parameter spaces, biologically inspired meta-learning, and dynamic connectivity generation. Our contributions to simulation frameworks such as NEST and TVB mainly consist of the implementation of methods to study plasticity and the relationships between structure and function in the brain.
We also provide high-level support to the user community in the efficient usage of HPC infrastructure for simulation and data analysis, with special emphasis on research at the whole brain scale. Moreover, we contribute to the design and implementation of standards to describe data and models in neuroscience workflows, improving integration and reproducibility.
Team members: Dr. Sandra Diaz (lead), Dr. Thorsten Hater, Dr. Han Lu , Drs. Ir. Michiel van der Vlag, Sinovia Fotiadou-Kotsopoulou, Hanna Mohr
Associate members: Daniel Todt (RWTH Aachen) and Cristian Jimenez-Romero (Cergy University Paris)
Research and Software:
- Learning to Learn (L2L) on HPC
- Structural Plasticity
- Arbor - multi-compartment models of neural network
- High Performance Computing for the Virtual Brain
- Multiscale co-simulation
- Visual Connectivity Generation
- Interactive steering and visualization
- EBRAINS and EBRAINS 2.0 Project
- Virtual Brain Twin
- eBrain-Health
Multiscale Simulation and Design
Our team contributes HPC expertise to brain simulation software at the interfaces between scales: whole brain, point neuron, and morphologically detailed scales. We design and integrate tools for the deployment of complex co-simulation workflows combining multiple simulators into connected systems, exemplified in the Virtual Brain Twin project.
The team hosts the EBRAINS Science Support Team where we promote knowledge exchange between science, technology, and other stakeholders. Using structured requirements analysis methods, the team gathers feedback from users about the functionality and usability of different tools that are integrated into EBRAINS to ensure that the infrastructure remains competitive in a rapidly evolving research landscape.
We further support Sano Center building relationships with scientific leaders, infrastructure designers, and developers. We collaborate on Sano projects, focusing on advancing computational personalized medicine through interdisciplinary cooperation in IT and technology.
Team members: Wouter Klijn (lead), Dr. Marissa Diaz Pier, Dr. Krishna Kant Singh, Jithu Murugan, Ekaterina Zossimova
Research and Software:
- Modular Science – co-simulator framework
- Visual Connectivity Generation
- Sano
- EBRAINS and EBRAINS 2.0 Project
- Virtual Brain Twin
Coordination, Communication and Project Management
Our team supports the Simulation and Data Lab Neuroscience (SDLN) in the coordination, management, and dissemination of its projects, networks, and alliances.
For more than ten years we have been coordinating the co-design and provisioning of computing and storage infrastructure for EBRAINS, a major European research infrastructure (RI) connecting Neuroscience with High-Performance Computing (HPC) and a legacy of the Human Brain Project. On behalf of Forschungszentrum Jülich as the lead partner of EBRAINS Germany, the National Node of the distributed EBRAINS RI, we facilitate the coordination and collaboration between the member institutions across Germany. Additionally, we support the SDLN in its role as the Bernstein Facility for High-Performance Simulation and Data Analysis, collaborating closely with the the Bernstein Network Computational Neuroscience on dissemination and training at the intersection of HPC and Neuroscience.
Team members: Dr. Boris Orth (lead), Dr. Maren Frings, Steffen Graber, Dr. Olivera Korculanin
Projects, networks and alliances: