P172 Scalable Computational Modeling of Neuron-Astrocyte Interactions in NEST
Marja-Leena Linne*1, Han-Jia Jiang2,3, Jugoslava Aćimović1, Tiina Manninen1, Iiro Ahokainen1, Jonas Stapmanns2,4, Mikko Lehtimäki1, Markus Diesmann2,4,5, Sacha J. van Albada2,3, Hans Ekkehard Plesser2,6,7
1Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
2Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany
3Institute of Zoology, Faculty of Mathematics and Natural Sciences, University of Cologne, Cologne, Germany
4Department of Physics, Faculty 1, RWTH Aachen University, Aachen, Germany
5Department of Psychiatry, Psychotherapy and Psychosomatics, School of Medicine, RWTH Aachen University, Aachen, Germany
6Department of Data Science, Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
7Käte Hamburger Kolleg: Cultures of Research (c:o/re), RWTH Aachen University, Aachen, Germany
*Email: marja-leena.linne@tuni.fi
Introduction
Astrocytes play a key role in modulating synaptic activity and network dynamics, yet large-scale models incorporating neuron-astrocyte interactions remain scarce [1]. This study introduces a novel NEST-based [2] simulation framework to model tripartite connectivity, where astrocytes interact with both presynaptic and postsynaptic neurons, extending traditional binary synaptic architectures. By integrating astrocytic calcium signaling and astrocyte-induced synaptic currents (SICs), the model enables dynamic modulation of neuronal activity, offering insights into the role of astrocytes in neural computation.
Methods
Our implementation integrates astrocytic calcium dynamics and SICs within a scalable, parameterized framework. The model allows controlled modulation of astrocytic influence, capturing transitions between asynchronous and synchronized neuronal states. Simulation scalability was assessed through strong and weak scaling benchmarks, leveraging parallel computing for network performance evaluation. Strong scaling benchmarks tested performance under fixed model size while increasing computing resources. Weak scaling benchmarks examined proportional upscaling of model size and computational power. These benchmarks evaluated network connection times, state propagation efficiency, and computational cost across different neuron-astrocyte configurations.
Results
Benchmark results show efficient parallel execution of the reference implementation [3]. Strong scaling benchmarks show that increasing computing resources reduces network connection and state propagation times. Weak scaling benchmarks reveal a moderate increase in communication time for processes like spike delivery and SIC delivery, yet overall performance remains robust against changes in model size and connectivity scheme. In this study, we validate the framework’s scalability to at least 1 million cells through benchmarking experiments, leveraging distributed computing for efficient simulation of large-scale neuron-glia networks.
Discussion
By providing a computationally accessible and reproducible tool for studying neuron-astrocyte interactions, this framework sets the stage for investigating glial contributions to synaptic modulation, network coordination, and their roles in neurological disorders. The integration of tripartite connectivity into NEST offers a versatile platform for modeling astrocytic regulation of neural circuits, advancing both fundamental neuroscience and applied computational modeling.
Acknowledgements
EU Horizon 2020 No. 945539 (Human Brain Project SGA3) to SJvA and M-LL. SGA3 Partnering Project (AstroNeuronNets) to JA and SJvA. EU Horizon Europe No. 101147319 (EBRAINS 2.0 Project) to SJvA and M-LL. HiRSE PS to SJvA. Research Council of Finland, Nos. 326494, 326495, 345280, and 355256, to TM, and 297893 and 318879 to M-LL. BMBF No. 01UK2104 (KHK c:o/re) to HEP.
References
[1]Manninen, T., Aćimović, J., Linne, M.-L. (2023). Analysis of Network Models with Neuron-Astrocyte Interactions. Neuroinformatics, 21(2), 375-406.https://doi.org/10.1007/s12021-023-09622-w
[2]Graber, S., Mitchell, J., Kurth, A.C., Terhorst, D., Skaar, J.E.W., Schöfmann, C.M., et al.(2024). NEST 3.8.https://zenodo.org/records/12624784
[3]Jiang, H.-J.,Aćimović, J., Manninen, T., Ahokainen, I., Stapmanns, J., Lehtimäki, M., et al.(2024). Modeling neuron-astrocyte interactions in neural networks using distributed simulation. bioRxiv.https://doi.org/10.1101/2024.11.11.622953
