no code implementations • 16 Jun 2023 • Bruno Golosio, Jose Villamar, Gianmarco Tiddia, Elena Pastorelli, Jonas Stapmanns, Viviana Fanti, Pier Stanislao Paolucci, Abigail Morrison, Johanna Senk
Simulation speed matters for neuroscientific research: this includes not only how quickly the simulated model time of a large-scale spiking neuronal network progresses, but also how long it takes to instantiate the network model in computer memory.
no code implementations • 10 Dec 2022 • Agnes Korcsak-Gorzo, Charl Linssen, Jasper Albers, Stefan Dasbach, Renato Duarte, Susanne Kunkel, Abigail Morrison, Johanna Senk, Jonas Stapmanns, Tom Tetzlaff, Markus Diesmann, Sacha J. van Albada
This chapter sheds light on the synaptic organization of the brain from the perspective of computational neuroscience.
1 code implementation • 16 Dec 2021 • Jasper Albers, Jari Pronold, Anno Christopher Kurth, Stine Brekke Vennemo, Kaveh Haghighi Mood, Alexander Patronis, Dennis Terhorst, Jakob Jordan, Susanne Kunkel, Tom Tetzlaff, Markus Diesmann, Johanna Senk
Modern computational neuroscience strives to develop complex network models to explain dynamics and function of brains in health and disease.
no code implementations • 6 Oct 2021 • Johanna Senk, Birgit Kriener, Mikael Djurfeldt, Nicole Voges, Han-Jia Jiang, Lisa Schüttler, Gabriele Gramelsberger, Markus Diesmann, Hans E. Plesser, Sacha J. van Albada
We hope that the proposed standardizations will contribute to unambiguous descriptions and reproducible implementations of neuronal network connectivity in computational neuroscience.
no code implementations • 11 May 2021 • Stefan Dasbach, Tom Tetzlaff, Markus Diesmann, Johanna Senk
For networks with sufficiently heterogeneous in-degrees, the firing statistics can be preserved even if all synaptic weights are replaced by the mean of the weight distribution.
1 code implementation • 25 May 2018 • Johanna Senk, Espen Hagen, Sacha J. van Albada, Markus Diesmann
Based on model predictions of spiking activity and LFPs, we find that the upscaling procedure preserves the overall spiking statistics of the original model and reproduces asynchronous irregular spiking across populations and weak pairwise spike-train correlations in agreement with experimental data recorded in the sensory cortex.