interneuron_rewiring.xz … Data/results related to the interneuron rewiring experiment connectivity_matrices/ … Input ConnectivityMatrix object circuits/ … New SONATA circuit with rewired connectome model_building/ … Results from model fitting structural_comparator/ … Results from structural comparison simulations/ … Results from simulation campaigns analysis/ … Analysis results from CortexETL simplified_connectomes.xz … Data/results related to the simplified connectomes experiment circuits/ … Readme pointing to separate datasets containing the five SONATA circuits with rewired (simplified) connectomes: 1st order - DOI: 10.5281/zenodo.12071006 2nd order - DOI: 10.5281/zenodo.12077952 3rd order - DOI: 10.5281/zenodo.12078722 4th order - DOI: 10.5281/zenodo.12080631 5th order - DOI: 10.5281/zenodo.12082177 model_building/ … Results from model fitting model_validation/ … Results from model order validation structural_comparator/ … Results from structural comparison missing_synapses/ … Results from missing synapses estimation simulations/ … Results from calibration simulation campaigns analysis/ … Calibration analysis results from CortexETL calibration/ … Calibration data frames as .parquet files (order0 = original) benchmarks.xz … Benchmark results related to strong/weak scaling behavior runtimes_strong_scaling.csv ... Runtimes from strong scaling tests runtimes_weak_scaling.csv ... Runtimes from weak scaling tests nodesets_weak_scaling.json ... Node set definitions used in weak scaling tests

This is an accompanying dataset to the article with the title "A connectome manipulation framework for the systematic and reproducible study of structure-function relationships through simulations" (DOI: 10.1162/netn_a_00429). It contains the resulting data of the manipulated SSCx network model, such as benchmarks, fitted stochastic models, manipulated connectomes, structural validations, as well as simulation data and analysis results. The corresponding repository with code, configuration files, and detailed instructions for reproducing the results in this dataset as well as generating the results figures in the accompanying article is available here: https://github.com/BlueBrain/sscx-connectome-manipulations The underlying Connectome-Manipulator software is available here: https://github.com/BlueBrain/connectome-manipulator Additional requirement: Original SSCx network model (DOI: 10.5281/zenodo.8026353) ℹ️ Disclaimer: Some results may have been produced with an older version of Connectome-Manipulator, so slight differences might be possible when re-running with the latest version. Update 25/09/2024 (v2): Added benchmark results for assessing strong and weak scaling behavior of connectome rewiring. Funding Funding provided by the Swiss government’s ETH Board to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL).

Uncompress: tar -xf .xz For rewired circuits under circuits/: Download and uncompress the original network model (DOI: 10.5281/zenodo.8026353) EITHER: Replace edges.h5 from the original SSCx network model by extracted edges.h5 file OR: Adjust the path references in circuit_config.json from the extracted circuit pointing to the folder location of the original SSCx network model For simulation data under simulations/: Adjust path references in simulation_config.json according to the respective circuit location For re-running simulations, follow simulation instruction of the original network model (DOI: 10.5281/zenodo.8026353)