3DSpineMFE
A MATLAB® toolbox that given a three-dimensional spine reconstruction computes a set of characteristic morphological measures that unequivocally determine the spine shape.
This Jupyter notebook contains Python code for creating openMINDS JSON-LD
metadata collections for TVB-ready data.
The code in this notebook was used to generate openMINDS metadata for
curation of TVB-on-EBRAINS datasets using openMINDS v1.
An overview over TVB-on-EBRAINS services is provided in the preprint https://arxiv.org/abs/2102.05888
The openMINDS schema standard specification is hosted in the repository https://github.com/HumanBrainProject/openMINDS
A MATLAB® toolbox that given a three-dimensional spine reconstruction computes a set of characteristic morphological measures that unequivocally determine the spine shape.
Arbor is a high-performance library for computational neuroscience simulations with multi-compartment, morphologically-detailed cells, from single cell models to very large networks. Arbor is written from the ground up with many-cpu and gpu architectures in mind, to help neuroscientists effectively use contemporary and future HPC systems to meet their simulation needs. Arbor supports NVIDIA and AMD GPUs as well as explicit vectorization on CPUs from Intel (AVX, AVX2 and AVX512) and ARM (Neon and SVE). When coupled with low memory overheads, this makes Arbor an order of magnitude faster than the most widely-used comparable simulation software. Arbor is open source and openly developed, and we use development practices such as unit testing, continuous integration, and validation.
BluePyEfe aims at easing the process of reading experimental recordings and extracting batches of electrical features from these recordings. To do so, it combines trace reading functions and features extraction functions from the eFel library. BluePyEfe outputs protocols and features files in the format used by BluePyOpt for neuron electrical model building.
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