Software for computational neuroscience

Upstream packages

The following tools are among the software currently tested in NeuroFedora and can be installed directly from upstream forges (e.g. PyPi). You can see the tests results here.

Python packages

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Software Summary pip (PyPi) Notes

Software	Summary	pip (PyPi)	Notes
bluepyopt	Blue Brain Python Optimisation Library (bluepyopt).	`bluepyopt`
lfpy	A module for modeling extracellular potentials of multicompartment neuron models built on NEURON.	`lfpy`
libneuroml	A Python library for working with NeuroML descriptions of neuronal models.	`libneuroml`
nest-neat		`nest-neat`	Does not currently install on Python 3.13. https://github.com/nest/NEAT/issues/183
netpyne	A Python package to develop, simulate and analyse biological neuronal networks in NEURON.	`netpyne`
neurom	NeuroM: a light-weight neuron morphology analysis package.	`neurom`
NEURON	Empirically-based simulator for modeling neurons and networks of neurons.	`NEURON`
neurotune	A Python library for optimising neuronal models.	`neurotune`
pylems	A Python library for working with the Low Entropy Model Specification language (LEMS).	`pylems`
pyneuroml	Python utilities for NeuroML.	`pyneuroml`
pynn	A Python package for simulator-independent specification of neuronal network models.	`pynn`
sciunit	A test-driven framework for formally validating scientific models against data.	`sciunit`

bluepyopt

Blue Brain Python Optimisation Library (bluepyopt).

bluepyopt

lfpy

A module for modeling extracellular potentials of multicompartment neuron models built on NEURON.

lfpy

libneuroml

A Python library for working with NeuroML descriptions of neuronal models.

libneuroml

nest-neat

nest-neat

Does not currently install on Python 3.13. https://github.com/nest/NEAT/issues/183