# NeuralIntegrator: Spiking neural network and synaptic plasticity in DifferentialEquations.jl
**URL:** https://discourse.julialang.org/t/neuralintegrator-spiking-neural-network-and-synaptic-plasticity-in-differentialequations-jl/130295
**Category:** Modelling & Simulations
**Tags:** package, biology, neural-network, differentialequation, simulations
**Created:** [June 28, 2025, 10:49am UTC](https://discourse.julialang.org/t/neuralintegrator-spiking-neural-network-and-synaptic-plasticity-in-differentialequations-jl/130295 "2025-06-28T10:49:34Z")
**Posts on this page:** 2
**Page:** 1
### Author:  [@flmuk](https://discourse.julialang.org/u/flmuk)
#### Post date: [June 28, 2025, 10:49am UTC](https://discourse.julialang.org/t/neuralintegrator-spiking-neural-network-and-synaptic-plasticity-in-differentialequations-jl/130295/1 "2025-06-28T10:49:34Z")
## NeuralIntegrator: simulating spiking neural networks with discontinuities
I work in the field of computational neuroscience and model spiking neural networks (SNNs) with different synaptic plasticity rules, i.e. rules on how weights between neurons change with the neurons’ activity:
> **[GitHub - flmuk/NeuralIntegrator](https://github.com/flmuk/NeuralIntegrator)**
>
> Contribute to flmuk/NeuralIntegrator development by creating an account on GitHub.
I implemented a small repo that simulates an SNN
with synaptic plasticity to produce clusters of strongly connected neurons, based on DifferentialEquations.jl, inspired by
[Manz, P., & Memmesheimer, R.-M. (2023). Purely STDP-based assembly dynamics: Stability, learning, overlaps, drift and aging. PLOS Computational Biology, 19(4), e1011006](https://doi.org/10.1371/journal.pcbi.1011006),
a paper on the spontaneous formation of neuronal assemblies through synaptic plasticity.
There is a python package [Brian2](https://brian2.readthedocs.io/en/stable/) that offers a rich set of tools to implement such networks (also see e.g. [NEST](https://www.nest-simulator.org) for an alternative).
However, I haven’t seen a similar tool in Julia yet, and while Brian2 is fantastic for prototyping, it brings many C++ dependencies under the hood and can be difficult to debug.
The idea of the project is to keep it lightweight and low-level (for now), s.t. it is easy to adapt to other needs. It is not optimized for performance, and there is still much room for improvement.
I hope this is helpful to other people in the field or generally for those who model systems of ODEs with discontinuities.
Feedback and improvements are very welcome!
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### Author:  [@afishy](https://discourse.julialang.org/u/afishy)
#### Post date: [July 1, 2025, 8:09am UTC](https://discourse.julialang.org/t/neuralintegrator-spiking-neural-network-and-synaptic-plasticity-in-differentialequations-jl/130295/2 "2025-07-01T08:09:13Z")
That’s awesome! Check out [Neuroblox](https://neuroblox.github.io/NeurobloxDocsHost/dev/), they’re working on a pretty big brain network simulation environment, also based off the Julia DiffEq ecosystem.
Also, not very often updated, but [Conductor.jl](https://github.com/wsphillips/Conductor.jl) looks pretty cool