BrainPy Examples
This repository contains examples of using BrainPy to implement various models about neurons, synapse, networks, etc. We welcome your implementation, which can be post through our github page.
If you run some codes failed, please tell us through github issue: https://github.com/PKU-NIP-Lab/BrainPyExamples/issues
If you found these examples are useful for your research, please kindly cite us.
If you want to add more examples, please fork our github: https://github.com/PKU-NIP-Lab/BrainPyExamples
Neuron Models
- (Izhikevich, 2003) Izhikevich Model
- (Brette, Romain. 2004) LIF phase locking
- (Gerstner, 2005): Adaptive Exponential Integrate-and-Fire model
- (Niebur, et. al, 2009) Generalized integrate-and-fire model
- (Jansen & Rit, 1995): Jansen-Rit Model
- (Teka, et. al, 2018): Fractional-order Izhikevich neuron model
- (Mondal, et. al, 2019): Fractional-order FitzHugh-Rinzel bursting neuron model
Continuous-attractor Network
Decision Making Model
E/I Balanced Network
Brain-inspired Computing
- Classify MNIST dataset by a fully connected LIF layer
- Convolutional SNN to Classify Fashion-MNIST
- (2022, NeurIPS): Online Training Through Time for Spiking Neural Networks
- (2019, Zenke, F.): SNN Surrogate Gradient Learning
- (2019, Zenke, F.): SNN Surrogate Gradient Learning to Classify Fashion-MNIST
- (2021, Raminmh): Liquid time-constant Networks
Reservoir Computing
Gap Junction Network
Oscillation and Synchronization
- (Wang & Buzsáki, 1996) Gamma Oscillation
- (Brunel & Hakim, 1999) Fast Global Oscillation
- (Diesmann, et, al., 1999) Synfire Chains
- (Li, et. al, 2017): Unified Thalamus Oscillation Model
- (Susin & Destexhe, 2021): Asynchronous Network
- (Susin & Destexhe, 2021): CHING Network for Generating Gamma Oscillation
- (Susin & Destexhe, 2021): ING Network for Generating Gamma Oscillation
- (Susin & Destexhe, 2021): PING Network for Generating Gamma Oscillation
Large-Scale Modeling
Recurrent Neural Network
- (Sussillo & Abbott, 2009) FORCE Learning
- Integrator RNN Model
- Train RNN to Solve Parametric Working Memory
- (Song, et al., 2016): Training excitatory-inhibitory recurrent network
- (Masse, et al., 2019): RNN with STP for Working Memory
- (Yang, 2020): Dynamical system analysis for RNN
- (Bellec, et. al, 2020): eprop for Evidence Accumulation Task
Working Memory Model
Dynamics Analysis
- [1D] Simple systems
- [2D] NaK model analysis
- [2D] Wilson-Cowan model
- [2D] Decision Making Model with
SlowPointFinder - [2D] Decision Making Model with Low-dimensional Analyzer
- [3D] Hindmarsh Rose Model
- Continuous-attractor Neural Network
- Gap junction-coupled FitzHugh-Nagumo Model
- (Yang, 2020): Dynamical system analysis for RNN
Classical Dynamical Systems
Unclassified Models