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.
Ask questions: https://github.com/PKU-NIP-Lab/BrainPyExamples/issues
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
Gap Junction Network
Oscillation and Synchronization
Recurrent Neural Network
- (Sussillo & Abbott, 2009) FORCE Learning
- (Laje & Buonomano, 2013) Robust Timing in RNN
- 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
Reservoir Computing
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