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BrainPy Examples

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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

(Si Wu, 2008): Continuous-attractor Neural Network 1D
(Si Wu, 2008): Continuous-attractor Neural Network 2D
CANN 1D Oscillatory Tracking

Decision Making Model

(Wang, 2002) Decision making spiking model
(Wong & Wang, 2006) Decision making rate model

E/I Balanced Network

(Vreeswijk & Sompolinsky, 1996) E/I balanced network
(Brette, et, al., 2007) COBA
(Brette, et, al., 2007) CUBA
(Brette, et, al., 2007) COBA-HH
(Tian, et al., 2020) E/I Net for fast response

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

Predicting Mackey-Glass timeseries
(Gauthier, et. al, 2021): Next generation reservoir computing
(Sussillo & Abbott, 2009) FORCE Learning

Gap Junction Network

(Sherman & Rinzel, 1992) Gap junction leads to anti-synchronization
(Fazli and Richard, 2022): Electrically Coupled Bursting Pituitary Cells

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

(Joglekar, et. al, 2018): Inter-areal Balanced Amplification Figure 1
(Joglekar, et. al, 2018): Inter-areal Balanced Amplification Figure 2
(Joglekar, et. al, 2018): Inter-areal Balanced Amplification Figure 5

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

(Bouchacourt & Buschman, 2019) Flexible Working Memory Model
(Mi, et. al., 2017) STP for Working Memory Capacity
(Masse, et al., 2019): RNN with STP for Working Memory

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

Hénon map
Logistic map
Lorenz system
Mackey-Glass equation
Multiscroll chaotic attractor (多卷波混沌吸引子)
Rabinovich-Fabrikant equations
Fractional-order Chaos Gallery

Unclassified Models

(Brette & Guigon, 2003): Reliability of spike timing

BrainPy Examples

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(Si Wu, 2008): Continuous-attractor Neural Network 1D
(Si Wu, 2008): Continuous-attractor Neural Network 2D
CANN 1D Oscillatory Tracking

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