Simulation module

Simulations utilities

Simulate MEEG-like signals with different connectivity patterns or methods.

Todo

• Follow up on these:

  • RNN of rate models: RNN of rate models

  • ctRNN revision, see ctRNN revision

• Simulation based on connectivity matrix: implement a network of N nodes simply using the connectivity matrix and node-specific implementations

• Neural mass models to be added:

  • Wilson-Cowan

Classes

NeuralMassNode([dt, seed])	Abstract base class for a single neural-mass node.
NeuralMassNetwork(N, W[, delay, ...])	Abstract base class for a network of coupled neural-mass nodes.
HopfOscillator([a, frequency, dt, seed])	Two-dimensional Stuart-Landau (Hopf normal-form) oscillator.
Phasor([frequency, dt, seed])	One-dimensional phase oscillator with sinusoidal readout.
WilsonCowan([tau_e, tau_i, w_ee, w_ei, ...])	Two-population excitatory/inhibitory Wilson-Cowan rate model.
Kuramoto([N, W, coupling_strength, ...])	Convenience network of Phasor nodes with Kuramoto coupling.
CTRNN(N, W[, input_dim, output_dim, dt, ...])	Continuous Time Recurrent Neural Network (CTRNN) model.
JansenRit([dt, seed, nonlinearity])	Jansen-Rit model.
JansenRitExtended([w, dt, seed, nonlinearity])	Jansen-Rit model - Exctended version: dual kinetic model.
JRNetwork([N, W, delay, w, node_dynamics, ...])	Network of coupled Jansen-Rit extended neural-mass nodes.

Functions

simulate_ar(order, coefs, n[, sigma, seed])	Simulate an autoregressive process of order order.
simulate_var(order, coef[, nobs, ndim, ...])	Simulate a VAR model of order order.
simulate_var_from_cov(cov[, nobs, ndim, ...])	Simulate a VAR model of order order from a covariance matrix.
linear_coupling(readouts, connectivity[, phases])	Linear projection of node readouts through the connectivity matrix.
diffusive_coupling(readouts, connectivity[, ...])	Weighted diffusive coupling of scalar node readouts.
kuramoto_coupling(readouts, connectivity, phases)	Sinusoidal phase-difference (Kuramoto) coupling.
dummy_trf_kernel([tmin, tmax, srate, tloc, ...])	Dummy kernel for testing purposes.
simulate_smooth_input([dur, srate, fmax, seed])	Simulate a smooth input signal.
simulate_pulse_inputs([n_events, dur, ...])	Simulate a pulse input signal.
simulate_trf_output(tkernel, kernel, input)	Simulate the output of a kernel given an input signal.