class brainpy.dyn.DiffusiveCoupling(coupling_var1, coupling_var2, var_to_output, conn_mat, delay_steps=None, initial_delay_data=None, name=None, mode=None)[source]#

Diffusive coupling.

This class simulates the model of:

coupling = g * (delayed_coupling_var1 - coupling_var2)
target_var += coupling


>>> import brainpy as bp
>>> from brainpy import rates
>>> areas = bp.rates.FHN(80, x_ou_sigma=0.01, y_ou_sigma=0.01, name='fhn')
>>> conn = bp.synapses.DiffusiveCoupling(areas.x, areas.x, areas.input,
>>>                                      conn_mat=Cmat, delay_steps=Dmat,
>>>                                      initial_delay_data=bp.init.Uniform(0, 0.05))
>>> net = bp.Network(areas, conn)
  • coupling_var1 (Variable) – The first coupling variable, used for delay.

  • coupling_var2 (Variable) – Another coupling variable.

  • var_to_output (Variable, sequence of Variable) – The target variables to output.

  • conn_mat (ArrayType) – The connection matrix.

  • delay_steps (int, ArrayType) – The matrix of delay time steps. Must be int.

  • initial_delay_data (Initializer, Callable) – The initializer of the initial delay data.

  • name (str) – The name of the model.


The function to specify the updating rule.