DiffusiveCoupling#
- 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
Examples
>>> 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)
- Parameters:
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.