brainpy.dyn.channels.Ih

class brainpy.dyn.channels.Ih(size, g_max=10.0, E=- 90.0, phi=1.0, method='exp_auto', name=None)

The hyperpolarization-activated cation current model.

The hyperpolarization-activated cation current model is adopted from (Huguenard, et, al., 1992) 1. Its dynamics is given by:

\[\begin{split}\begin{aligned} I_h &= g_{\mathrm{max}} p \\ \frac{dp}{dt} &= \phi \frac{p_{\infty} - p}{\tau_p} \\ p_{\infty} &=\frac{1}{1+\exp ((V+75) / 5.5)} \\ \tau_{p} &=\frac{1}{\exp (-0.086 V-14.59)+\exp (0.0701 V-1.87)} \end{aligned}\end{split}\]

where \(\phi=1\) is a temperature-dependent factor.

Parameters

• g_max (float) – The maximal conductance density (\(mS/cm^2\)).

• E (float) – The reversal potential (mV).

• phi (float) – The temperature-dependent factor.

References

1

Huguenard, John R., and David A. McCormick. “Simulation of the currents involved in rhythmic oscillations in thalamic relay neurons.” Journal of neurophysiology 68, no. 4 (1992): 1373-1383.

__init__(size, g_max=10.0, E=- 90.0, phi=1.0, method='exp_auto', name=None)

Methods

__init__(size[, g_max, E, phi, method, name])
current(V)
derivative(p, t, V)
get_delay_data(name, delay_step, *indices)	Get delay data according to the provided delay steps.
ints([method])	Collect all integrators in this node and the children nodes.
load_states(filename[, verbose])	Load the model states.
nodes([method, level, include_self])	Collect all children nodes.
register_delay(name, delay_step, delay_target)	Register delay variable.
register_implicit_nodes(nodes)
register_implicit_vars(variables)
reset(V)	Reset function which reset the whole variables in the model.
reset_delay(name, delay_target)	Reset the delay variable.
save_states(filename[, variables])	Save the model states.
train_vars([method, level, include_self])	The shortcut for retrieving all trainable variables.
unique_name([name, type_])	Get the unique name for this object.
update(t, dt, V)	The function to specify the updating rule.
update_delay(name, delay_data)	Update the delay according to the delay data.
vars([method, level, include_self])	Collect all variables in this node and the children nodes.

Attributes

global_delay_vars
name
steps