brainpy.dyn.channels.ICaL

class brainpy.dyn.channels.ICaL(size, T=36.0, T_base_p=3.55, T_base_q=3.0, g_max=1.0, V_sh=0.0, method='exp_auto', name=None)

The L-type calcium channel model.

The L-type calcium channel model is adopted from (Inoue, et, al., 2008) 1. Its dynamics is given by:

\[\begin{split}I_{CaL} &= g_{max} p^2 q(V-E_{Ca}) \\ {dp \over dt} &= {\phi_p \cdot (p_{\infty}-p)\over \tau_p} \\ &p_{\infty} = {1 \over 1+\exp [-(V+10-V_{sh}) / 4.]} \\ &\tau_{p} = 0.4+{0.7 \over \exp [(V+5-V_{sh}) / 15]+\exp [-(V+5-V_{sh}) / 15]} \\ {dq \over dt} &= {\phi_q \cdot (q_{\infty}-q) \over \tau_q} \\ &q_{\infty} = {1 \over 1+\exp [(V+25-V_{sh}) / 2]} \\ &\tau_q = 300 + {100 \over \exp [(V+40-V_{sh}) / 9.5]+\exp [-(V+40-V_{sh}) / 9.5]}\end{split}\]

where \(phi_p = 3.55^{\frac{T-24}{10}}\) and \(phi_q = 3^{\frac{T-24}{10}}\) are temperature-dependent factors (\(T\) is the temperature in Celsius), \(E_{Ca}\) is the reversal potential of Calcium channel.

Parameters

• T (float) – The temperature.

• T_base_p (float) – The base temperature factor of \(p\) channel.

• T_base_q (float) – The base temperature factor of \(q\) channel.

• g_max (float) – The maximum conductance.

• V_sh (float) – The membrane potential shift.

References

1

Inoue, Tsuyoshi, and Ben W. Strowbridge. “Transient activity induces a long-lasting increase in the excitability of olfactory bulb interneurons.” Journal of neurophysiology 99, no. 1 (2008): 187-199.

__init__(size, T=36.0, T_base_p=3.55, T_base_q=3.0, g_max=1.0, V_sh=0.0, method='exp_auto', name=None)

Methods

__init__(size[, T, T_base_p, T_base_q, ...])
current(V, C_Ca, E_Ca)
dp(p, t, V)
dq(q, 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, C_Ca, E_Ca)	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, C_Ca, E_Ca)	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