traub_psc_alpha

traub_psc_alpha - Traub model according to Borgers 2017

Reduced Traub-Miles Model of a Pyramidal Neuron in Rat Hippocampus 1. parameters got from reference 2.

Incoming spike events induce a post-synaptic change of current modelled by an alpha function.

References

1

18. 4. Traub and R. Miles, Neuronal Networks of the Hippocampus,Cam- bridge University Press, Cambridge, UK, 1991.

2

Borgers, C., 2017. An introduction to modeling neuronal dynamics (Vol. 66). Cham: Springer.

See also

hh_cond_exp_traub

Parameters

Name	Physical unit	Default value	Description
t_ref	ms	2ms	Refractory period
g_Na	nS	10000nS	Sodium peak conductance
g_K	nS	8000nS	Potassium peak conductance
g_L	nS	10nS	Leak conductance
C_m	pF	100pF	Membrane capacitance
E_Na	mV	50mV	Sodium reversal potential
E_K	mV	-100mV	Potassium reversal potential
E_L	mV	-67mV	Leak reversal potential (aka resting potential)
V_Tr	mV	-20mV	Spike threshold
tau_syn_exc	ms	0.2ms	Rise time of the excitatory synaptic alpha function
tau_syn_inh	ms	2ms	Rise time of the inhibitory synaptic alpha function
I_e	pA	0pA	constant external input current

State variables

Name	Physical unit	Default value	Description
r	integer	0	number of steps in the current refractory phase
V_m	mV	-70.0mV	Membrane potential
Act_m	real	alpha_m_init / (alpha_m_init + beta_m_init)	Activation variable m for Na
Inact_h	real	alpha_h_init / (alpha_h_init + beta_h_init)	Inactivation variable h for Na
Act_n	real	alpha_n_init / (alpha_n_init + beta_n_init)	Activation variable n for K

Equations

\[\frac{ dV_{m} } { dt }= \frac 1 { C_{m} } \left( { (-(I_{Na} + I_{K} + I_{L}) + I_{e} + I_{stim} + I_{syn,exc} - I_{syn,inh}) } \right)\]

\[\frac{ dAct_{n} } { dt }= \frac 1 { \mathrm{ms} } \left( { (\alpha_{n} \cdot (1 - Act_{n}) - \beta_{n} \cdot Act_{n}) } \right)\]

\[\frac{ dAct_{m} } { dt }= \frac 1 { \mathrm{ms} } \left( { (\alpha_{m} \cdot (1 - Act_{m}) - \beta_{m} \cdot Act_{m}) } \right)\]

\[\frac{ dInact_{h} } { dt }= \frac 1 { \mathrm{ms} } \left( { (\alpha_{h} \cdot (1 - Inact_{h}) - \beta_{h} \cdot Inact_{h}) } \right)\]

Source code

neuron traub_psc_alpha:
  state:
    r integer = 0 # number of steps in the current refractory phase
    V_m mV = -70.0mV # Membrane potential
    Act_m real = alpha_m_init / (alpha_m_init + beta_m_init) # Activation variable m for Na
    Inact_h real = alpha_h_init / (alpha_h_init + beta_h_init) # Inactivation variable h for Na
    Act_n real = alpha_n_init / (alpha_n_init + beta_n_init) # Activation variable n for K
  end
  equations:
    # synapses: alpha functions
    kernel K_syn_inh = (e / tau_syn_inh) * t * exp(-t / tau_syn_inh)
    kernel K_syn_exc = (e / tau_syn_exc) * t * exp(-t / tau_syn_exc)
    inline I_syn_exc pA = convolve(K_syn_exc,exc_spikes)
    inline I_syn_inh pA = convolve(K_syn_inh,inh_spikes)
    inline I_Na pA = g_Na * Act_m * Act_m * Act_m * Inact_h * (V_m - E_Na)
    inline I_K pA = g_K * Act_n * Act_n * Act_n * Act_n * (V_m - E_K)
    inline I_L pA = g_L * (V_m - E_L)
    V_m'=(-(I_Na + I_K + I_L) + I_e + I_stim + I_syn_exc - I_syn_inh) / C_m
    # Act_n
    inline alpha_n real = 0.032 * (V_m / mV + 52.0) / (1.0 - exp(-(V_m / mV + 52.0) / 5.0))
    inline beta_n real = 0.5 * exp(-(V_m / mV + 57.0) / 40.0)
    Act_n'=(alpha_n * (1 - Act_n) - beta_n * Act_n) / ms # n-variable
    # Act_m

    # Act_m
    inline alpha_m real = 0.32 * (V_m / mV + 54.0) / (1.0 - exp(-(V_m / mV + 54.0) / 4.0))
    inline beta_m real = 0.28 * (V_m / mV + 27.0) / (exp((V_m / mV + 27.0) / 5.0) - 1.0)
    Act_m'=(alpha_m * (1 - Act_m) - beta_m * Act_m) / ms # m-variable
    # Inact_h'

    # Inact_h'
    inline alpha_h real = 0.128 * exp(-(V_m / mV + 50.0) / 18.0)
    inline beta_h real = 4.0 / (1.0 + exp(-(V_m / mV + 27.0) / 5.0))
    Inact_h'=(alpha_h * (1 - Inact_h) - beta_h * Inact_h) / ms # h-variable
  end

  parameters:
    t_ref ms = 2ms # Refractory period
    g_Na nS = 10000nS # Sodium peak conductance
    g_K nS = 8000nS # Potassium peak conductance
    g_L nS = 10nS # Leak conductance
    C_m pF = 100pF # Membrane capacitance
    E_Na mV = 50mV # Sodium reversal potential
    E_K mV = -100mV # Potassium reversal potential
    E_L mV = -67mV # Leak reversal potential (aka resting potential)
    V_Tr mV = -20mV # Spike threshold
    tau_syn_exc ms = 0.2ms # Rise time of the excitatory synaptic alpha function
    tau_syn_inh ms = 2ms # Rise time of the inhibitory synaptic alpha function
    # constant external input current

    # constant external input current
    I_e pA = 0pA
  end
  internals:
    RefractoryCounts integer = steps(t_ref) # refractory time in steps
    alpha_n_init real = 0.032 * (V_m / mV + 52.0) / (1.0 - exp(-(V_m / mV + 52.0) / 5.0))
    beta_n_init real = 0.5 * exp(-(V_m / mV + 57.0) / 40.0)
    alpha_m_init real = 0.32 * (V_m / mV + 54.0) / (1.0 - exp(-(V_m / mV + 54.0) / 4.0))
    beta_m_init real = 0.28 * (V_m / mV + 27.0) / (exp((V_m / mV + 27.0) / 5.0) - 1.0)
    alpha_h_init real = 0.128 * exp(-(V_m / mV + 50.0) / 18.0)
    beta_h_init real = 4.0 / (1.0 + exp(-(V_m / mV + 27.0) / 5.0))
  end
  input:
    inh_spikes pA <-inhibitory spike
    exc_spikes pA <-excitatory spike
    I_stim pA <-current
  end

  output: spike

  update:
    U_old mV = V_m
    integrate_odes()
    # sending spikes: crossing 0 mV, pseudo-refractoriness and local maximum...

    # sending spikes: crossing 0 mV, pseudo-refractoriness and local maximum...
    if r > 0: # is refractory?
      r -= 1
    elif V_m > V_Tr and U_old > V_Tr:
      r = RefractoryCounts
      emit_spike()
    end
  end

end

Characterisation