import brian2 as br from brian2 import umetre, ufarad, cm, siemens, mV, msiemens, nS, ms # Hodgkin Huxley model from Brian2 documentation # The model area = 20000 * umetre ** 2 hodgkin_huxley_params = { "Cm": 1 * ufarad * cm ** -2 * area, "gl": 5e-5 * siemens * cm ** -2 * area, "El": -65 * mV, "EK": -90 * mV, "ENa": 50 * mV, "g_na": 100 * msiemens * cm ** -2 * area, "g_kd": 30 * msiemens * cm ** -2 * area, "VT": -63 * mV } hodgkin_huxley_eqs = br.Equations(''' dv/dt = (gl*(El-v) - g_na*(m*m*m)*h*(v-ENa) - g_kd*(n*n*n*n)*(v-EK) + I + ih)/Cm : volt dm/dt = 0.32*(mV**-1)*(13.*mV-v+VT)/ (exp((13.*mV-v+VT)/(4.*mV))-1.)/ms*(1-m)-0.28*(mV**-1)*(v-VT-40.*mV)/ (exp((v-VT-40.*mV)/(5.*mV))-1.)/ms*m : 1 dn/dt = 0.032*(mV**-1)*(15.*mV-v+VT)/ (exp((15.*mV-v+VT)/(5.*mV))-1.)/ms*(1.-n)-.5*exp((10.*mV-v+VT)/(40.*mV))/ms*n : 1 dh/dt = 0.128*exp((17.*mV-v+VT)/(18.*mV))/ms*(1.-h)-4./(1+exp((40.*mV-v+VT)/(5.*mV)))/ms*h : 1 I : amp ''') hodgkin_huxley_cond_synapse_weak_noise_eqs = br.Equations(''' dv/dt = (gl*(El-v) - g_na*(m*m*m)*h*(v-ENa) - g_kd*(n*n*n*n)*(v-EK) + I + ih - g_syn*(v-E_i))/Cm + sigma_noise*sqrt(1./tau_noise)*xi : volt dm/dt = 0.32*(mV**-1)*(13.*mV-v+VT)/ (exp((13.*mV-v+VT)/(4.*mV))-1.)/ms*(1-m)-0.28*(mV**-1)*(v-VT-40.*mV)/ (exp((v-VT-40.*mV)/(5.*mV))-1.)/ms*m : 1 dn/dt = 0.032*(mV**-1)*(15.*mV-v+VT)/ (exp((15.*mV-v+VT)/(5.*mV))-1.)/ms*(1.-n)-.5*exp((10.*mV-v+VT)/(40.*mV))/ms*n : 1 dh/dt = 0.128*exp((17.*mV-v+VT)/(18.*mV))/ms*(1.-h)-4./(1+exp((40.*mV-v+VT)/(5.*mV)))/ms*h : 1 I : amp g_syn: siemens ''') hodgkin_huxley_with_external_input_eqs = br.Equations(''' dv/dt = (gl*(El-v) - g_na*(m*m*m)*h*(v-ENa) - g_kd*(n*n*n*n)*(v-EK) + I + ih)/Cm : volt dm/dt = 0.32*(mV**-1)*(13.*mV-v+VT)/ (exp((13.*mV-v+VT)/(4.*mV))-1.)/ms*(1-m)-0.28*(mV**-1)*(v-VT-40.*mV)/ (exp((v-VT-40.*mV)/(5.*mV))-1.)/ms*m : 1 dn/dt = 0.032*(mV**-1)*(15.*mV-v+VT)/ (exp((15.*mV-v+VT)/(5.*mV))-1.)/ms*(1.-n)-.5*exp((10.*mV-v+VT)/(40.*mV))/ms*n : 1 dh/dt = 0.128*exp((17.*mV-v+VT)/(18.*mV))/ms*(1.-h)-4./(1+exp((40.*mV-v+VT)/(5.*mV)))/ms*h : 1 I = I_ext_const + stimulus(t) : amp (constant over dt) I_ext_const : amp ''') hodgkin_huxley_eqs_with_synaptic_conductance = br.Equations(''' dv/dt = (gl*(El-v) - g_na*(m*m*m)*h*(v-ENa) - g_kd*(n*n*n*n)*(v-EK) + I + ih - g_syn*(v-E_i))/Cm : volt dm/dt = 0.32*(mV**-1)*(13.*mV-v+VT)/ (exp((13.*mV-v+VT)/(4.*mV))-1.)/ms*(1-m)-0.28*(mV**-1)*(v-VT-40.*mV)/ (exp((v-VT-40.*mV)/(5.*mV))-1.)/ms*m : 1 dn/dt = 0.032*(mV**-1)*(15.*mV-v+VT)/ (exp((15.*mV-v+VT)/(5.*mV))-1.)/ms*(1.-n)-.5*exp((10.*mV-v+VT)/(40.*mV))/ms*n : 1 dh/dt = 0.128*exp((17.*mV-v+VT)/(18.*mV))/ms*(1.-h)-4./(1+exp((40.*mV-v+VT)/(5.*mV)))/ms*h : 1 I : amp g_syn: siemens ''') # # First H-current from Izhikevich p. 48 # ghbar = 40. * nS #Other values would be 0.5, 2, 3.5, 20 depending on neuron type (Rothman, Manis) # Eh = -43*mV # V_half_h = -75.0 # k_h = -5.5 # V_max_h = -75. # sigma_h = 15. # C_amp_h = 1000. # C_base_h = 100. # eqs_ih = """ # ih = ghbar*r*(Eh-v) : amp # dr/dt= (rinf-r)/rtau : 1 # rinf = 1. / (1+exp((V_half_h - v/mV) / k_h)) : 1 # rtau = (C_base_h + C_amp_h * exp(-(V_max_h-v/mV)**2./sigma_h**2)) * ms : second # """ # Second H-current from Izhikevich p. 48 # eqs_ih = """ # ih = ghbar*r*(Eh-v) : amp # dr/dt=(rinf-r)/rtau : 1 # rinf = 1. / (1+exp((v/mV + 90.) / 7.)) : 1 # # rtau = ((100000. / (237.*exp((v/mV+60.) / 12.) + 17.*exp(-(v/mV+60.) / 14.))) + 25.)*ms : second # rtau = 0.01*(100. + 1000. * exp(-(-76.-v/mV)**2./15.**2)) * ms : second #From Izhikevich # """ ih_params = { "ghbar": 40. * nS, # Other values would be 0.5, 2, 3.5, 20 depending on neuron type (Rothman, Manis) "Eh": -1. * mV, "V_half_h": -95.0, "k_h": -5.5, "V_max_h": -75., "sigma_h": 20., "C_amp_h": 50., "C_base_h": 10., } eqs_ih = """ ih = ghbar*r*(Eh-v) : amp dr/dt= (rinf-r)/rtau : 1 rinf = 1. / (1+exp((V_half_h - v/mV) / k_h)) : 1 rtau = 0.1*(C_base_h + C_amp_h * exp(-(V_max_h-v/mV)**2./sigma_h**2)) * ms : second """ lif_eqs = """ dv/dt =1.0/tau* (-v + u_ext) :volt (unless refractory) u_ext = u_ext_const : volt """ lif_params = { "tau": 7 * ms, "v_threshold": -40 * mV, "v_reset": -60 * mV, "tau_refractory": 0.0 * ms, "u_ext_const": -50 * mV } lif_options = { "threshold": "v>v_threshold", "reset": "v=v_reset", "refractory": "tau_refractory", 'method': 'euler' } delta_synapse_model = 'synaptic_strength: volt' delta_synapse_on_pre = 'v+=synaptic_strength' delta_synapse_param = {} exponential_synapse = """ dg/dt = -g/tau_syn : siemens (clock-driven) g_syn_post = g :siemens (summed) synaptic_strength : siemens """ exponential_synapse_on_pre = "g+=synaptic_strength" exponential_synapse_params = { "tau_syn": 1 * ms } noise_params = { 'sigma_noise': 1.0 * mV, 'tau_noise': 10. * ms }