def _build_model(self, traj, brian_list, network_dict): """Builds the neuron groups from `traj`. Adds the neuron groups to `brian_list` and `network_dict`. """ model = traj.parameters.model # Create the equations for both models eqs_dict = self._build_model_eqs(traj) # Create inhibitory neurons eqs_i = eqs_dict['i'] neurons_i = NeuronGroup(N=model.N_i, model=eqs_i, threshold=model.V_th, reset=model.reset_func, refractory=model.refractory, freeze=True, compile=True, method='Euler') # Create excitatory neurons eqs_e = eqs_dict['e'] neurons_e = NeuronGroup(N=model.N_e, model=eqs_e, threshold=model.V_th, reset=model.reset_func, refractory=model.refractory, freeze=True, compile=True, method='Euler') # Set the bias terms neurons_e.mu = rand( model.N_e) * (model.mu_e_max - model.mu_e_min) + model.mu_e_min neurons_i.mu = rand( model.N_i) * (model.mu_i_max - model.mu_i_min) + model.mu_i_min # Set initial membrane potentials neurons_e.V = rand(model.N_e) neurons_i.V = rand(model.N_i) # Add both groups to the `brian_list` and the `network_dict` brian_list.append(neurons_i) brian_list.append(neurons_e) network_dict['neurons_e'] = neurons_e network_dict['neurons_i'] = neurons_i
def _build_model(self, traj, brian_list, network_dict): """Builds the neuron groups from `traj`. Adds the neuron groups to `brian_list` and `network_dict`. """ assert(isinstance(traj,SingleRun)) model = traj.parameters.model # Create the equations for both models eqs_dict = self._build_model_eqs(traj) # Create inhibitory neurons eqs_i = eqs_dict['i'] neurons_i = NeuronGroup(N=model.N_i, model = eqs_i, threshold=model.V_th, reset=model.reset_func, refractory=model.refractory, freeze=True, compile=True, method='Euler') # Create excitatory neurons eqs_e = eqs_dict['e'] neurons_e = NeuronGroup(N=model.N_e, model = eqs_e, threshold=model.V_th, reset=model.reset_func, refractory=model.refractory, freeze=True, compile=True, method='Euler') # Set the bias terms neurons_e.mu =rand(model.N_e) * (model.mu_e_max - model.mu_e_min) + model.mu_e_min neurons_i.mu =rand(model.N_i) * (model.mu_i_max - model.mu_i_min) + model.mu_i_min # Set initial membrane potentials neurons_e.V = rand(model.N_e) neurons_i.V = rand(model.N_i) # Add both groups to the `brian_list` and the `network_dict` brian_list.append(neurons_i) brian_list.append(neurons_e) network_dict['neurons_e']=neurons_e network_dict['neurons_i']=neurons_i