diff --git a/multiarea_model/default_params.py b/multiarea_model/default_params.py index f1d85dac7656aec5be8dbcfaf8ad854be95b6c33..bbe72df88b54484b920e5030468c77cd076ea747 100644 --- a/multiarea_model/default_params.py +++ b/multiarea_model/default_params.py @@ -281,7 +281,7 @@ theory_params = {'neuron_params': neuron_params, # The simulation time of the mean-field theory integration 'T': 50., # The time step of the mean-field theory integration - 'dt': 0.1, + 'dt': 0.01, # Time interval for recording the trajectory of the mean-field calcuation # If None, then the interval is set to dt 'rec_interval': None} diff --git a/multiarea_model/theory.py b/multiarea_model/theory.py index ba9ec58012b6e41fe75e84fe5feab469f2dfb321..c00e54ca6a5e01ffb0664428a6d91762f4eeb428 100644 --- a/multiarea_model/theory.py +++ b/multiarea_model/theory.py @@ -78,13 +78,14 @@ class Theory: 'use_wfr': False, 'print_time': False, 'overwrite_files': True}) + + nest.SetDefaults('siegert_neuron', self.NP) # create neurons for external drive drive = nest.Create( 'siegert_neuron', 1, params={'rate': rate_ext, 'mean': rate_ext}) # create neurons representing populations - neurons = nest.Create( - 'siegert_neuron', dim, params=self.NP) + neurons = nest.Create('siegert_neuron', dim) # external drive syn_dict = {'drift_factor': tau * np.array([K[:, -1] * J[:, -1]]).transpose(), 'diffusion_factor': tau * np.array([K[:, -1] * J[:, -1]**2]).transpose(), @@ -132,7 +133,7 @@ class Theory: interval = self.params['rec_interval'] if interval is None: interval = dt - + multimeter = nest.Create('multimeter', params={'record_from': ['rate'], 'interval': interval, 'to_screen': False,