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"""
Network of integrate-and-fire neurons with distance-dependent connectivity and STDP.
"""
from pyNN.utility import get_simulator
sim, options = get_simulator()
from pyNN import space
n_exc = 80
n_inh = 20
n_stim = 20
cell_parameters = {
'tau_m' : 20.0, 'tau_syn_E': 2.0, 'tau_syn_I': 5.0,
'v_rest': -65.0, 'v_reset' : -70.0, 'v_thresh': -50.0,
'cm': 1.0, 'tau_refrac': 2.0, 'e_rev_E': 0.0,
'e_rev_I': -70.0,
}
grid_parameters = {
'aspect_ratio': 1, 'dx': 50.0, 'dy': 50.0, 'fill_order': 'random'
}
stimulation_parameters = {
'rate': 100.0,
'duration': 50.0
}
connectivity_parameters = {
'gaussian': {'d_expression': 'exp(-d**2/1e4)'},
'global': {'p_connect': 0.1},
'input': {'n': 10},
}
synaptic_parameters = {
'excitatory': {
'timing_dependence': {'tau_plus': 20.0, 'tau_minus': 20.0,
'A_plus': 0.01, 'A_minus': 0.012},
'weight_dependence': {'w_min': 0, 'w_max': 0.04},
'weight': 0.01,
'delay': '0.1+0.001*d'},
'inhibitory': {'weight': 0.05, 'delay': '0.1+0.001*d'},
'input': {'weight': 0.01, 'delay': 0.1},
}
sim.setup()
all_cells = sim.Population(n_exc + n_inh, sim.IF_cond_exp(**cell_parameters),
structure=space.Grid2D(**grid_parameters),
label="All Cells")
exc_cells = all_cells[:n_exc]; exc_cells.label = "Excitatory cells"
inh_cells = all_cells[n_exc:]; inh_cells.label = "Inhibitory cells"
ext_stim = sim.Population(n_stim, sim.SpikeSourcePoisson(**stimulation_parameters),
label="External Poisson stimulation")
stdp_mechanism = sim.STDPMechanism(
timing_dependence=sim.SpikePairRule(**synaptic_parameters['excitatory']['timing_dependence']),
weight_dependence=sim.AdditiveWeightDependence(**synaptic_parameters['excitatory']['weight_dependence']),
weight=synaptic_parameters['excitatory']['weight'],
delay=synaptic_parameters['excitatory']['delay'])
gaussian_connectivity = sim.DistanceDependentProbabilityConnector(
**connectivity_parameters['gaussian'])
global_connectivity = sim.FixedProbabilityConnector(
**connectivity_parameters['global'])
input_connectivity = sim.FixedNumberPostConnector(
**connectivity_parameters['input'])
exc_connections = sim.Projection(exc_cells, all_cells,
gaussian_connectivity,
receptor_type='excitatory',
synapse_type=stdp_mechanism,
label='Excitatory connections')
inh_connections = sim.Projection(inh_cells, all_cells,
global_connectivity,
receptor_type='inhibitory',
synapse_type=sim.StaticSynapse(**synaptic_parameters['inhibitory']),
label='Inhibitory connections')
stim_connections = sim.Projection(ext_stim, all_cells,
input_connectivity,
receptor_type='excitatory',
synapse_type=sim.StaticSynapse(**synaptic_parameters['input']),
label='Input connections')
print(__doc__)
print("The network consists of:\n")
print(all_cells.describe())
print(exc_cells.describe())
print(inh_cells.describe())
print(ext_stim.describe())
print("connected as follows:\n")
print(exc_connections.describe())
print(inh_connections.describe())
print(stim_connections.describe())
sim.end()
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