def run(argv):
sim = ncs.Simulation()
phasic_spiking_parameters = sim.addNeuron(
"phasic_spiking", "izhikevich", {
"a": 0.02,
"b": 0.25,
"c": -65.0,
"d": 6.0,
"u": -16.25,
"v": -65.0,
"threshold": 30,
})
group_1 = sim.addNeuronGroup("group_1", 1, phasic_spiking_parameters, None)
if not sim.init(argv):
print "failed to initialize simulation."
return
sim.addStimulus("rectangular_current", {
"amplitude": 0.5,
"width": 1,
"frequency": 1
}, group_1, 1, 0.01, 1.0)
voltage_report = sim.addReport("group_1", "neuron", "neuron_voltage", 1.0,
0.0, 1.0)
voltage_report.toAsciiFile("./phasic_spiking_izh.txt")
sim.run(duration=1.0)
return
def run(argv):
sim = ncs.Simulation()
bursting_parameters = sim.addNeuron("bursting","izhikevich",
{
"a": 0.02,
"b": 0.3,
"c": -50.0,
"d": 4.0,
"u": -12.0,
"v": -65.0,
"threshold": 30,
})
group_1=sim.addNeuronGroup("group_1",1,bursting_parameters,None)
group_2=sim.addNeuronGroup("group_2",1,bursting_parameters,None)
flat_parameters = sim.addSynapse("flat_synapse",
"flat",
{ "delay": 3,
"current": 10.0
})
sim.addSynapseGroup("1_to_2", group_1, group_2, 1.0, flat_parameters)
if not sim.init(argv):
print "failed to initialize simulation."
return
sim.addStimulus("rectangular_current",{"amplitude":18,"width": 1, "frequency": 1},group_1,1,0.0,1.0)
# current_report=sim.addReport("group_1","neuron","synaptic_current",1.0)
# current_report.toStdOut()
voltage_report=sim.addReport("group_2","neuron","synaptic_current",1.0,0.0,0.1).toStdOut()
#voltage_report.toAsciiFile("./bursting_izh.txt")
sim.run(duration = 0.1)
return
def run(argv):
sim = ncs.Simulation()
bursting_parameters = sim.addNeuron(
"bursting", "izhikevich", {
"a": 0.02,
"b": 0.3,
"c": -50.0,
"d": 4.0,
"u": -12.0,
"v": -65.0,
"threshold": 30,
})
group_1 = sim.addNeuronGroup("group_1", 2, bursting_parameters, None)
if not sim.init(argv):
print "failed to initialize simulation."
return
sim.addStimulus("rectangular_current", {
"amplitude": 18,
"width": 1,
"frequency": 1
}, group_1, 1, 0.01, 1.0)
voltage_report = sim.addReport("group_1", "neuron", "neuron_fire", 1.0,
0.0, 1.0).toStdOut()
sim.run(duration=1.0)
del sim
del voltage_report
return
def run(argv):
sim = ncs.Simulation()
regular_spiking_parameters = sim.addNeuron("regular_spiking","izhikevich",
{
"a": 0.02,
"b": 0.2,
"c": -65.0,
"d": 8.0,
"u": -12.0,
"v": -60.0,
"threshold": 30
})
group_1=sim.addNeuronGroup("group_1",1,regular_spiking_parameters,None)
if not sim.init(argv):
print "failed to initialize simulation."
return
input_parameters = {
"amplitude":10
}
sim.addStimulus("rectangular_current", input_parameters, group_1, 1, 0.01, 1.0)
voltage_report=sim.addReport("group_1", "neuron", "neuron_voltage", 1, 0.0, 1.0)
voltage_report.toAsciiFile("./regular_spiking_izh.txt")
sim.run(duration=1.0)
return
def run(argv):
sim = ncs.Simulation()
fast_spiking_parameters = sim.addNeuron("fast_spiking","izhikevich",
{
"a": 0.1,
"b": 0.3,
"c": -55.0,
"d": 2.0,
"u": -12.0,
"v": -65.0,
"threshold": 30,
})
group_1=sim.addNeuronGroup("group_1",1,fast_spiking_parameters,None)
if not sim.init(argv):
print "failed to initialize simulation."
return
sim.addStimulus("rectangular_current",{"amplitude":10,"width": 1, "frequency": 1},group_1,1,0.01,1.0)
voltage_report=sim.addReport("group_1","neuron","neuron_voltage",1.0,0.0,0.01)
#Place report file in current directory
voltage_report.toAsciiFile("./fast_spiking.txt")
sim.run(duration=0.01)
return
def run(argv):
sim = ncs.Simulation()
bursting_parameters = sim.addNeuron(
"bursting", "izhikevich", {
"a": 0.02,
"b": 0.3,
"c": -50.0,
"d": 4.0,
"u": -12.0,
"v": -65.0,
"threshold": 30,
})
group_1 = sim.addNeuronGroup("group_1", 2, bursting_parameters, None)
if not sim.init(argv):
print "failed to initialize simulation."
return
sim.addStimulus(
"sine_current", {
"amplitude_scale": 10,
"time_scale": 200.0 / math.pi,
"phase": 0.0,
"amplitude_shift": 10
}, group_1, 1, 0.01, 1.0)
# current_report=sim.addReport("group_1","neuron","synaptic_current",1.0)
# current_report.toStdOut()
voltage_report = sim.addReport("group_1", "neuron", "input_current", 1.0,
0.0, 1.0).toStdOut()
#voltage_report.toAsciiFile("./bursting_izh.txt")
sim.run(duration=1.0)
return
def run(argv):
sim = ncs.Simulation()
excitatory_parameters = sim.addNeuron("label_excitatory",
"izhikevich",
{
"a": 0.2,
"b": 0.2,
"c": -65.0,
"d": ncs.Uniform(7.0, 9.0),
"u": ncs.Uniform(-15.0, -11.0),
"v": ncs.Normal(-60.0, 5.0),
"threshold": 30,
}
)
group_1 = sim.addNeuronGroup("group_1", 100, "label_excitatory", None) # last param is geometry
group_2 = sim.addNeuronGroup("group_2", 100, excitatory_parameters)
all_cells = sim.addNeuronAlias("all_cells", [group_1, "group_2"])
sim.addNeuronAlias("all", all_cells)
sim.addNeuronAlias("all_2", "all_cells")
flat_parameters = sim.addSynapse("flat_synapse",
"flat",
{ "delay": 2,
"current": ncs.Normal(18.0,2.0)
})
all_to_all = sim.addSynapseGroup("all_to_all", all_cells, "all_2", 0.1, flat_parameters)
all_to_all_2 = sim.addSynapseGroup("all_to_all_2",
[group_1, group_2],
"all_2",
0.1,
flat_parameters)
one_to_two = sim.addSynapseGroup("one_to_two",
group_1,
"group_2",
0.1,
"flat_synapse")
all_connections = sim.addSynapseAlias("all_connections", [all_to_all, one_to_two])
if not sim.init(argv):
print "Failed to initialize simulation."
return
sim.addStimulus("rectangular_current", { "amplitude": 18.0 }, group_1, 0.1, 0.0, 1.0)
sim.addStimulus("rectangular_current", { "amplitude": 18.0 }, "all", 0.1, 0.0, 0.5)
sim.addStimulus("rectangular_current", { "amplitude": 18.0 }, "group_2", 0.1, 0.1, 1.1)
voltage_report = sim.addReport("group_1", "neuron", "neuron_voltage", 1.0,0.0,0.01)
voltage_report.toAsciiFile("/tmp/foo.txt")
fire_report = sim.addReport(all_cells, "neuron", "neuron_fire", 1.0,0.0,0.01)
fire_report.toStdOut()
sim.run(duration=0.01)
return
def Run(argv):
sim = ncs.Simulation()
anatomy_pcrain.add(sim)
if not sim.init(argv):
print "Failed to initialize simulation."
return
sim.step(50)
return
def Run(argv):
sim = ncs.Simulation()
excitatory_parameters = sim.addNeuron(
"label_excitatory", "izhikevich", {
"a": 0.2,
"b": 0.2,
"c": -65.0,
"d": ncs.Uniform(7.0, 9.0),
"u": ncs.Uniform(-15.0, -11.0),
"v": ncs.Normal(-60.0, 5.0),
"threshold": 30,
})
group_1 = sim.addNeuronGroup("group_1", 1, "label_excitatory",
None) # last param is geometry
group_2 = sim.addNeuronGroup("group_2", 1, excitatory_parameters)
flat_parameters = sim.addNeuron(
"synapse", "ncs", {
"utilization": ncs.Normal(0.5, 0.05),
"redistribution": 1.0,
"last_prefire_time": 0.0,
"last_postfire_time": 0.0,
"tau_facilitation": 0.001,
"tau_depression": 0.001,
"tau_ltp": 0.015,
"tau_ltd": 0.03,
"A_ltp_minimum": 0.003,
"A_ltd_minimum": 0.003,
"max_conductance": 0.004,
"reversal_potential": 0.0,
"tau_postsynaptic_conductance": 0.025,
"psg_waveform_duration": 0.05,
"delay": ncs.Uniform(1, 5),
})
synapse = sim.addSynapseGroup("1_to_2", group_1, "group_2", 1,
flat_parameters)
if not sim.init(argv):
print "Failed to initialize simulation."
return
sim.addStimulus("rectangular_current", {"amplitude": 18.0}, group_1, 1.0,
0.0, 1.0)
#current_report = sim.addReport(group_2, "neuron", "synaptic_current", 1.0)
current_report = sim.addReport(group_2, "neuron", "synaptic_current", 1.0,
0.0, 0.05)
current_report.toStdOut()
sim.run(duration=0.05)
return
def run(argv):
#ncs.simulation() is required
sim = ncs.Simulation()
#start writing model - biology information
#addNeuron function
#Parameters for addNeuron function:
# 1. A neuron name (string)
# 2. A neuron type (string)
# izhikevich, ncs, or hh
# 3. A map for parameter names to their values(Generators)
# Generators can be exact, Normal, uniform
# exact example : "a": 0.02
# uniform example: "a": ncs.Uniform(min, max)
# normal example: "a": ncs.Normal(mean, standard deviation)
# Example of addNeuron with regular_spiking izhikevich neuron
regular_spiking_parameters = sim.addNeuron("regular_spiking","izhikevich",
{
"a": 0.02,
"b": 0.2,
"c": -65.0,
"d": 8.0,
"u": -12.0,
"v": -60.0,
"threshold": 30,
})
#addSynapse function
#Parameters for addSynapse function
# 1. A synapse name (string)
# 2. A synapse type (string)
# ncs or flat
# 3. A map for parameter names to their values (Generators)
ncs_synapse_parameters = sim.addSynapse("flat_synapse","ncs",{
"utilization": ncs.Normal(0.5,0.05),
"redistribution": 1.0,
"last_prefire_time": 0.0,
"last_postfire_time": 0.0,
"tau_facilitation": 0.001,
"tau_depression": 0.001,
"tau_ltp": 0.015,
"tau_ltd": 0.03,
"A_ltp_minimum": 0.003,
"A_ltd_minimum": 0.003,
"max_conductance": 0.3,
"reversal_potential":0.0,
"tau_postsynaptic_conductance": 0.02,
"psg_waveform_duration": 0.05,
"delay": 1,
})
#addNeuronGroup function
#Parameters for addNeuronGroup function:
# 1. A name of the group (string)
# 2. Number of cells (integer)
# 3. Neuron parameters
# 4. Geometry generator (optional)
group_1=sim.addNeuronGroup("group_1",1,regular_spiking_parameters,None)
group_2=sim.addNeuronGroup("group_2",1,regular_spiking_parameters,None)
#addSynapseGroup function
#Parameters for addSynapseGroup function:
# 1. A name of the connection
# 2. Presynaptic NeuronAlias or NeuronGroup
# 3. Postsynaptic NeuronAlias or NeuronGroup
# 4. Probability of connection
# 5. Parameters for synapse
connection1=sim.addSynapseGroup("connection1","group_1","group_2",1,"flat_synapse");
#initialize simulation
if not sim.init(argv):
print "failed to initialize simulation."
return
#addStimulus function
#parameters for addStimulus function:
# 1. A stimulus type (string)
# rectangular_current, rectangular_voltage, linear_current, linear_voltage,
# sine_current, or sine_voltage
# 2. A map from parameter names (strings) to their values (Generators)
# Parameter names are amplitude, starting_amplitude, ending_amplitude,
# delay, current, amplitude_scale, time_scale, phase, amplitude_shift,
# etc. based on the stimulus type
# 3. A set of target neuron groups
# 4. probability of a neuron receiving input
# 5. start time for stimulus (seconds)
# For example, if you wanted to start stimulus at 1 ms, write 0.01
# 6. end time for stimulus (seconds)
sim.addStimulus("rectangular_current",{"amplitude":10},group_1,1,0.01,1.0)
#addReport function
#Parameters for addReport function:
# 1. A set of neuron group or a set of synapse group to report on
# 2. A target type: "neuron" or "synapses"
# 3. type of report: synaptic_current, neuron_voltage, neuron_fire,
# input current, etc.
# 4. Probability (the percentage of elements to report on)
voltage_report_1=sim.addReport([group_1,group_2],"neuron","neuron_voltage",1.0,0.0,1.0)
#An example of a report to file
voltage_report_1.toAsciiFile("reg_voltage_report.txt");
#duration (in seconds) - each time step is 1 ms
sim.run(duration=1.0)
return
def run(argv):
sim = ncs.Simulation()
excitatory_parameters = sim.addNeuron("label_excitatory",
"izhikevich",
{
"a": 0.2,
"b": 0.2,
"c": -65.0,
"d": ncs.Uniform(7.0, 9.0),
"u": ncs.Uniform(-15.0, -11.0),
"v": ncs.Normal(-60.0, 5.0),
"threshold": 30
}
)
group_1 = sim.addNeuronGroup("group_1", 100, "label_excitatory", None) # last param is geometry
group_2 = sim.addNeuronGroup("group_2", 100, excitatory_parameters)
all_cells = sim.addNeuronAlias("all_cells", [group_1, "group_2"])
sim.addNeuronAlias("all", all_cells)
sim.addNeuronAlias("all_2", "all_cells")
flat_parameters = sim.addSynapse("synapse",
"ncs",
{ "utilization": ncs.Normal(0.5, 0.05),
"redistribution": 1.0,
"last_prefire_time": 0.0,
"last_postfire_time": 0.0,
"tau_facilitation": 0.001,
"tau_depression": 0.001,
"tau_ltp": 0.015,
"tau_ltd": 0.03,
"A_ltp_minimum": 0.003,
"A_ltd_minimum": 0.003,
"max_conductance": 0.004,
"reversal_potential": 0.0,
"tau_postsynaptic_conductance": 0.025,
"psg_waveform_duration": 0.05,
"delay": ncs.Uniform(1,5)
})
all_to_all = sim.addSynapseGroup("all_to_all", all_cells, "all_2", 0.1, flat_parameters)
all_to_all_2 = sim.addSynapseGroup("all_to_all_2",
[group_1, group_2],
"all_2",
0.1,
flat_parameters)
one_to_two = sim.addSynapseGroup("one_to_two",
group_1,
"group_2",
0.1,
"synapse")
all_connections = sim.addSynapseAlias("all_connections", [all_to_all, one_to_two])
if not sim.init(argv):
print "Failed to initialize simulation."
return
sim.addStimulus("rectangular_current", { "amplitude": 18.0 }, group_1, 0.1, 0.0, 0.1)
sim.addStimulus("rectangular_current", { "amplitude": 18.0 }, "all", 0.1, 0.0, 0.2)
sim.addStimulus("rectangular_current", { "amplitude": 18.0 }, "group_2", 0.1, 0.1, 0.3)
voltage_report = sim.addReport("group_1", "neuron", "neuron_voltage", 1.0, 0.0, 0.01)
voltage_report.toAsciiFile("foo.txt")
fire_report = sim.addReport(all_cells, "neuron", "neuron_fire", 1.0, 0.0, 0.01)
fire_report.toStdOut()
current_report = sim.addReport(all_cells, "neuron", "synaptic_current", 1.0, 0.0, 0.01)
current_report.toStdOut()
sim.run(duration=0.5)
del sim
return
def run(argv):
calcium_channel = {
#type of channel
"type": "calcium_dependent",
#starting value, Unit: none
"m_initial": 0.0,
#Unit: mV
"reversal_potential": -80,
"m_power": 2,
#conductance = unitary_g * strength, unit = pS/(cm^2)
"conductance": 6.0 * 0.025,
"forward_scale": 0.000125,
"forward_exponent": 2,
"backwards_rate": 2.5,
"tau_scale": 0.01,
}
ncs_cell = {
"threshold": -47.0,
"resting_potential": -65.0,
#initial calcium concentration (required. default 0)
"calcium": 5.0,
#increment calcium concentration by this value each time the cell spikes
#required. default 0
"calcium_spike_increment": 100.0,
"tau_calcium": 0.08,
#decay time for voltage, Unit:seconds
"tau_membrane": 0.020,
#resistance, Unit ohms
"r_membrane": 180,
"leak_reversal_potential": 0.0,
"leak_conductance": 0.0,
#spike template
"spike_shape": [-38, 30, -38, -43],
#channels
"channels": [
calcium_channel,
],
"capacitance": 1.0,
}
sim = ncs.Simulation()
neuron_parameters = sim.addNeuron("ncs_neuron", "ncs", ncs_cell)
group_1 = sim.addNeuronGroup("group_1", 1, "ncs_neuron", None)
#initialize
if not sim.init(argv):
print "Failed to initialize simulation"
return
#stimulus
#sim.addInput("linear_current",{"starting_amplitude":1.98, "ending_amplitude":1.98,"width":0.3,"time_increment":0.01,"dyn_range": ncs.Uniform(25,60)},group_1,1,0.02,1.0)
sim.addStimulus("linear_current", {
"starting_amplitude": 1.98,
"ending_amplitude": 1.98
}, group_1, 1, 0.02, 1.0)
voltage_report = sim.addReport("group_1", "neuron", "neuron_voltage", 1.0,
0.0, 1.0)
voltage_report.toAsciiFile("./reg_voltage.txt")
current_report = sim.addReport("group_1", "neuron", "input_current", 1.0,
0.0, 1.0)
current_report.toAsciiFile("./reg_current.txt")
sim.run(duration=1.0)
del sim
return
def Run(argv):
ak = 10.0 / (100.0 * (math.exp(1.0) - 1))
bk = 0.125
tk = 1.0 / (ak + bk)
xk0 = ak * tk
potassium_channel = {
"type": "voltage_gated",
"conductance": 36.0,
"reversal_potential": -72.0,
"particles": [
{ #n
"x_initial": xk0,
"alpha": {
"a": 0.5,
"b": 0.01,
"c": 1.0,
"d": 50.0,
"f": -10.0,
"h": -1.0,
},
"beta": {
"a": 0.125,
"b": 0.0,
"c": 0.0,
"d": 60.0,
"f": 80.0,
"h": 1.0,
},
"power": 4.0,
}
],
}
am = 25.0 / (10.0 * (math.exp(2.5) - 1.0))
bm = 4.0
tm = 1.0 / (am + bm)
xm0 = am * tm
ah = 0.07
bh = 1.0 / (math.exp(3.0) + 1)
th = 1.0 / (ah + bh)
xh0 = ah * th
sodium_activation = {
"x_initial": xm0,
"alpha": {
"a": 3.5,
"b": 0.1,
"c": 1.0,
"d": 35.0,
"f": -10.0,
"h": -1.0,
},
"beta": {
"a": 4.0,
"b": 0.0,
"c": 0.0,
"d": 60.0,
"f": 18.0,
"h": 1.0,
},
"power": 3.0,
}
sodium_deactivation = {
"x_initial": xh0,
"alpha": {
"a": 0.07,
"b": 0.0,
"c": 0.0,
"d": 60.0,
"f": 20.0,
"h": 1.0,
},
"beta": {
"a": 1.0,
"b": 0.0,
"c": 1.0,
"d": 30.0,
"f": -10.0,
"h": 1.0,
},
"power": 1.0,
}
sodium_channel = {
"type": "voltage_gated",
"conductance": 120.0,
"reversal_potential": 55.0,
"particles": [sodium_activation, sodium_deactivation],
}
leak_channel = {
"type": "voltage_gated",
"conductance": 0.3,
"reversal_potential": 10.6 - 60.0,
"particles": [
{ #m
"x_initial": 1.0,
"alpha": {
"a": 1.0,
"b": 0.0,
"c": 1.0,
"d": 0.0,
"f": 0.0,
"h": 0.0,
},
"beta": {
"a": 1.0,
"b": 0.0,
"c": 1.0,
"d": 0.0,
"f": 0.0,
"h": 0.0,
},
"power": 1.0,
}
],
}
hh_cell = {
"threshold": -50.0,
"resting_potential": -60.0,
"capacitance": 1.0,
"channels": [potassium_channel, sodium_channel, leak_channel]
}
sim = ncs.Simulation()
neuron_parameters = sim.addNeuron("hh_neuron", "hh", hh_cell)
group_1 = sim.addNeuronGroup("group_1", 1, "hh_neuron",
None) # last param is geometry
all_cells = sim.addNeuronAlias("all_cells", [group_1])
sim.addNeuronAlias("all", all_cells)
sim.addNeuronAlias("all_2", "all_cells")
if not sim.init(argv):
print "Failed to initialize simulation."
return
sim.addStimulus("rectangular_current", {"amplitude": 10.0}, group_1, 1.0,
0.0, 1.0)
voltage_report = sim.addReport("group_1", "neuron", "neuron_voltage", 1.0,
0.0, 0.5)
#voltage_report.toAsciiFile("/tmp/voltages.txt")
voltage_report.toStdOut()
sim.run(duration=0.500)
return
def run(argv):
voltage_channel = {
"type": "voltage_gated_ion",
"m_initial": 0.0,
"reversal_potential": -80,
"v_half": -44,
"deactivation_slope": 40,
"activation_slope": 20,
"equilibrium_slope": 8.8,
"r": 1.0 / 0.303,
"conductance": 5 * 0.00015
}
calcium_channel = {
"type": "calcium_dependent",
"m_initial": 0.0,
"reversal_potential": -80,
"m_power": 2,
"conductance": 6.0 * 0.0009,
"forward_scale": 0.000125,
"forward_exponent": 2,
"backwards_rate": 2.5,
"tau_scale": 0.01,
}
ncs_cell = {
"threshold": -50.0,
"resting_potential": -60.0,
"calcium": 5.0,
"calcium_spike_increment": 100.0,
"tau_calcium": 0.07,
"leak_reversal_potential": 0.0,
"leak_conductance":0.0 ,
"tau_membrane": 0.02,
"r_membrane": 200.0,
"spike_shape": [
-38, 30, -43, -60, -60
],
"capacitance": 1.0,
"channels": [
voltage_channel,
calcium_channel,
]
}
sim = ncs.Simulation()
neuron_parameters = sim.addNeuron("ncs_neuron",
"ncs",
ncs_cell
)
group_1 = sim.addNeuronGroup("group_1", 100, "ncs_neuron", None) # last param is geometry
all_cells = sim.addNeuronAlias("all_cells", [group_1])
sim.addNeuronAlias("all", all_cells)
sim.addNeuronAlias("all_2", "all_cells")
if not sim.init(argv):
print "Failed to initialize simulation."
return
sim.addStimulus("rectangular_current", { "amplitude": 0.1 }, group_1, 1.0, 0.0, 1.0)
#voltage_report = sim.addReport("group_1", "neuron", "neuron_voltage", 1.0)
#voltage_report.toAsciiFile("/tmp/voltages.txt")
#voltage_report.toStdOut()
sim.run(duration = 1.0)
del sim
return
