def connect_to_input(self, source: Nucleus):
source.nuclei(Neurotransmitters.GLU.value).connect(
nucleus=self.__structure[0].get_right_group().nuclei(Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=Weights.MR.value,
conn_type=ConnectionTypes.ALL_TO_ALL.value
)
def __init__(self, index: int):
self.index = index
self.left_excitatory = Nucleus(
nucleus_name='HiddenTier{}LeftExcitatory'.format(self.index))
self.right_excitatory = Nucleus(
nucleus_name='HiddenTier{}RightExcitatory'.format(self.index))
self.right_inhibitory = Nucleus(
nucleus_name='HiddenTier{}RightInhibitory'.format(self.index))
self.left_inhibitory = Nucleus(
nucleus_name='HiddenTier{}LeftInhibitory'.format(self.index))
self.left_excitatory.addSubNucleus(
neurotransmitter=Neurotransmitters.GLU.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.right_excitatory.addSubNucleus(
neurotransmitter=Neurotransmitters.GLU.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.left_inhibitory.addSubNucleus(
neurotransmitter=Neurotransmitters.GABA.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.right_inhibitory.addSubNucleus(
neurotransmitter=Neurotransmitters.GABA.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.add_neurons(Constants.NEURONS_IN_GROUP.value * 4)
def connect_output_to_pool(self, pool: Nucleus):
for tier in self.__structure:
tier.get_left_group().nuclei(Neurotransmitters.GLU.value).connect(
nucleus=pool.nuclei(Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=Weights.LIP.value[tier.get_tier()+1],
conn_type=ConnectionTypes.ALL_TO_ALL.value
)
def connect_spike_generator(target: Nucleus):
spike_generator = api_kernel.NEST.Create(
'spike_generator', 1, {
'spike_times': Constants.SPIKE_GENERATOR_TIMES.value,
'spike_weights': Constants.SPIKE_GENERATOR_WEIGHTS.value
})
api_kernel.NEST.Connect(
spike_generator,
target.nuclei(Neurotransmitters.GLU.value).getNeurons())
def __init__(self):
self.polysynaptic_circuit = PolysynapticCircuit()
self.mediator = Nucleus('Mediator')
self.interneuronal_pool = Nucleus('InterneuronalPool')
self.mediator.addSubNucleus(
neurotransmitter=Neurotransmitters.GLU.value,
number=1,
params=Neurons.NEUCOGAR.value)
self.interneuronal_pool.addSubNucleus(
neurotransmitter=Neurotransmitters.GLU.value,
number=1,
params=Neurons.NEUCOGAR.value)
CreateNetwork(simulation_neuron_number=PolysynapticCircuit.
get_number_of_neurons() + 2)
self.set_connections()
self.connect_multimeters()
self.connect_spike_generator()
def __init__(self, index: int):
"""
Args:
index: a number of the index in order
"""
self.index = index
self.left_group = Nucleus(nucleus_name='Tier{}Left'.format(index))
self.left_group.addSubNucleus(
neurotransmitter=Neurotransmitters.GLU.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.right_group = Nucleus(nucleus_name='Tier{}Right'.format(index))
self.right_group.addSubNucleus(
neurotransmitter=Neurotransmitters.GLU.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.inhibitory_group = Nucleus(
nucleus_name='Tier{}Inhibitory'.format(index))
self.inhibitory_group.addSubNucleus(
neurotransmitter=Neurotransmitters.GABA.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.add_neurons(Constants.NEURONS_IN_GROUP.value * 3)
def __init__(self, tier, inhibitory_group=False):
self.tier = tier
self.left_group = Nucleus(nucleus_name='Tier{}Left'.format(tier))
self.left_group.addSubNucleus(
neurotransmitter=Neurotransmitters.GLU.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.right_group = Nucleus(nucleus_name='Tier{}Right'.format(tier))
self.right_group.addSubNucleus(
neurotransmitter=Neurotransmitters.GLU.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
if inhibitory_group:
self.inhibitory_group = Nucleus(
nucleus_name='Tier{}Inhibitory'.format(tier))
self.inhibitory_group.addSubNucleus(
neurotransmitter=Neurotransmitters.GABA.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.right_group.nuclei(Neurotransmitters.GLU.value).connect(
nucleus=self.left_group.nuclei(Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=Weights.RL.value.reverse()[tier - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
self.left_group.nuclei(Neurotransmitters.GLU.value).connect(
nucleus=self.right_group.nuclei(Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=Weights.LR.value.reverse()[tier - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
if inhibitory_group:
self.inhibitory_group.nuclei(Neurotransmitters.GABA.value).connect(
nucleus=self.right_group.nuclei(Neurotransmitters.GLU.value),
synapse=Synapses.GABAERGIC.value,
weight=Weights.IR.value.reverse()[tier - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
from neucogar.namespaces import *
from neucogar.Nucleus import Nucleus
from neucogar.api_kernel import CreateNetwork
from .parameters import *
hippocampus = Nucleus("Hippocampus")
hippocampus.addSubNucleus(Glu, params=nrn_parameters,
number=5000) # ToDo Check
hippocampus.addSubNucleus(GABA, params=nrn_parameters,
number=1000) # ToDo Check
amygdala = Nucleus("Amygdala")
amygdala.addSubNucleus(Glu, params=nrn_parameters,
number=3000) # ToDo not real
hypothalamus = Nucleus("Hypothalamus")
hypothalamus.addSubNucleus(Glu, params=nrn_parameters,
number=1000) # ToDo not real
hypothalamus.addSubNucleus(GABA, params=nrn_parameters,
number=1000) # ToDo not real
drn = Nucleus("Raphe nucleus")
drn.addSubNucleus(HT5, params=nrn_parameters, number=15000)
drn.addSubNucleus(GABA, params=nrn_parameters, number=1000) # ToDo not real
locus_coeruleus = Nucleus("Locus coeruleus")
locus_coeruleus.addSubNucleus(NA, params=nrn_parameters, number=1500)
CreateNetwork(28000)
def __init__(self, column_index):
# Create Nucleus objects and put into the dict of the layers
self._dict_layers = {
L2: Nucleus("Column {} Layer 2".format(column_index)),
L3: Nucleus("Column {} Layer 3".format(column_index)),
L4: Nucleus("Column {} Layer 4".format(column_index)),
L5A: Nucleus("Column {} Layer 5A".format(column_index)),
L5B: Nucleus("Column {} Layer 5B".format(column_index)),
L6: Nucleus("Column {} Layer 6".format(column_index))
}
# Add sub-nucleui and create neurons without sqaling (because of flag 'forColumns'=True)
self.layers(L2).addSubNucleus(Glu,
number=546,
params=self._nrn_parameters,
forColumns=True)
self.layers(L2).addSubNucleus(GABA,
number=107,
params=self._nrn_parameters,
forColumns=True)
self.layers(L3).addSubNucleus(Glu,
number=1145,
params=self._nrn_parameters,
forColumns=True)
self.layers(L3).addSubNucleus(GABA,
number=123,
params=self._nrn_parameters,
forColumns=True)
self.layers(L4).addSubNucleus(Glu,
number=1656,
params=self._nrn_parameters,
forColumns=True)
self.layers(L4).addSubNucleus(GABA,
number=140,
params=self._nrn_parameters,
forColumns=True)
self.layers(L5A).addSubNucleus(Glu,
number=454,
params=self._nrn_parameters,
forColumns=True)
self.layers(L5A).addSubNucleus(GABA,
number=90,
params=self._nrn_parameters,
forColumns=True)
self.layers(L5B).addSubNucleus(Glu,
number=641,
params=self._nrn_parameters,
forColumns=True)
self.layers(L5B).addSubNucleus(GABA,
number=131,
params=self._nrn_parameters,
forColumns=True)
self.layers(L6).addSubNucleus(Glu,
number=1288,
params=self._nrn_parameters,
forColumns=True)
self.layers(L6).addSubNucleus(GABA,
number=127,
params=self._nrn_parameters,
forColumns=True)
# Invoke method to create synapses
self.setConnectomes()
class Tier:
def __init__(self, tier, inhibitory_group=False):
self.tier = tier
self.left_group = Nucleus(nucleus_name='Tier{}Left'.format(tier))
self.left_group.addSubNucleus(
neurotransmitter=Neurotransmitters.GLU.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.right_group = Nucleus(nucleus_name='Tier{}Right'.format(tier))
self.right_group.addSubNucleus(
neurotransmitter=Neurotransmitters.GLU.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
if inhibitory_group:
self.inhibitory_group = Nucleus(
nucleus_name='Tier{}Inhibitory'.format(tier))
self.inhibitory_group.addSubNucleus(
neurotransmitter=Neurotransmitters.GABA.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.right_group.nuclei(Neurotransmitters.GLU.value).connect(
nucleus=self.left_group.nuclei(Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=Weights.RL.value.reverse()[tier - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
self.left_group.nuclei(Neurotransmitters.GLU.value).connect(
nucleus=self.right_group.nuclei(Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=Weights.LR.value.reverse()[tier - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
if inhibitory_group:
self.inhibitory_group.nuclei(Neurotransmitters.GABA.value).connect(
nucleus=self.right_group.nuclei(Neurotransmitters.GLU.value),
synapse=Synapses.GABAERGIC.value,
weight=Weights.IR.value.reverse()[tier - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
def connect_to_tier(self, tier):
"""
Connects this tier to another tier
Args:
tier: Tier
Returns:
bool
"""
if self.tier - tier.get_tier() == 1:
self.left_group.nuclei(Neurotransmitters.GLU.value).connect(
nucleus=tier.get_left_group().nuclei(
Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=Weights.LL.value.reverse()[tier.get_tier() - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
tier.right_group().nuclei(Neurotransmitters.GLU.value).connect(
nucleus=self.right_group.nuclei(Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=Weights.RR.value.reverse()[tier.get_tier() - 2],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
self.right_group.nuclei(Neurotransmitters.GLU.value).connect(
nucleus=tier.get_inhibitory_group().nuclei(
Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=Weights.RI.value.reverse()[tier.get_tier() - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
return True
else:
return False
def get_tier(self):
return self.tier
def get_left_group(self):
return self.left_group
def get_right_group(self):
return self.right_group
def get_inhibitory_group(self):
return self.inhibitory_group if self.inhibitory_group else None
class Layer2:
def __init__(self):
self.polysynaptic_circuit = PolysynapticCircuit()
self.mediator = Nucleus('Mediator')
self.interneuronal_pool = Nucleus('InterneuronalPool')
self.mediator.addSubNucleus(
neurotransmitter=Neurotransmitters.GLU.value,
number=1,
params=Neurons.NEUCOGAR.value)
self.interneuronal_pool.addSubNucleus(
neurotransmitter=Neurotransmitters.GLU.value,
number=1,
params=Neurons.NEUCOGAR.value)
CreateNetwork(simulation_neuron_number=PolysynapticCircuit.
get_number_of_neurons() + 2)
self.set_connections()
self.connect_multimeters()
self.connect_spike_generator()
def set_connections(self):
self.mediator.nuclei(Neurotransmitters.GLU.value).connect(
nucleus=self.polysynaptic_circuit.get_input().nuclei(
Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=Weights.MR.value,
conn_type=ConnectionTypes.ALL_TO_ALL.value)
for tier, weight in zip(self.polysynaptic_circuit.get_output(),
Weights.LIP.value[::-1]):
tier.nuclei(Neurotransmitters.GLU.value).connect(
nucleus=self.interneuronal_pool.nuclei(
Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=weight,
conn_type=ConnectionTypes.ALL_TO_ALL.value)
for tier in self.polysynaptic_circuit.get_tiers():
tier.set_connections()
for hidden_tier in self.polysynaptic_circuit.get_hidden_tiers():
hidden_tier.set_connections()
self.polysynaptic_circuit.set_connections()
def connect_multimeters(self):
self.mediator.nuclei(Neurotransmitters.GLU.value).ConnectMultimeter()
self.interneuronal_pool.nuclei(
Neurotransmitters.GLU.value).ConnectMultimeter()
for tier in self.polysynaptic_circuit.get_tiers():
tier.connect_multimeters()
for hidden_tier in self.polysynaptic_circuit.get_hidden_tiers():
hidden_tier.connect_multimeters()
def connect_spike_generator(self):
spike_generator = api_kernel.NEST.Create(
'spike_generator', 1, {
'spike_times': Constants.SPIKE_GENERATOR_TIMES.value,
'spike_weights': Constants.SPIKE_GENERATOR_WEIGHTS.value
})
api_kernel.NEST.Connect(
spike_generator,
self.mediator.nuclei(Neurotransmitters.GLU.value).getNeurons())
def __init__(self):
layer2 = Layer2()
mediator = Nucleus(nucleus_name='Mediator')
mediator.addSubNucleus(neurotransmitter=Neurotransmitters.GLU.value,
number=1,
params=Neurons.NEUCOGAR.value)
mediator.ConnectMultimeter()
mediator.ConnectDetector()
connect_spike_generator(mediator)
layer2.connect_to_input(mediator)
interneuronal_pool = Nucleus(nucleus_name='Interneuronal_Pool')
interneuronal_pool.addSubNucleus(
neurotransmitter=Neurotransmitters.GLU.value,
number=1,
params=Neurons.NEUCOGAR.value)
interneuronal_pool.ConnectMultimeter()
interneuronal_pool.ConnectDetector()
layer2.connect_output_to_pool(interneuronal_pool)
class Tier:
__number_of_neurons = 0
@classmethod
def add_neurons(cls, number: int):
cls.__number_of_neurons += number
@classmethod
def get_number_of_neurons(cls):
return cls.__number_of_neurons
def __init__(self, index: int):
"""
Args:
index: a number of the index in order
"""
self.index = index
self.left_group = Nucleus(nucleus_name='Tier{}Left'.format(index))
self.left_group.addSubNucleus(
neurotransmitter=Neurotransmitters.GLU.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.right_group = Nucleus(nucleus_name='Tier{}Right'.format(index))
self.right_group.addSubNucleus(
neurotransmitter=Neurotransmitters.GLU.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.inhibitory_group = Nucleus(
nucleus_name='Tier{}Inhibitory'.format(index))
self.inhibitory_group.addSubNucleus(
neurotransmitter=Neurotransmitters.GABA.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.add_neurons(Constants.NEURONS_IN_GROUP.value * 3)
def connect_multimeters(self):
self.right_group.nuclei(
Neurotransmitters.GLU.value).ConnectMultimeter()
self.left_group.nuclei(Neurotransmitters.GLU.value).ConnectMultimeter()
self.inhibitory_group.nuclei(
Neurotransmitters.GABA.value).ConnectMultimeter()
def set_connections(self):
# connect right group to left group
self.right_group.nuclei(Neurotransmitters.GLU.value).connect(
nucleus=self.left_group.nuclei(Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=Weights.RL.value[::-1][self.get_index() - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
# connect left group to right group
self.left_group.nuclei(Neurotransmitters.GLU.value).connect(
nucleus=self.right_group.nuclei(Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=Weights.LR.value[::-1][self.get_index() - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
# connect inhibitory group to right group
self.inhibitory_group.nuclei(Neurotransmitters.GABA.value).connect(
nucleus=self.right_group.nuclei(Neurotransmitters.GLU.value),
synapse=Synapses.GABAERGIC.value,
weight=Weights.IR.value[::-1][self.get_index() - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
# connect right group to inhibitory group
self.right_group.nuclei(Neurotransmitters.GLU.value).connect(
nucleus=self.inhibitory_group.nuclei(Neurotransmitters.GABA.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=Weights.RI.value[::-1][self.get_index() - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
def connect(self, tier):
"""
Connects this tier to a lower tier
Args:
tier (Tier): a lower tier
Returns:
bool
"""
if self.index - tier.get_index() == 1:
self.left_group.nuclei(Neurotransmitters.GLU.value).connect(
nucleus=tier.get_left_group().nuclei(
Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=Weights.LL.value[::-1][tier.get_index() - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
tier.get_right_group().nuclei(Neurotransmitters.GLU.value).connect(
nucleus=self.right_group.nuclei(Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=Weights.RR.value[::-1][tier.get_index() - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
return True
else:
return False
def get_index(self):
return self.index
def get_left_group(self):
return self.left_group
def get_right_group(self):
return self.right_group
def get_inhibitory_group(self):
return self.inhibitory_group
class HiddenTier:
__number_of_neurons = 0
@classmethod
def add_neurons(cls, number: int):
cls.__number_of_neurons += number
@classmethod
def get_number_of_neurons(cls):
return cls.__number_of_neurons
def __init__(self, index: int):
self.index = index
self.left_excitatory = Nucleus(
nucleus_name='HiddenTier{}LeftExcitatory'.format(self.index))
self.right_excitatory = Nucleus(
nucleus_name='HiddenTier{}RightExcitatory'.format(self.index))
self.right_inhibitory = Nucleus(
nucleus_name='HiddenTier{}RightInhibitory'.format(self.index))
self.left_inhibitory = Nucleus(
nucleus_name='HiddenTier{}LeftInhibitory'.format(self.index))
self.left_excitatory.addSubNucleus(
neurotransmitter=Neurotransmitters.GLU.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.right_excitatory.addSubNucleus(
neurotransmitter=Neurotransmitters.GLU.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.left_inhibitory.addSubNucleus(
neurotransmitter=Neurotransmitters.GABA.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.right_inhibitory.addSubNucleus(
neurotransmitter=Neurotransmitters.GABA.value,
number=Constants.NEURONS_IN_GROUP.value,
params=Neurons.NEUCOGAR.value)
self.add_neurons(Constants.NEURONS_IN_GROUP.value * 4)
def connect_multimeters(self):
self.left_excitatory.nuclei(
Neurotransmitters.GLU.value).ConnectMultimeter()
self.right_excitatory.nuclei(
Neurotransmitters.GLU.value).ConnectMultimeter()
self.left_inhibitory.nuclei(
Neurotransmitters.GABA.value).ConnectMultimeter()
self.right_inhibitory.nuclei(
Neurotransmitters.GABA.value).ConnectMultimeter()
def set_connections(self):
self.left_excitatory.nuclei(Neurotransmitters.GLU.value).connect(
nucleus=self.right_excitatory.nuclei(Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=HiddenWeights.LR.value[::-1][self.index - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
self.right_excitatory.nuclei(Neurotransmitters.GLU.value).connect(
nucleus=self.left_excitatory.nuclei(Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=HiddenWeights.RL.value[::-1][self.index - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
self.right_excitatory.nuclei(Neurotransmitters.GLU.value).connect(
nucleus=self.left_inhibitory.nuclei(Neurotransmitters.GABA.value),
synapse=Synapses.GABAERGIC.value,
weight=HiddenWeights.RI.value[::-1][self.index - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
self.left_inhibitory.nuclei(Neurotransmitters.GABA.value).connect(
nucleus=self.right_excitatory.nuclei(Neurotransmitters.GLU.value),
synapse=Synapses.GABAERGIC.value,
weight=HiddenWeights.IR.value[::-1][self.index - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
def get_index(self):
return self.index
def get_right_excitatory(self):
return self.right_excitatory
def get_right_inhibitory(self):
return self.right_inhibitory
def connect(self, upper_tier: Tier, lower_tier: Tier):
self.get_right_excitatory().nuclei(
Neurotransmitters.GLU.value).connect(
nucleus=upper_tier.get_right_group().nuclei(
Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=HiddenWeights.RRU.value[::-1][self.get_index() - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
self.get_right_inhibitory().nuclei(
Neurotransmitters.GABA.value).connect(
nucleus=lower_tier.get_right_group().nuclei(
Neurotransmitters.GLU.value),
synapse=Synapses.GABAERGIC.value,
weight=HiddenWeights.IRD.value[::-1][self.get_index() - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
upper_tier.get_right_group().nuclei(
Neurotransmitters.GLU.value).connect(
nucleus=self.get_right_inhibitory().nuclei(
Neurotransmitters.GABA.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=HiddenWeights.RID.value[::-1][self.get_index() - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
lower_tier.get_right_group().nuclei(
Neurotransmitters.GLU.value).connect(
nucleus=self.get_right_excitatory().nuclei(
Neurotransmitters.GLU.value),
synapse=Synapses.GLUTAMATERGIC.value,
weight=HiddenWeights.RDR.value[::-1][self.get_index() - 1],
conn_type=ConnectionTypes.ONE_TO_ONE.value)
from neucogar.Nucleus import Nucleus
from neucogar.api_kernel import CreateNetwork
from neucogar.namespaces import *
from parameters import *
motor_cortex = Nucleus("Motor cortex")
motor_cortex.addSubNucleus(Glu_0, params=nrn_parameters, number=3866666)
motor_cortex.addSubNucleus(Glu_1, params=nrn_parameters, number=966666)
thalamus = Nucleus("Thalamus")
thalamus.addSubNucleus(Glu, params=nrn_parameters, number=833333)
striatum = Nucleus("Striatum")
striatum.addSubNucleus(GABA_D1, params=nrn_parameters, number=1062500)
striatum.addSubNucleus(GABA_D2, params=nrn_parameters, number=1062500)
gpe = Nucleus("GPe")
gpe.addSubNucleus(GABA, params=nrn_parameters, number=84100)
gpi = Nucleus("GPi")
gpi.addSubNucleus(GABA, params=nrn_parameters, number=12600)
stn = Nucleus("STN")
stn.addSubNucleus(Glu, params=nrn_parameters, number=22700)
snr = Nucleus("SNr")
snr.addSubNucleus(GABA, params=nrn_parameters, number=47200)
snc = Nucleus("SNc")
snc.addSubNucleus(DA, params=nrn_parameters, number=12700)