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A C. elegans neuron connectome simulator

Analyze C. elegans neuron activity
based on networkx 3.0


Connectome.py

1 Class Neuron(name:str | transmitter_weight = 1 | cat:str | transmitter:str | co_transmitter:str)

1.1 Attribute

  • name:str| Name of the neuron
  • cat:str | Category of 'sensory','interneuron','motorneuron'
  • transmitter,co_transmitter:str | neuron transmitter
  • pre,post:list | list of pre/post neuron synapses (see "Class Synapse")
  • ej:list | list of gap junctions (see "Class GapJunc")

1.2 Method

pass


Class Synapse(weight:float | pre:str | post:str | transmitter:str | co:str)

1.1 Attribute

  • pre/post:str | name of pre/post synaptic neurons
  • transmitter/co_transmitter":str | neuron transmitter of the post synaptic cell
  • weight:float | 1/(number of synapses between pre-post neurons)
  • ele:bool | is electric synapse or not

1.2 Method

pass


Class GapJunc(factor:float | weight:float | pre:str | post:str | transmitter:str | co:str)

define this class for the switch of the weight of gap junction

1.1 Attribute

class GapJunc(Synapse):
    super().__init__
  • gap_weight:float | factor(default=1) * self.weight

1.2 Method

pass


Class NetWork(neuron_list:dict)

1.1 Attribute

  • neurons:dict | dictionary {name:class Neuron}
  • G:MultiDiGraph | networkx MultiDiGraph of all synapse
  • G_ej:MultiDiGraph | networkx MultiDiGraph of gap junction
  • G_chem:MultiDiGraph | networkx MultiDiGraph of chemical synapse

1.2 Method

1.2.1 add_neuron(self,neuron_lst)

append a novel neuron list to the attribute-neurons


1.2.2 construct(self)

construct the self.G/self.G_ej/self.G_chem


1.2.3 total_plot(self,with_labels:bool = False,node_size:float = 20,width:float = 0.3)

plot self.G with gap junction colored 'deepskyblue' and chemical synapses colored 'coral'


1.2.4 gap_plot/chem_plot(self)

plot self.G_ej/self.G_chem


1.2.5 ablation(self,name:str)

return a copy of the network with a neuron deleted


1.2.6 sub_network(self,name_lst:list)

return a copy of the network constructed with the selected neurons in the name_lst

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