class_docstr: !
  @brief Central element consist of two central neurons that are described by a little bit different dynamic than peripheral.
  
  @see hhn_network
class_docstr_tok: ["!","@","brief","Central","element","consist","of","two","central","neurons","that","are","described","by","a","little","bit","different","dynamic","than","peripheral",".","@","see","hhn_network"]
docstr: !
  @brief Constructor of central element.
docstr_tok: ["!","@","brief","Constructor","of","central","element","."]
code: def __init__(self):
      """!
      @brief Constructor of central element.
  
      """
  
      ## Membrane potential of cenral neuron (V).
      self.membrane_potential = 0.0
  
      ## Activation conductance of the sodium channel (m).
      self.active_cond_sodium = 0.0
  
      ## Inactivaton conductance of the sodium channel (h).
      self.inactive_cond_sodium = 0.0
  
      ## Activaton conductance of the sodium channel (h).
      self.active_cond_potassium = 0.0
  
      ## Spike generation of central neuron.
      self.pulse_generation = False
  
      ## Timestamps of generated pulses.
      self.pulse_generation_time = []
  
imports: from scipy.integrate import odeint
  from pyclustering.core.wrapper import ccore_library
  import pyclustering.core.hhn_wrapper
  from pyclustering.nnet import *
  from pyclustering.utils import allocate_sync_ensembles
  import numpy
  import random
label_desc: Use image node_id 1 to create a new central_element object  with example: obj = central_element()