Spikelet generation and AP initiation in a L5 neocortical pyr neuron (Michalikova et al. 2017) Fig 1

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Accession:206398
The article by Michalikova et al. (2017) explores the generation of spikelets in cortical pyramidal neurons. The model cell, adapted from Hu et al. (2009), is a layer V pyramidal neuron. The cell is stimulated by fluctuating synaptic inputs and generates somatic APs and spikelets in response. The spikelets are initiated as APs at the AIS that do not activate the soma.
Reference:
1 . Michalikova M, Remme MW, Kempter R (2017) Spikelets in Pyramidal Neurons: Action Potentials Initiated in the Axon Initial Segment That Do Not Activate the Soma. PLoS Comput Biol 13:e1005237 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Axon;
Brain Region(s)/Organism:
Cell Type(s): Neocortex L5/6 pyramidal GLU cell;
Channel(s): I Na,t;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; Python;
Model Concept(s): Action Potentials; Electrotonus; Action Potential Initiation; Axonal Action Potentials;
Implementer(s): Michalikova, Martina [tinka.michalikova at gmail.com];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; I Na,t;
/* ----------------------------------------------------------------
    Define the Axon Geometry
    
    Layer 5 cortical pyramidal cell has a long unmyelinated axon!
    Similar to Mainen et al (Neuron, 1995)
------------------------------------------------------------------*/ 

n_myelin = 14  // number of myelins and nodes
create ais[2],hill,nakeaxon,myelin[2],node[2]  // forward declaration

proc create_axon() {

  create ais[10],hill,nakeaxon,myelin[n_myelin],node[n_myelin]
  
  // Acquire the equivalent diameter of soma
  soma {  equiv_diam = sqrt(area(0.5)*nseg/(4*PI))  }   // "*nseg" is needed !!
  if (numarg()) equiv_diam = $1
  
  // Set axonal diameters
  diamAis=equiv_diam/10
  diamNakeAxon=equiv_diam/12  
  diamMyelin=diamAis*1.
  diamNode=diamAis*0.75    // nodes are thinner than axon

  // Initial segment

hill {                                          
    L = 10                          
    nseg = 10                           
    diam(   0   :   0.25    ) =     6   :   3.8
    diam(   0.25    :   0.5 ) =     3.8 :   2.8
    diam(   0.5 :   0.75    ) =     2.8 :   1.7
    diam(   0.75    :   1   ) =     1.7 :   1.3
                                
  }                         
                
                            
for i=0,9 ais[i] {                 
    L = 5
    nseg = 10
    diam = 1.22
  }

/* diameters in the original Hu-model
ais[0]  {                       
    diam(   0   :   1   ) =     1.7 :   1.5
    }                       
                            
ais[1]  {                       
    diam(   0   :   1   ) =     1.5 :   1.22
    }         
*/

/* MM: changed diameters of ais[0] and ais[1] to avoid the discontinuity at the hill-ais boundary */

ais[0]  {  
    diam(   0   :   1   ) =     1.3 :   1.22
    }
    
    
  // Unmylined axon
  nakeaxon {                
    L = 400
    nseg = 100
    diam = diamNakeAxon
  }

  // Myelinated axon with nodes of Ranvier
  for i=0,n_myelin-1 {
    myelin[i] {         // myelin element
      nseg = 5
      L = 100
      diam = diamMyelin    
    }
    node[i] {           // nodes of Ranvier
      nseg = 1
      L = 1           
      diam = diamNode     
    }
  }

  // Connecting
  
  soma connect hill(0), axonOnSoma       // dend11 -> soma(0) -> soma(1) -> hill
  hill connect ais[0] (0), 1      // hill -> ais[0]
  for i=0,8 ais[i] {              // ais[0] -> ... -> ais[9]
    connect ais[i+1] (0), 1
  }
  ais[9] connect nakeaxon(0), 1        // ais[9] -> nakeaxon
  nakeaxon connect myelin[0] (0), 1    // nakeaxon -> myelin[0]
  myelin[0] connect node[0](0), 1            // myelin[0] -> node[0]
  for i=1,n_myelin-1  {                    // (myelin[0] node[0]) -> ... -> (myelin[n_myelin] node[n_myelin]) 
      node[i-1] connect myelin[i](0), 1 
      myelin[i] connect node[i](0), 1
  }

}

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