Neocort. pyramidal cells subthreshold somatic voltage controls spike propagation (Munro Kopell 2012)

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Accession:136309
There is suggestive evidence that pyramidal cell axons in neocortex may be coupled by gap junctions into an ``axonal plexus" capable of generating Very Fast Oscillations (VFOs) with frequencies exceeding 80 Hz. It is not obvious, however, how a pyramidal cell in such a network could control its output when action potentials are free to propagate from the axons of other pyramidal cells into its own axon. We address this problem by means of simulations based on 3D reconstructions of pyramidal cells from rat somatosensory cortex. We show that somatic depolarization enables propagation via gap junctions into the initial segment and main axon, while somatic hyperpolarization disables it. We show further that somatic voltage cannot effectively control action potential propagation through gap junctions on minor collaterals; action potentials may therefore propagate freely from such collaterals regardless of somatic voltage. In previous work, VFOs are all but abolished during the hyperpolarization phase of slow-oscillations induced by anesthesia in vivo. This finding constrains the density of gap junctions on collaterals in our model and suggests that axonal sprouting due to cortical lesions may result in abnormally high gap junction density on collaterals, leading in turn to excessive VFO activity and hence to epilepsy via kindling.
Reference:
1 . Munro E, Kopell N (2012) Subthreshold somatic voltage in neocortical pyramidal cells can control whether spikes propagate from the axonal plexus to axon terminals: a model study. J Neurophysiol 107:2833-52 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell; Axon;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex L5/6 pyramidal GLU cell; Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell;
Channel(s): I Na,t; I K; I Sodium; I Potassium;
Gap Junctions: Gap junctions;
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; MATLAB;
Model Concept(s): Oscillations; Detailed Neuronal Models; Axonal Action Potentials; Epilepsy;
Implementer(s): Munro, Erin [ecmun at math.bu.edu];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell; I Na,t; I K; I Sodium; I Potassium;
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Munro_Kopell_corticalcontrol
NEURON
cell_geoms
run_files
readme.txt
extrema.mod
gap.mod
k2_Traub.mod *
ka_Traub.mod *
kdr_Jonas.mod
kdr_Traub.mod
kdr_Yu.mod
naf_Jonas.mod
naf_Traub.mod
naf_Yu.mod
pas_basket.mod
pas_chand.mod
030625DS2.hoc
axon_templates.hoc
C040896A-P3.hoc
C040896A-P3axgeom.hoc
C230797B-P4.hoc
C270999B-P2axgeom.hoc
C280199C-P1.hoc
C290500C-P1axgeom.hoc
cell_templates.hoc
expcell_templates.hoc
gap_junction.hoc
gj_propagation_test.ses
junction_stats.hoc
kinetics.hoc
kinetics_wholecell.hoc
mosinit.hoc
propagation_test.ses
PropagationSearch.hoc
simulation_base.hoc
vs-arg_cutoff.hoc
vs-arg_cutoff_Jonas.hoc
vs-expcell_gj.hoc
vs-expcell_gj_gL.hoc
vs-expcell_gj_Jonas.hoc
vs-expcell_gjCC.hoc
vs-expcell_gjISgNa.hoc
vs-expcell_gjsISgNa.hoc
vs-generic_cutoff.hoc
vs-generic_cutoff_Jonas.hoc
                            
proc insert_Traub(){
  forall {
    insert pas
    g_pas =   1/1000
    //g_pas =   mu*0.001
    e_pas = -70
    Ra =   100.0
    cm = 0.9
    insert nafTraub
    gbar_nafTraub =   0.45
    ena = 50
    insert kdrTraub
    gbar_kdrTraub =   0.45
    ek = -95
       //insert ka
       //gbar_ka =   0.002
       //insert k2
       //gbar_k2 =   0.0001
  }
  tstop = 20
}

proc uninsert_Traub(){
    forall {
        uninsert pas
        uninsert nafTraub
        uninsert kdrTraub
    }
}

proc insert_modTraub(){local IS localobj cell
    forall {
        insert pas
        g_pas =   0.001
        e_pas = -70
        Ra =   100.0
        cm = 0.9
        insert nafTraub
        gbar_nafTraub =   0.2
        ena = 50
        insert kdrTraub
        gbar_kdrTraub =   0.2
        ek = -95
    }
    cell = $o1
    IS = $2
    cell.axon[IS]{
        for(x,0){
            if(x*L<40){
                gbar_nafTraub(x) =   0.45
                gbar_kdrTraub(x) =   0.45
            }
        }
        insert pasChand
    }
    tstop = 20
}

proc reset_modTraub(){local IS,gna localobj cell
    // call after insert_modTraub to adjust g_na in axons
    gna = $2
    forall{
        gbar_nafTraub = gna
        gbar_kdrTraub = gna
    }
    cell = $o1
    IS = cell.IS
    cell.axon[IS]{
        for(x,0){
            if(x*L<40){
                gbar_nafTraub(x) = 0.45
                gbar_kdrTraub(x) = 0.45
            }
        }
    }
}

proc insert_Jonas(){
  forall {
    insert pas
    g_pas =   1/36000
    e_pas = -85
    Ra =   163
    cm = 1
    insert nafJonas
    gbar_nafJonas =   0.096
    ena = 60
    insert kdrJonas
    gbar_kdrJonas =  0.096 //0.036
    ek = -85
  }
  tstop = 70
}

proc uninsert_Jonas(){
  forall {
    uninsert pas
    uninsert nafJonas
    uninsert kdrJonas
  }
}

proc insert_Yu(){
  forall {
    insert pas
    g_pas = 0.333*1e-4
    e_pas = -70
    Ra =   150
    cm = 0.75
    insert nafYu
    gbar_nafYu =   0.8
    ena = 60
    insert kdrYu
    gbar_kdrYu =   0.08
    ek = -90
  }
  tstop = 50
}

proc uninsert_Yu(){
  forall {
    uninsert pas
    uninsert nafYu
    uninsert kdrYu
  }
}

proc insert_conglomerate(){
  forall {
    insert pas
    g_pas = 0.001 // Traub //0.333*1e-4
    e_pas = -85 // Jonas
    Ra =   100 // Traub //150 // Yu
    cm = 0.75 // Yu
    insert nafJonas
    gbar_nafJonas =   0.8 // Yu
    ena = 60 
    insert kdrJonas
    gbar_kdrJonas =   0.08 // Yu
    ek = -85 
  }
  tstop = 30
}

proc uninsert_conglomerate(){
  forall {
    uninsert pas
    uninsert nafJonas
    uninsert kdrJonas
  }
}

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