Excitability of PFC Basal Dendrites (Acker and Antic 2009)

 Download zip file   Auto-launch 
Help downloading and running models
Accession:117207
".. We carried out multi-site voltage-sensitive dye imaging of membrane potential transients from thin basal branches of prefrontal cortical pyramidal neurons before and after application of channel blockers. We found that backpropagating action potentials (bAPs) are predominantly controlled by voltage-gated sodium and A-type potassium channels. In contrast, pharmacologically blocking the delayed rectifier potassium, voltage-gated calcium or Ih, conductance had little effect on dendritic action potential propagation. Optically recorded bAP waveforms were quantified and multicompartmental modeling (NEURON) was used to link the observed behavior with the underlying biophysical properties. The best-fit model included a non-uniform sodium channel distribution with decreasing conductance with distance from the soma, together with a non-uniform (increasing) A-type potassium conductance. AP amplitudes decline with distance in this model, but to a lesser extent than previously thought. We used this model to explore the mechanisms underlying two sets of published data involving high frequency trains of action potentials, and the local generation of sodium spikelets. ..."
Reference:
1 . Acker CD, Antic SD (2009) Quantitative assessment of the distributions of membrane conductances involved in action potential backpropagation along basal dendrites. J Neurophysiol 101:1524-41 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex V1 L6 pyramidal corticothalamic GLU cell;
Channel(s): I Na,t; I L high threshold; I T low threshold; I A; I K; I h; I Potassium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Dendritic Action Potentials; Parameter Fitting; Active Dendrites; Detailed Neuronal Models; Calcium dynamics;
Implementer(s): Acker, Corey [acker at uchc.edu];
Search NeuronDB for information about:  Neocortex V1 L6 pyramidal corticothalamic GLU cell; I Na,t; I L high threshold; I T low threshold; I A; I K; I h; I Potassium;
/
acker_antic
Model
ca.mod *
Cad.mod
CaT.mod
IL.mod
kadist.mod
kaprox.mod *
kv.mod
na.mod
PlateauConductance.mod
vmax.mod
CA 229.hoc
PFC_L5Pyramid_AckerAntic06.hoc
                            
/* Channel distributions and all other biophysical properties of model basal 
   dendrites of prefrontal layer V pyramidal cell from Acker, Antic (2008) 
   Membrane Exitability and Action Potential Backpropagation in Basal Dendrites 
   of Prefrontal Cortical Pyramidal Neurons.

   Corey Acker
   Neuroscience
   UConn Health Center

   June 2006 */

load_file("CA 229.hoc") // cell morphology

// Cell passive properties
global_Ra=90
spineFACTOR = 1.5
somaRm = 1000/0.04
dendRm = somaRm/spineFACTOR
somaCm = 1
dendCm = somaCm*spineFACTOR
spinedist = 50 // distance at which spines start
Vk=-80
VNa=60
pasVm = -65

// Specify cell biophysics
somaNa = 900  // [pS/um2]
axonNa = 5000
basalNa = 150
mNa = 0.5  // decrease in sodium channel conductance in basal dendrites [pS/um2/um]
apicalNa = 375
gNamax = 2000  // maximum basal sodium conductance
vshiftna = -10

somaKv = 40 // somatic, apical, and initial basal Kv conductance
mKV = 0  // increase in KV conductance in basal dendrites
gKVmax = 500  // maximum basal KV conductance
axonKv = 100

somaKA = 150  // initial basal total GKA conductance [pS/um2] equals somatic
mgka = 0.7  // linear rise in IA channel density
mgkaratio = 1/300  // linear drop in KAP portion, 1 at soma
apicalKA = 300 // apical total GKA conductance
gkamax = 2000  // pS/um2

somaCa=10 // total calcium channel conductance density of soma [pS/um^2]
dendCa=2 // dendritic total calcium conductance density
cadist=30  // dendritic calcium channel conductance equals that of soma up until this distance
gcaratio=0.2 // portion of gHVA to gHVA+gIT total, 1 is all HVA, 0 is all IT

gkl=0.005
ILdist=15

proc biophys() {local x, dist

  forall {
    Ra = global_Ra
    insert vmax
  }

  forsec "soma" {
     cm = somaCm
     insert pas g_pas = 1/somaRm e_pas = pasVm
     insert na ena = VNa vshift_na=vshiftna
     insert kv ek=Vk
     insert kap
     insert ca
     insert it eca = 140 ion_style("ca_ion",0,1,0,0,0) vshift_ca = 10 boostca()
     insert cad
  }

  forsec basals {
     insert pas e_pas = pasVm
     insert na ena = VNa vshift_na=vshiftna
     insert kv ek=Vk
     insert kap
     insert kad
     insert ca
     insert it eca = 140 ion_style("ca_ion",0,1,0,0,0) vshift_ca = 10 boostca()
     insert cad
  }

  forsec axon {
    cm = somaCm
    insert pas g_pas = 1/somaRm e_pas = pasVm
    insert na ena = VNa vshift_na=vshiftna thi1_na = -58 thi2_na = -58
    insert kv ek=Vk
    insert kl
    for (x,0) {
       dist=distance(x)
       if (dist>=ILdist) {
          gbar_kl(x) = gkl
       } else gbar_kl(x) = 0
    }
  }

  forsec "apical" {
     insert pas e_pas = pasVm
     insert na ena = VNa vshift_na=vshiftna
     insert kv ek=Vk
     insert kap
     insert kad
     insert ca
     insert it eca = 140 ion_style("ca_ion",0,1,0,0,0) vshift_ca = 10 boostca()
     insert cad
  }
  
  gna_control()
  distCa()
  distKV()
  distKA()
  distspines()
}

proc gna_control() {local x,dist,gNalin
  forsec "soma" gbar_na = somaNa 

  forsec basals for (x,0) {
     dist=distance(x)
     gNalin=basalNa-mNa*dist
     if (gNalin>gNamax) {
         gNalin=gNamax
         print "Setting basal Na to maximum ",gNamax," at distance ",dist," in basal dendrite ",secname()
     } else {
         if (gNalin<0) {
            gNalin=0
            print "Setting basal Na to zero at distance ",dist," in basal dendrite ",secname()
         }
     }
     gbar_na(x)=gNalin
  }

  forsec axon gbar_na = axonNa
  forsec "apical" gbar_na = apicalNa
}

proc distKV() {local x,dist,gKVlin // distribute KV channels
  forsec "soma" gbar_kv = somaKv 

  forsec basals for (x,0) {
     dist=distance(x)
     gKVlin=somaKv+mKV*dist
     if (gKVlin>gKVmax) {
         gKVlin=gKVmax
         print "Setting basal GKV to maximum ",gKVmax," at distance ",dist," in basal dendrite",secname()
     } else {
         if (gKVlin<0) {
            gKVlin=0
            print "Setting basal GKV to zero at distance ",dist," in basal dendrite ",secname()
         }
     }
     gbar_kv(x)=gKVlin
  }

  forsec axon gbar_kv = axonKv 
  forsec "apical" gbar_kv = somaKv 
}

proc distKA() {local x, dist, gkalin, ratiolin, ratio  // distribute IA channels
   forsec "soma" gkabar_kap = somaKA/1e4

   forsec basals for (x,0) {
      dist=distance(x)
      gkalin=somaKA+mgka*dist // continuous with soma
      ratiolin=1-mgkaratio*dist
      if (ratiolin<0) {
         ratio=0
      } else ratio=ratiolin
      if (gkalin>gkamax) {
         gkalin=gkamax
         print "Setting GKA to maximum ",gkamax," in basal dendrite",secname()
      } else {
         if (gkalin<0) {
             gkalin=0
             print "Setting GKA to 0 in basal dendrite",secname()
         }
      gkabar_kap(x)=gkalin*ratio/10000
      gkabar_kad(x)=gkalin*(1-ratio)/1e4
      }
   }

   forsec "apical" for (x,0) {
      dist=distance(x)
      ratiolin=1-mgkaratio*dist
      if (ratiolin<0) {
         ratio=0
      } else ratio=ratiolin
      gkabar_kap(x)=apicalKA*ratio/1e4
      gkabar_kad(x)=apicalKA*(1-ratio)/1e4
   }
}

proc distCa() {local x, dist // distribute Ca channels
   forsec "soma" {
      gbar_ca = somaCa*gcaratio
      gbar_it = somaCa*(1-gcaratio)/1e4
   }

   forsec basals for (x,0) {
      dist=distance(x)
      if (dist>cadist) {
         gbar_ca(x) = dendCa*gcaratio
         gbar_it(x) = dendCa*(1-gcaratio)/1e4
      } else {
         gbar_ca(x) = somaCa*gcaratio
         gbar_it(x) = somaCa*(1-gcaratio)/1e4
      }
   }

   forsec "apical" for (x,0) {
      dist=distance(x)
      if (dist>cadist) {
         gbar_ca(x) = dendCa*gcaratio
         gbar_it(x) = dendCa*(1-gcaratio)/1e4
      } else {
         gbar_ca(x) = somaCa*gcaratio
         gbar_it(x) = somaCa*(1-gcaratio)/1e4
      }
   }
}

proc distspines() {local x, dist  // distribute spines on dendrites
   forsec basals for (x,0) {
      dist=distance(x)
      if (dist>=spinedist) {
         cm(x) = dendCm
         g_pas(x) = 1/dendRm 
      } else {
         cm(x) = somaCm
         g_pas(x) = 1/somaRm 
      }
   }

   forsec "apical" for (x,0) {
      dist=distance(x)
      if (dist>=spinedist) {
         cm(x) = dendCm
         g_pas(x) = 1/dendRm 
      } else {
         cm(x) = somaCm
         g_pas(x) = 1/somaRm 
      }
   }
}

proc boostca() {
   vh1_it = 56
   vh2_it = 415
   ah_it = 30				
   v12m_it = 45
   v12h_it = 65  
   am_it = 3
   vshift_it = 10
   vm1_it = 50
   vm2_it = 125
}

biophys()

/* Define which tips I'm interested in */
Nbasaldends=13
objref record_dend[Nbasaldends]
for i=0,Nbasaldends-1 record_dend[i] = new SectionList()
basal[4] record_dend[0].append() // tip of dendrite of interest
basal[7] record_dend[1].append() // tip of dendrite of interest
basal[8] record_dend[2].append() // tip of dendrite of interest
basal[14] record_dend[3].append() // tip of dendrite of interest
basal[15] record_dend[4].append() // tip of dendrite of interest
basal[25] record_dend[5].append() // tip of dendrite of interest
basal[10] record_dend[6].append() // tip of dendrite of interest
basal[13] record_dend[7].append() // tip of dendrite of interest
basal[24] record_dend[8].append() // tip of dendrite of interest
basal[34] record_dend[9].append() // tip of dendrite of interest
basal[22] record_dend[10].append() // tip of dendrite of interest
basal[20] record_dend[11].append() // tip of dendrite of interest
basal[31] record_dend[12].append() // tip of dendrite of interest



Loading data, please wait...