Rhesus Monkey Layer 3 Pyramidal Neurons: V1 vs PFC (Amatrudo, Weaver et al. 2012)

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Accession:144553
Whole-cell patch-clamp recordings and high-resolution 3D morphometric analyses of layer 3 pyramidal neurons in in vitro slices of monkey primary visual cortex (V1) and dorsolateral granular prefrontal cortex (dlPFC) revealed that neurons in these two brain areas possess highly distinctive structural and functional properties. ... Three-dimensional reconstructions of V1 and dlPFC neurons were incorporated into computational models containing Hodgkin-Huxley and AMPA- and GABAA-receptor gated channels. Morphology alone largely accounted for observed passive physiological properties, but led to AP firing rates that differed more than observed empirically, and to synaptic responses that opposed empirical results. Accordingly, modeling predicts that active channel conductances differ between V1 and dlPFC neurons. The unique features of V1 and dlPFC neurons are likely fundamental determinants of area-specific network behavior. The compact electrotonic arbor and increased excitability of V1 neurons support the rapid signal integration required for early processing of visual information. The greater connectivity and dendritic complexity of dlPFC neurons likely support higher level cognitive functions including working memory and planning.
Reference:
1 . Amatrudo JM, Weaver CM, Crimins JL, Hof PR, Rosene DL, Luebke JI (2012) Influence of highly distinctive structural properties on the excitability of pyramidal neurons in monkey visual and prefrontal cortices. J Neurosci 32:13644-60 [PubMed]
Citations  Citation Browser
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; Prefrontal cortex (PFC);
Cell Type(s): Neocortex L2/3 pyramidal GLU cell;
Channel(s): I N; I K;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Influence of Dendritic Geometry; Detailed Neuronal Models; Electrotonus; Conductance distributions; Vision;
Implementer(s): Weaver, Christina [christina.weaver at fandm.edu];
Search NeuronDB for information about:  Neocortex L2/3 pyramidal GLU cell; I N; I K;
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V1_PFC_ModelDB
README
kvz_nature.mod *
naz_nature.mod *
vsource.mod *
actionPotentialPlayer.hoc *
add_axon.hoc
analyticFunctions.hoc *
analyze_EPSC.m
aux_procs.hoc
batchrun.hoc
custominit.hoc
define_PFC.hoc
electro_procs.hoc *
figOptions.hoc
fixnseg.hoc *
init_model.hoc
init_PFC.hoc
Jul16IR3f_fromSWCthenManual_Nov22-11.hoc
load_scripts.hoc *
main_fig10_pfc.hoc
main_fig10_v1baseline.hoc
main_fig10_v1tuned.hoc
main_fig9_pfcElec.hoc
main_fig9_v1Elec.hoc
main_PFC-ApBas_fig11epsc.hoc
main_PFC-ApBas_fig12ipsc.hoc
main_V1-ApBas_fig11epsc.hoc
main_V1-ApBas_fig12ipsc.hoc
May3IR2t_ImportFromSWCthenManual_Aug19-11.hoc
measureMeanAtten.hoc
mosinit.hoc
PFC-V1_AddSynapses.hoc
plot_seClamp_i.ses
plot_seClamp_IPSC.ses
read_EPSCsims_mdb.m
read_IPSCsims_mdb.m
readcell.hoc
readNRNbin_Vclamp.m
rigPFCmod.ses
synTweak.hoc
vsrc.ses
                            
/************************************************************

	Christina Weaver
	August 2011
	
	insert channels from Vetter et al (2001) into Jennie's 
	PFC and Visual Cortex neurons.  Includes Mainen's 
	synthetic axon (from the 1995 Mainen et al. paper).

************************************************************/

load_file("nrngui.hoc")

// now load morph;  recall that 'basic_shape()' resets the morphology
load_file("May3IR2t_ImportFromSWCthenManual_Aug19-11.hoc")

load_file("aux_procs.hoc")

xopen("electro_procs.hoc")

    PFC_effective_ApicalSpineDensity = 0.83524895	//  total of 5891 spines, divided by total apical length of 7052.987 microns
    PFC_effective_BasalSpineDensity  = 1.1177593	//  total of 4014 spines, divided by total basal  length of 3591.1131 microns

    applySubtreeConstantSpineDensity(apical, SurfaceAreaOneApicalSpine, PFC_effective_ApicalSpineDensity)
    applySubtreeConstantSpineDensity(basal,  SurfaceAreaOneBasalSpine,  PFC_effective_BasalSpineDensity)
    geom_nseg(100,0.1)

// Using SEClamp, as recommended on the NEURON User Forum.  See init_PFC.hoc for details.
INITDUR = 80	

steps_per_ms = 40
dt = 0.025

xopen("PFC-V1_AddSynapses.hoc")









distance()

objref synBranches, synLoc

/*** new parameter settings as of 23 Jan 2012 ***/
VO = -70
V0 = -70	//avoid ambiguity of "Capital O" vs "zero 0"

set_epasNG(69)
scale_gpas(3.8e-5)
scaleNa(105,1e3)
scaleKV(115,16.6667)

forall { if( ismembrane("na") )   vshift_na=-10.5 }  

forall { v_init = -70 }


/**** 
    set up a Voltage Clamp
****/

objref seClamp
    soma seClamp = new SEClamp(0.5)
    seClamp.dur1 = 1e9
    seClamp.amp1 = -70
    seClamp.dur2 = 0




/***** end voltage clamp ****/






/**********************  copied from synTweak.hoc in ~/LuebkeAmatrudo_forCluster  *********/



strdef synFilename
objref synFout, tv, iv

/**********************

    Written originally in main_PFC_simEPSC_all.hoc; now copied here.

    $1  number of synapses
    $2  value of tau1
    $3  value of tau2
    $4  value of gAMPA
    $s5 file basename

**********************/
proc synTweak() { local i, vecsz, btyp

    adjust_tau1($2,$1)
    adjust_tau2($3,$1)
    adjust_gAMPA($4,$1)

    sprint(synFilename,"%s_tR%.4f_tF%.2f_gAMP%.5f.Ibin",$s5,$2,$3,$4)
    synFout = new File()
    synFout.wopen(synFilename)

    tv = new Vector()
    tv.record(&t)
    iv = new Vector()
    iv.record(&seClamp.i)

    init()
    run()

    vecsz = tv.size()
    synFout.vwrite(&vecsz)
    tv.fwrite(synFout)
    iv.fwrite(synFout)
    synFout.close()

    sprint(synFilename,"%s_tR%.4f_tF%.2f_gAMP%.5f_dist.txt",$s5,$2,$3,$4)
    synFout = new File()
    synFout.wopen(synFilename)

    i = 0
    forsec synBranches {
        btyp = 0
	ifsec apical { btyp = 1 }
	ifsec basal  { btyp = 2 }
        synFout.printf("%d\t%g\t%g\t%d\n",i,distance(synLoc.x[i]),distance(synLoc.x[i])-soma.diam,btyp)
         i+=1
    }
    synFout.close()
}



/**********************  end from synTweak.hoc in ~/LuebkeAmatrudo_forCluster  *********/





xopen("plot_seClamp_i.ses")

nBr = 0

if( doApic == 1 ) {

    // activate apical synapses
    nSynapse = AddExcSynapses_byNumber(59,0,200,200,synBranches,synLoc)

    endSyn = 200 + (nSynapse + 2)*200
    distance()
    cnt = 0

    tstop=endSyn
    synTweak(nSynapse,.15,4,.00054,"fig11_PFCapic")

} else {

    // activate basal synapses
    nSynapse = AddExcSynapses_byNumber(0,40,200,200,synBranches,synLoc)

    endSyn = 200 + (nSynapse + 2)*200
    distance()
    cnt = 0

    tstop=endSyn
    synTweak(nSynapse,.15,4,.00054,"fig11_PFCbas")
}


printf("\n\n**************************\n\n")
printf("Output has been written to a file ending in .Ibin, a customized binary file format.\n")
printf("These files can be read with MATLAB.  See the .m files contained in this directory.\n")
printf("MATLAB's Statistics Toolbox is required to analyze EPSC shapes.\n")
printf("\tSample usage:  read_EPSCsims_mdb('fig11_PFCapic',0.00054)\n")
printf("\n\n**************************\n\n")