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]
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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
                            
load_file("nrngui.hoc")
load_file("define_PFC.hoc") // or a hoc file that specifies the model cell's
  // anatomical and biophysical properties
load_file("rigPFCmod.ses") // brings up the following:
  // RunControl panel
  // PointProcessManager configured as an IClamp at soma(0.5)
  // Voltage axis plot of v at the current injection site
  // space plot of v along at least one path that passes through the current injection site
  // a Movie Run tool to generate smooth evolution of space plot over time

/*
1.  First, make sure that the load_file("custominit.hoc") statement below 
has been commented out.  Then double click on init.hoc or type
nrngui init.hoc

2.  Determine the "initialization run time" INITDUR.
Use the GUI to set the IClamp's amp parameter to a value that drives
v at the current injection site to a level close to what you want.
Note how long it takes for v throughout the cell to reach steady state.
This is the value you should use for INITDUR (actually you could use 
a slightly shorter time, because in the end the cell will be driven 
to steady state by a voltage clamp, so it will settle a bit faster than 
the simulation that uses an IClamp does).
Adjust Tstop in the RunControl panel and run another simulation
if necessary to make sure that the model is reaching steady state.

3.  Exit NEURON and edit this file to make the following changes in the 
assignment statements that follow these comments.
(1)  Change the value assigned to INITDUR to what you determined in step 2.
(2)  Change the value assigned to V0 so that it is whatever you want the 
     initial membrane potential at the current injection site to be.
(3)  Uncomment the load_file("custominit.hoc") statement, 
     i.e. remove the double slashes // that precede it.

4.  Restart NEURON by double clicking on init.hoc or typing
nrngui init.hoc
and you will see a run executed after a custom initialization.
Verify that membrane potential at the injection site is what 
you want.

5.  Exit NEURON and make the following additional change:
Uncomment the load_file("batchrun.hoc") command.

You will now be able to execute a family of runs by entering commands 
like this at the oc> prompt:
batchrun(10, 100, -0.1, 0.02, 10)
will run 10 simulations in which the current pulse 
begins at 10 ms and lasts 100 ms.
The pulse amplitudes, starting with the first run, 
will be -0.1, -0.08, -0.06 . . . 0.08 nA.

Left to right, the parameters specify:
t at which each pulse starts
pulse duration
amplitude of the first run's current pulse
increment of pulse amplitude between runs
number of runs
*/

INITDUR = 50 // change this according to what you discover in step 2 above
V0 = -62 // the initial v you want at the current injection site

scale_gpas(1.79e-4)
set_epasNG(60)

load_file("custominit.hoc")

// Uncomment the next line only after load_file("custominit.hoc") has been executed.
load_file("batchrun.hoc") // executes a family of simulations
  // that step through a range of current pulses
  // and shows the time course of membrane potential.