Input Fluctuations effects on f-I curves (Arsiero et al. 2007)

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Accession:83590
"... We examined in vitro frequency versus current (f-I) relationships of layer 5 (L5) pyramidal cells of the rat medial prefrontal cortex (mPFC) using fluctuating stimuli. ...our results show that mPFC L5 pyramidal neurons retain an increased sensitivity to input fluctuations, whereas their sensitivity to the input mean diminishes to near zero. This implies that the discharge properties of L5 mPFC neurons are well suited to encode input fluctuations rather than input mean in their firing rates, with important consequences for information processing and stability of persistent activity at the network level."
Reference:
1 . Arsiero M, L├╝scher HR, Lundstrom BN, Giugliano M (2007) The impact of input fluctuations on the frequency-current relationships of layer 5 pyramidal neurons in the rat medial prefrontal cortex. J Neurosci 27:3274-84 [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: Prefrontal cortex (PFC);
Cell Type(s): Neocortex L5/6 pyramidal GLU cell;
Channel(s): I Sodium; I Potassium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Simplified Models; Action Potentials; Spike Frequency Adaptation;
Implementer(s):
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; I Sodium; I Potassium;
/
Arsiero_et_al2007
mechanisms
mylibs
readme.txt
mosinit.hoc
plotme.m
runme.hoc
                            
//
// This NEURON simulation aims at replicating Figure 4A of the Arsiero et al., 2007 - submitted.
// Refer to: Arsiero, M., Luescher, H.-R., Lundstrom, B.N., and Giugliano, M. (2007). The Impact of Input Fluctuations on the Frequency-Current Relationships of Layer 5 Pyramidal Neurons in the Rat Medial Prefrontal Cortex. sumbitted.
//

//-------------------------------------------------------------------------------------------------------//
load_file("nrngui.hoc")                     // Loading of the standard GUI controls...
load_file("mylibs/graphs.hoc")              // Loading some ad-hoc proc for displaying live traces...
load_file("mylibs/singlecompneuron_1.hoc")  // Loading model neuron (morphology, biophysics, etc)...
load_file("mylibs/myinit.hoc")              // Loading some ad-hoc proc for file creation and initialization...
load_file("mylibs/TFparams.hoc")            // Settings for the TF...
//-------------------------------------------------------------------------------------------------------//

a_hhin    = 1.                 // a == 1, slow inactivation included, a == 0 excluded


tstart = 0.                   // ms - just for the purpouse of 'addgraph'
tstop  = Tdelay + T1 + T      // ms - just for the purpouse of 'addgraph' 
  
access soma

//
// Displaying live trace is of course slowing down the simulation, so commenting the following
// line could be useful..
//

addgraph("soma.v(0.5)",-80,40)

ccc = 1
for (mu = mustart; mu <= mustop; mu = mu + mustep) {
 TF_file.printf("%f\t ", mu)
 N     = 0

 for (sigma = sigmastart; sigma <= sigmastop; sigma = sigma + sigmastep){
  fl.m   = 0.           // During the first Tdelay [ms] - no stimulation takes place.
  fl.s   = 0.           // During the first Tdelay [ms] - no stimulation takes place.
  apc.n  = 0            // The spike counter is reset to 0.
  t      = 0.           // ms - The current simulation time is set to 0.
  tstart = 0.           // ms
  tstop  = Tdelay       // ms
  finitialize(-65)
  run()

  fl.m   = mu           //
  fl.s   = sigma        //
  tstop  = t + T1       // ms - We advance the simulation of T1, while stimulating..
  continuerun(tstop)
  
  apc.n  = 0            // We discard the count of the spikes emitted during the previous interval..
  tstop  = t + T        // ms - We advance the simulation of T, during which we count the spikes..
  continuerun(tstop)
  N      = apc.n        // N spikes have been counted.

  TF_file.printf( "%f\t ", 1000. * N / T )      // The firing rate is computed and written on disk - measured in Hz

  printf("%d/%d points  done!\n", ccc, numpoints  )
 
  ccc = ccc +1
 }//end for sigma
 
 TF_file.printf("\n")
 TF_file.flush()

} //end for mu

TF_file.close()

printf("The data points of the f-I response function are now available for further analysis and plot!\n")
printf("The data points of the f-I response function are now available for further analysis and plot!\n")


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