CA1 pyramidal neuron: as a 2-layer NN and subthreshold synaptic summation (Poirazi et al 2003)

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Accession:20212
We developed a CA1 pyramidal cell model calibrated with a broad spectrum of in vitro data. Using simultaneous dendritic and somatic recordings, and combining results for two different response measures (peak vs. mean EPSP), two different stimulus formats (single shock vs. 50 Hz trains), and two different spatial integration conditions (within vs. between-branch summation), we found the cell's subthreshold responses to paired inputs are best described as a sum of nonlinear subunit responses, where the subunits correspond to different dendritic branches. In addition to suggesting a new type of experiment and providing testable predictions, our model shows how conclusions regarding synaptic arithmetic can be influenced by an array of seemingly innocuous experimental design choices.
References:
1 . Poirazi P, Brannon T, Mel BW (2003) Arithmetic of subthreshold synaptic summation in a model CA1 pyramidal cell. Neuron 37:977-87 [PubMed]
2 . Poirazi P, Brannon T, Mel BW (2003) Pyramidal neuron as two-layer neural network. Neuron 37:989-99 [PubMed]
3 . Poirazi P, Brannon T, Mel BW (2003ab-sup) Online Supplement: About the Model Neuron 37 Online:1-20
4 . Polsky A, Mel BW, Schiller J (2004) Computational subunits in thin dendrites of pyramidal cells. Nat Neurosci 7:621-7 [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:
Cell Type(s): Hippocampus CA1 pyramidal cell;
Channel(s): I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I Calcium;
Gap Junctions:
Receptor(s): GabaA; GabaB; NMDA; Glutamate;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Action Potential Initiation; Activity Patterns; Dendritic Action Potentials; Active Dendrites; Influence of Dendritic Geometry; Detailed Neuronal Models; Action Potentials; Depression; Delay;
Implementer(s): Poirazi, Panayiota [poirazi at imbb.forth.gr];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal cell; GabaA; GabaB; NMDA; Glutamate; I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I Calcium;
/
CA1_multi
lib
basic_graphics.hoc *
basic-graphics.hoc *
choose-secs.hoc *
current-balance.hoc *
cut-sections.hoc *
deduce-ratio.hoc *
find-gmax.hoc *
GABA_shiftsyn.hoc *
GABA_shiftsyn_bg.hoc *
ken.h *
map-segments-to-3d.hoc *
maxmin.hoc *
mod_func.c *
newshiftsyn.c *
newshiftsyn.exe *
num-rec.h *
salloc.hoc *
shiftsyn-init_bg.hoc *
shiftsyn-initA.hoc *
shiftsyn-initA.hoc~ *
spikecount.hoc *
tune-epsps.hoc *
vector-distance.hoc *
verbose-system.hoc *
                            
/*

This file contains all Numerical Recipes that I use.

*/


/********* Begin of Numerical Recipes routines **********/


#define M1 259200
#define IA1 7141
#define IC1 54773
#define RM1 (1.0/M1)
#define M2 134456
#define IA2 8121
#define IC2 28411
#define RM2 (1.0/M2)
#define M3 243000
#define IA3 4561
#define IC3 51349


/*
 *  numerical recipes random gaussian number generator
 */

float gasdev(idum)
     int *idum;
{
  static int iset=0;
  static float gset;
  float fac,r,v1,v2;
  float ran1();
  
  if  (iset == 0) {
    do {
      v1=2.0*ran1(idum)-1.0;
      v2=2.0*ran1(idum)-1.0;
      r=v1*v1+v2*v2;
    } while (r >= 1.0);
    fac=sqrt(-2.0*log(r)/r);
    gset=v1*fac;
    iset=1;
    return v2*fac;
  } else {
    iset=0;
    return gset;
  }
}

/*
 *	gaussian - return a gaussian random number of
 *		   variance 1 and mean 0
 */

float gaussian ()
{
	int seed = 0;

	return ( gasdev(&seed) );
}


/*
 *  numerical recipes random number generator
 */

float ran1(idum)
     int *idum;
{
  static long ix1,ix2,ix3;
  static float r[98];
  float temp;
  static int iff=0;
  int j;
  void nrerror();
  
  if (*idum < 0 || iff == 0) {
    iff=1;
    ix1=(IC1-(*idum)) % M1;
    ix1=(IA1*ix1+IC1) % M1;
    ix2=ix1 % M2;
    ix1=(IA1*ix1+IC1) % M1;
    ix3=ix1 % M3;
    for (j=1;j<=97;j++) {
      ix1=(IA1*ix1+IC1) % M1;
      ix2=(IA2*ix2+IC2) % M2;
      r[j]=(ix1+ix2*RM2)*RM1;
    }
    *idum=1;
  }
  ix1=(IA1*ix1+IC1) % M1;
  ix2=(IA2*ix2+IC2) % M2;
  ix3=(IA3*ix3+IC3) % M3;
  j=1 + ((97*ix3)/M3);
  if (j > 97 || j < 1) nrerror("RAN1: This cannot happen.");
  temp=r[j];
  r[j]=(ix1+ix2*RM2)*RM1;
  return temp;
}


/*
 *  numerical recipes error routine
 */

void nrerror(error_text)
     char error_text[];
{
  /*	void exit();
   */
  fprintf(stderr,"Numerical Recipes run-time error...\n");
  fprintf(stderr,"%s\n",error_text);
  fprintf(stderr,"...now exiting to system...\n");
  exit(1);
}

#undef M1
#undef IA1
#undef IC1
#undef RM1
#undef M2
#undef IA2
#undef IC2
#undef RM2
#undef M3
#undef IA3
#undef IC3

/********* End of Numerical Recipes routines **********/





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