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;
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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 *
                            
// For each band of AMPA and NMDA synapses, this function makes a file with
// the stimulation train and shifts the activation time (by temporal_offset) 
// written by Yiota Poirazi, July 2001, poirazi@LNC.usc.edu

double iaryE[1000]
objref varyE[1000], s_file, stimtmp, rpid, shiftsynf
stimtmp=new Vector()
strdef shiftsyn_filename, syscmd, estr, shiftsyns

proc shiftsyn_init () { local synapses, temporal_offset, hertz, gmax_default, PID, lo, hi
    total_synapses = $1        // number of synapses in the band
    tstop = $2		       // stimulation end time
    dt = $3
    hertz = $4                 // stimulation train frequency 
    synch = $5                 // synchronous or a synchronous stimulation of synapses
    perio = $6		       // periodic or not periodic stimulation
    PID = $7
    PID = abs(PID)             // only positive random seeds used for spike train generation 
    temporal_offset = $8       // shift stimulation time by temporal_offset
    skip = $9		       // time points to skip before starting the spike train
    items = int(tstop/dt)      // number of stimuli (firing patterns) for each synapse

// Make the desired activation pattern file and
// Set AMPA and NMDA pointers to activation pattern

   if (hertz > 3) {           // in most cases 
        sprint(shiftsyn_filename,"shiftsyn-%d-%.2f-%.2f-%.2f-%.2f-%.2f-%d-%.2f",\
            total_synapses,tstop,dt,hertz,synch,perio,PID,temporal_offset)   // filename
              
        sprint(syscmd,"newshiftsyn shiftsyn %d %g %g %g %g %g %d %g",\
         total_synapses,tstop,dt,hertz,synch,perio,PID,temporal_offset)  // use newshiftsyn to make
								         // stimulation train

        system(syscmd)       // Same as typing syscmd in DOS, execute above command
        print  syscmd
        s_file = new File()
        s_file.ropen(shiftsyn_filename) // open the stimulation train file
        stimtmp.scanf(s_file) //read temporal stimulation pattern in a 1-d vector
        s_file.close()
  
  } else {
  
// for single shock experiments, set the single spike at t = 0+offset (synchronous stimulation for all synapses)
     
       stimtmp = new Vector(items*total_synapses,0) 
       offset = temporal_offset/dt
       for i = 0, total_synapses-1 {
          stimtmp.x[total_synapses*offset + i] = 1
       } 
 }
 
 for i=0,total_synapses-1 {
//    printf(" -- synapse %d\n", i)

    varyE[i] = new Vector(items)  // for each synapse, save firing pattern in this vector

  // Put the firing patterns from stimtmp (1-d vector) for each syanpse i
 
    for j=0,items-1 {   
            varyE[i].x[j]=stimtmp.x[i + j*total_synapses] 

    }
 }

//  print "setpointer to each synapse"

    for s=0, total_synapses-1 {
        sprint(estr,"varyE[%d].play(&iaryE[%d])", s,s)
        execute1(estr)
//        print estr

        sprint(estr,"setpointer ampa[%d].pre, iaryE[%d]", s+skip,s)
        execute1(estr)
//        print estr

        sprint(estr,"setpointer nmda[%d].pre, iaryE[%d]", s+skip,s)
        execute1(estr)
//        print estr
         
      
       }
    
sprint(econ.syscmd,  "rm %s", shiftsyn_filename) // remove firing pattern file
print  econ.syscmd
system(econ.syscmd) 

}


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