Parametric computation and persistent gamma in a cortical model (Chambers et al. 2012)

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Accession:144579
Using the Traub et al (2005) model of the cortex we determined how 33 synaptic strength parameters control gamma oscillations. We used fractional factorial design to reduce the number of runs required to 4096. We found an expected multiplicative interaction between parameters.
Reference:
1 . Chambers JD, Bethwaite B, Diamond NT, Peachey T, Abramson D, Petrou S, Thomas EA (2012) Parametric computation predicts a multiplicative interaction between synaptic strength parameters that control gamma oscillations. Front Comput Neurosci 6:53 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Axon; Synapse; Channel/Receptor; Dendrite;
Brain Region(s)/Organism:
Cell Type(s): Neocortex L5/6 pyramidal GLU cell; Neocortex L2/3 pyramidal GLU cell; Neocortex V1 interneuron basket PV GABA cell; Neocortex fast spiking (FS) interneuron; Neocortex spiny stellate cell; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron;
Channel(s): I A; I K; I K,leak; I K,Ca; I Calcium; I_K,Na;
Gap Junctions: Gap junctions;
Receptor(s): GabaA; AMPA; NMDA;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Oscillations; Parameter sensitivity;
Implementer(s): Thomas, Evan [evan at evan-thomas.net]; Chambers, Jordan [jordandchambers at gmail.com];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; Neocortex L2/3 pyramidal GLU cell; Neocortex V1 interneuron basket PV GABA cell; GabaA; AMPA; NMDA; I A; I K; I K,leak; I K,Ca; I Calcium; I_K,Na; Gaba; Glutamate;
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FRBGamma
net
durand.hoc *
groucho.hoc
groucho_gapbld.hoc *
groucho_gapbld_mix.hoc *
groucho_traub.hoc
network_specification_interface.hoc *
serial_or_par_wrapper.hoc *
synaptic_compmap_construct.hoc *
synaptic_map_construct.hoc *
                            
// groucho_gapbld.hoc
/*
*****************************this is one big comment ***************************
from            SUBROUTINE GROUCHO_gapbld (thisno, numcells, numgj,
     &       gjtable, allowedcomps, num_allowedcomps, display)
c       Construct a gap-junction network for groucho.f
$1 thisno double
$2 numcells = number of cells in population, e.g. number of tufted IB cells
$3 numgj = total number of gj to be formed in this population
// this matrix is returned: gjtable = table of gj's: each row is a gj.  
     Entries are: cell A,
c    compartment on cell A; cell B, compartment on cell B
$o4 c allowedcomps = a list of compartments where gj allowed to form
$5 num_allowedcomps = number of compartments in a cell on which a gj 
c    might form.
$6 display is an integer flag.  If display = 1, print gjtable

        INTEGER thisno, numcells, numgj, gjtable(numgj,4),
     &    num_allowedcomps, allowedcomps(num_allowedcomps)
        INTEGER i,j,k,l,m,n,o,p, ictr /0/
c ictr keeps track of how many gj have been "built"
        INTEGER display

        double precision seed, x(2), y(2)

Note: this function is for gap junctions that form between a cells that are
members of a population of a single cell type
*****************************this is one big comment ***************************
*/
objref gjtable, x, y, allowedcomps
obfunc groucho_gapbld() {localobj used
// see above note for arguments $1,$2,$3,$o4,$5
// print "arrived"
	thisno = $1
	numcells = $2
	numgj = $3
	allowedcomps = $o4
	num_allowedcomps = $5
	display = $6

	seed = new Vector()
	seed.append(137.e0)

	objref gjtable
	gjtable = new Matrix(numgj+1, 4+1) // fortran notation indicies start at 1

	ictr = 0
	k = 2
	not_unique = 0 // make global so not local in loops
        used = new Matrix(numcells+1, numcells+1, 2) // sparse

// 2
// print "starting loop"
	while (ictr < numgj) {
 //         print "ictr = ",ictr
	  not_unique = 1 // 1 is true, 0 is false
	    while (not_unique) {
		x = durand (seed, k, x)
// This defines a candidate cell pair
		y = durand (seed, k, y)
// This defines a candidate pair of compartments

		i = int ( x.x[0] * numcells ) + 1
		j = int ( x.x[1] * numcells ) + 1
//		print "i,j: ",i,", ",j
// no longer required		if (i.eq.0) i = 1
// no longer required		if (i.gt.numcells) i = numcells
// no longer required		if (j.eq.0) j = 1
// no longer required		if (j.gt.numcells) j = numcells

// Is the unordered cell pair (i,j) in the list so far?
// not necessary to be this efficient  if (ictr.eq.0) goto 1

 		not_unique = 0
 if (0) {
		for eL = 1, ictr {
//		  print "compare i,j with eL = ",eL, " : ",gjtable.x(eL,1),", ",gjtable.x(eL,3)
		  if ((gjtable.x(eL,1) == i) && (gjtable.x(eL,3) == j)) { not_unique = 1 }
 		  if ((gjtable.x(eL,1) == j) && (gjtable.x(eL,3) == i)) { not_unique = 1 }
		}
//		print " at end of loop not_unique = ",not_unique
  }else{
                if (used.getval(i, j) || used.getval(j, i)){
                        not_unique = 1
                }else{
                        used.x[i][j] = 1
                }
		if (one_tenth_ncell) {
			not_unique = 0
		}
  }
	    } // while replaces if (not_unique.eq.1) goto 2

// Proceed with construction
// 1
	  ictr = ictr + 1
          m = int ( y.x[0] * num_allowedcomps ) + 1
          n = int ( y.x[1] * num_allowedcomps ) + 1
//	print "assigning quantities: ", i, ", ", j, ", ", allowedcomps.x[m], ", ",allowedcomps.x[n]

         gjtable.x(ictr,1) = i
         gjtable.x(ictr,3) = j
         gjtable.x(ictr,2) = allowedcomps.x (m)
         gjtable.x(ictr,4) = allowedcomps.x (n)
	}
//            if (ictr.lt.numgj) goto 2

// Possibly print out gjtable when done.
       if ((display == 1) && (thisno == 0)) {
        print " GJTABLE "
        for i = 1, numgj {
        printf("%6d %6d %6d %6d",gjtable.x(i,1), gjtable.x(i,2), \
                gjtable.x(i,3), gjtable.x(i,4))
        }
       }
	return gjtable
}