Cell splitting in neural networks extends strong scaling (Hines et al. 2008)

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Accession:97917
Neuron tree topology equations can be split into two subtrees and solved on different processors with no change in accuracy, stability, or computational effort; communication costs involve only sending and receiving two double precision values by each subtree at each time step. Application of the cell splitting method to two published network models exhibits good runtime scaling on twice as many processors as could be effectively used with whole-cell balancing.
Reference:
1 . Hines ML, Eichner H, Schürmann F (2008) Neuron splitting in compute-bound parallel network simulations enables runtime scaling with twice as many processors. J Comput Neurosci 25:203-10 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Generic;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Methods;
Implementer(s): Hines, Michael [Michael.Hines at Yale.edu];
/
splitcell
nrntraub
cells
deepaxax_template.hoc *
deepbask_template.hoc *
deepLTS_template.hoc *
nontuftRS_template.hoc *
nRT_template.hoc *
spinstell_template.hoc *
supaxax_template.hoc *
supbask_template.hoc *
supLTS_template.hoc *
suppyrFRB_template.hoc *
suppyrRS_template.hoc *
TCR_template.hoc *
tuftIB_template.hoc *
tuftRS_template.hoc *
                            
 // Trying to open ../diagnostic/tstop.dat
 // new end time timtot =   150.
 // Trying to open ../diagnostic/dt_F.dat
 // new dt =  0.002
 // COMPART. LEVEL  RADIUS  LENGTH(MU)
 //   1      1    10.00   42.0
 //   2      2     0.73   20.0
 //   3      3     0.58   57.5
 //   4      3     0.58   57.5
 //   5      3     0.58   57.5
 //   6      4     0.44   57.5
 //   7      4     0.44   57.5
 //   8      4     0.44   57.5
 //   9      4     0.44   57.5
 //  10      4     0.44   57.5
 //  11      4     0.44   57.5
 //  12      4     0.44   57.5
 //  13      4     0.44   57.5
 //  14      4     0.44   57.5
 //  15      2     0.73   20.0
 //  16      3     0.58   57.5
 //  17      3     0.58   57.5
 //  18      3     0.58   57.5
 //  19      4     0.44   57.5
 //  20      4     0.44   57.5
 //  21      4     0.44   57.5
 //  22      4     0.44   57.5
 //  23      4     0.44   57.5
 //  24      4     0.44   57.5
 //  25      4     0.44   57.5
 //  26      4     0.44   57.5
 //  27      4     0.44   57.5
 //  28      2     0.73   20.0
 //  29      3     0.58   57.5
 //  30      3     0.58   57.5
 //  31      3     0.58   57.5
 //  32      4     0.44   57.5
 //  33      4     0.44   57.5
 //  34      4     0.44   57.5
 //  35      4     0.44   57.5
 //  36      4     0.44   57.5
 //  37      4     0.44   57.5
 //  38      4     0.44   57.5
 //  39      4     0.44   57.5
 //  40      4     0.44   57.5
 //  41      2     0.73   20.0
 //  42      3     0.58   57.5
 //  43      3     0.58   57.5
 //  44      3     0.58   57.5
 //  45      4     0.44   57.5
 //  46      4     0.44   57.5
 //  47      4     0.44   57.5
 //  48      4     0.44   57.5
 //  49      4     0.44   57.5
 //  50      4     0.44   57.5
 //  51      4     0.44   57.5
 //  52      4     0.44   57.5
 //  53      4     0.44   57.5
 //  54      2     0.73   20.0
 //  55      3     0.58   57.5
 //  56      3     0.58   57.5
 //  57      3     0.58   57.5
 //  58      4     0.44   57.5
 //  59      4     0.44   57.5
 //  60      4     0.44   57.5
 //  61      4     0.44   57.5
 //  62      4     0.44   57.5
 //  63      4     0.44   57.5
 //  64      4     0.44   57.5
 //  65      4     0.44   57.5
 //  66      4     0.44   57.5
 //  67      2     0.73   20.0
 //  68      3     0.58   57.5
 //  69      3     0.58   57.5
 //  70      3     0.58   57.5
 //  71      4     0.44   57.5
 //  72      4     0.44   57.5
 //  73      4     0.44   57.5
 //  74      4     0.44   57.5
 //  75      4     0.44   57.5
 //  76      4     0.44   57.5
 //  77      4     0.44   57.5
 //  78      4     0.44   57.5
 //  79      4     0.44   57.5
 //  80      2     0.73   20.0
 //  81      3     0.58   57.5
 //  82      3     0.58   57.5
 //  83      3     0.58   57.5
 //  84      4     0.44   57.5
 //  85      4     0.44   57.5
 //  86      4     0.44   57.5
 //  87      4     0.44   57.5
 //  88      4     0.44   57.5
 //  89      4     0.44   57.5
 //  90      4     0.44   57.5
 //  91      4     0.44   57.5
 //  92      4     0.44   57.5
 //  93      2     0.73   20.0
 //  94      3     0.58   57.5
 //  95      3     0.58   57.5
 //  96      3     0.58   57.5
 //  97      4     0.44   57.5
 //  98      4     0.44   57.5
 //  99      4     0.44   57.5
 // 100      4     0.44   57.5
 // 101      4     0.44   57.5
 // 102      4     0.44   57.5
 // 103      4     0.44   57.5
 // 104      4     0.44   57.5
 // 105      4     0.44   57.5
 // 106      2     0.73   20.0
 // 107      3     0.58   57.5
 // 108      3     0.58   57.5
 // 109      3     0.58   57.5
 // 110      4     0.44   57.5
 // 111      4     0.44   57.5
 // 112      4     0.44   57.5
 // 113      4     0.44   57.5
 // 114      4     0.44   57.5
 // 115      4     0.44   57.5
 // 116      4     0.44   57.5
 // 117      4     0.44   57.5
 // 118      4     0.44   57.5
 // 119      2     0.73   20.0
 // 120      3     0.58   57.5
 // 121      3     0.58   57.5
 // 122      3     0.58   57.5
 // 123      4     0.44   57.5
 // 124      4     0.44   57.5
 // 125      4     0.44   57.5
 // 126      4     0.44   57.5
 // 127      4     0.44   57.5
 // 128      4     0.44   57.5
 // 129      4     0.44   57.5
 // 130      4     0.44   57.5
 // 131      4     0.44   57.5
 // 132      0     0.80   50.0
 // 133      0     0.70   50.0
 // 134      0     0.50   50.0
 // 135      0     0.50   50.0
 // 136      0     0.50   50.0
 // 137      0     0.50   50.0
 // Comp1  Comp2  Conductance_between_1_2   
 //  1   132    0.0796751205
 //  1   2    0.0946071642
 //  1   15    0.0946071642
 //  1   28    0.0946071642
 //  1   41    0.0946071642
 //  1   54    0.0946071642
 //  1   67    0.0946071642
 //  1   80    0.0946071642
 //  1   93    0.0946071642
 //  1   106    0.0946071642
 //  1   119    0.0946071642
 //  2   3    0.0174185429
 //  2   4    0.0174185429
 //  2   5    0.0174185429
 //  3   6    0.00766658232
 //  3   7    0.00766658232
 //  3   8    0.00766658232
 //  4   9    0.00766658232
 //  4   10    0.00766658232
 //  4   11    0.00766658232
 //  5   12    0.00766658232
 //  5   13    0.00766658232
 //  5   14    0.00766658232
 //  6   7    0.00598951744
 //  6   8    0.00598951744
 //  7   8    0.00598951744
 //  9   10    0.00598951744
 //  9   11    0.00598951744
 //  10   11    0.00598951744
 //  12   13    0.00598951744
 //  12   14    0.00598951744
 //  13   14    0.00598951744
 //  15   16    0.0174185429
 //  15   17    0.0174185429
 //  15   18    0.0174185429
 //  16   19    0.00766658232
 //  16   20    0.00766658232
 //  16   21    0.00766658232
 //  17   22    0.00766658232
 //  17   23    0.00766658232
 //  17   24    0.00766658232
 //  18   25    0.00766658232
 //  18   26    0.00766658232
 //  18   27    0.00766658232
 //  19   20    0.00598951744
 //  19   21    0.00598951744
 //  20   21    0.00598951744
 //  22   23    0.00598951744
 //  22   24    0.00598951744
 //  23   24    0.00598951744
 //  25   26    0.00598951744
 //  25   27    0.00598951744
 //  26   27    0.00598951744
 //  28   29    0.0174185429
 //  28   30    0.0174185429
 //  28   31    0.0174185429
 //  29   32    0.00766658232
 //  29   33    0.00766658232
 //  29   34    0.00766658232
 //  30   35    0.00766658232
 //  30   36    0.00766658232
 //  30   37    0.00766658232
 //  31   38    0.00766658232
 //  31   39    0.00766658232
 //  31   40    0.00766658232
 //  32   33    0.00598951744
 //  32   34    0.00598951744
 //  33   34    0.00598951744
 //  35   36    0.00598951744
 //  35   37    0.00598951744
 //  36   37    0.00598951744
 //  38   39    0.00598951744
 //  38   40    0.00598951744
 //  39   40    0.00598951744
 //  41   42    0.0174185429
 //  41   43    0.0174185429
 //  41   44    0.0174185429
 //  42   45    0.00766658232
 //  42   46    0.00766658232
 //  42   47    0.00766658232
 //  43   48    0.00766658232
 //  43   49    0.00766658232
 //  43   50    0.00766658232
 //  44   51    0.00766658232
 //  44   52    0.00766658232
 //  44   53    0.00766658232
 //  45   46    0.00598951744
 //  45   47    0.00598951744
 //  46   47    0.00598951744
 //  48   49    0.00598951744
 //  48   50    0.00598951744
 //  49   50    0.00598951744
 //  51   52    0.00598951744
 //  51   53    0.00598951744
 //  52   53    0.00598951744
 //  54   55    0.0174185429
 //  54   56    0.0174185429
 //  54   57    0.0174185429
 //  55   58    0.00766658232
 //  55   59    0.00766658232
 //  55   60    0.00766658232
 //  56   61    0.00766658232
 //  56   62    0.00766658232
 //  56   63    0.00766658232
 //  57   64    0.00766658232
 //  57   65    0.00766658232
 //  57   66    0.00766658232
 //  58   59    0.00598951744
 //  58   60    0.00598951744
 //  59   60    0.00598951744
 //  61   62    0.00598951744
 //  61   63    0.00598951744
 //  62   63    0.00598951744
 //  64   65    0.00598951744
 //  64   66    0.00598951744
 //  65   66    0.00598951744
 //  67   68    0.0174185429
 //  67   69    0.0174185429
 //  67   70    0.0174185429
 //  68   71    0.00766658232
 //  68   72    0.00766658232
 //  68   73    0.00766658232
 //  69   74    0.00766658232
 //  69   75    0.00766658232
 //  69   76    0.00766658232
 //  70   77    0.00766658232
 //  70   78    0.00766658232
 //  70   79    0.00766658232
 //  71   72    0.00598951744
 //  71   73    0.00598951744
 //  72   73    0.00598951744
 //  74   75    0.00598951744
 //  74   76    0.00598951744
 //  75   76    0.00598951744
 //  77   78    0.00598951744
 //  77   79    0.00598951744
 //  78   79    0.00598951744
 //  80   81    0.0174185429
 //  80   82    0.0174185429
 //  80   83    0.0174185429
 //  81   84    0.00766658232
 //  81   85    0.00766658232
 //  81   86    0.00766658232
 //  82   87    0.00766658232
 //  82   88    0.00766658232
 //  82   89    0.00766658232
 //  83   90    0.00766658232
 //  83   91    0.00766658232
 //  83   92    0.00766658232
 //  84   85    0.00598951744
 //  84   86    0.00598951744
 //  85   86    0.00598951744
 //  87   88    0.00598951744
 //  87   89    0.00598951744
 //  88   89    0.00598951744
 //  90   91    0.00598951744
 //  90   92    0.00598951744
 //  91   92    0.00598951744
 //  93   94    0.0174185429
 //  93   95    0.0174185429
 //  93   96    0.0174185429
 //  94   97    0.00766658232
 //  94   98    0.00766658232
 //  94   99    0.00766658232
 //  95   100    0.00766658232
 //  95   101    0.00766658232
 //  95   102    0.00766658232
 //  96   103    0.00766658232
 //  96   104    0.00766658232
 //  96   105    0.00766658232
 //  97   98    0.00598951744
 //  97   99    0.00598951744
 //  98   99    0.00598951744
 //  100   101    0.00598951744
 //  100   102    0.00598951744
 //  101   102    0.00598951744
 //  103   104    0.00598951744
 //  103   105    0.00598951744
 //  104   105    0.00598951744
 //  106   107    0.0174185429
 //  106   108    0.0174185429
 //  106   109    0.0174185429
 //  107   110    0.00766658232
 //  107   111    0.00766658232
 //  107   112    0.00766658232
 //  108   113    0.00766658232
 //  108   114    0.00766658232
 //  108   115    0.00766658232
 //  109   116    0.00766658232
 //  109   117    0.00766658232
 //  109   118    0.00766658232
 //  110   111    0.00598951744
 //  110   112    0.00598951744
 //  111   112    0.00598951744
 //  113   114    0.00598951744
 //  113   115    0.00598951744
 //  114   115    0.00598951744
 //  116   117    0.00598951744
 //  116   118    0.00598951744
 //  117   118    0.00598951744
 //  119   120    0.0174185429
 //  119   121    0.0174185429
 //  119   122    0.0174185429
 //  120   123    0.00766658232
 //  120   124    0.00766658232
 //  120   125    0.00766658232
 //  121   126    0.00766658232
 //  121   127    0.00766658232
 //  121   128    0.00766658232
 //  122   129    0.00766658232
 //  122   130    0.00766658232
 //  122   131    0.00766658232
 //  123   124    0.00598951744
 //  123   125    0.00598951744
 //  124   125    0.00598951744
 //  126   127    0.00598951744
 //  126   128    0.00598951744
 //  127   128    0.00598951744
 //  129   130    0.00598951744
 //  129   131    0.00598951744
 //  130   131    0.00598951744
 //  132   133    0.0348744292
 //  133   134    0.0208024203
 //  133   136    0.0208024203
 //  134   135    0.01570795
 //  134   136    0.01570795
 //  136   137    0.01570795
 /* TCR/TCR_template.hoc
 automatically written from f2nrn/neuron_code_writer.f
 via subroutines that were inserted into the fortran
 code e.g., TCR/integrate_TCR.hoc
 
 The template's form was derived by
 Tom Morse and Michael Hines
 from a template, pyr3_template created
 by Roger Traub and Maciej Lazarewicz when they ported
 
         Traub RD, Buhl EH, Gloveli T, Whittington MA.
 Fast Rhythmic Bursting Can Be Induced in Layer 2/3
 Cortical Neurons by Enhancing Persistent Na(+)
 Conductance or by Blocking BK Channels.J Neurophysiol.
 2003 Feb;89(2):909-21.
 
 to NEURON
 
 */
 
 begintemplate TCR
	public type
 
 // parts of the template were lifted from a default
 // cell writing from Network Builder NetGUI[0]
 
         public is_art
         public init, topol, basic_shape, subsets
         public geom, biophys 
         public synlist, x, y, z, position
         public connect2target
         public set_netcon_src_comp
         // the above function added to set neton
         // compartment source in the presyn cell
 
         public comp, level, Soma, Dendrites
         public Soma_Dendrites, Axon, all
         public presyn_comp, top_level
         // it is the responsibility of the calling
         // program to set the above presynapf_tcrtic
         // compartment number
 
         external traub_connect
         objref this
  create  comp[ 137+1]
         objref level[ 4+1], Soma, Dendrites
         objref Soma_Dendrites, Axon
         objref synlist
func type() {return       12 }

         proc init() {
           doubler = 1
  comp[0] delete_section() // clean up for fortran code
            traub_connect( 137+1)
 
            titlePrint()
 
            presyn_comp = 135
            // in Traub model;changed by calling prog.
            objref Soma, Axon, Dendrites, Soma_Dendrites
            objref level
 
            topol()
            shape()
 
            geom()        // the geometry and
            subsets()        // subsets and
            biophys()  // active currents
            synlist = new List() // list of synapses
 // NetGUI[0] stores synapses in the cell object, in 
 // Traub model it is easier to store them outside
            set_doubler() // to double or not
            if (doubler) {double_dend_cond()}
                          /* for taking
  spine membrane area correction into account (the 
  method used doubles max cond's when spines present)
 */
             more_adjustments()
         }
         proc double_dend_cond() {
         /* this function gets replaced later with 
 another one if double_dend_cond() is tacked on. */
         }
 
         proc titlePrint() {
 
 /*              print "
                 print "-----"
                 print "
             print "TCR Neuron Model based on "
             print "Traub RD et al (2005, 2003)"
                 print "
                 print "-----"
 Remove title printing with this comment for now.  
 Printing otherwise repeats (for each cell)
 -too voluminous for a network creation */
         }
 
         proc set_doubler() {doubler=1}
         // this function gets replaced with one that
         // sets doubler to 0 when there are no spines
         // in the cell (for no spines the additional
         // hoc code is written from integrate_cell.f
         // where cell is nRT, TCR.  Woops I just
         // found that deepaxax, deepbask, deepLTS,
         // supaxax, supbask, supLTS all use the script
         // cell/run_fortran.sh to replace the =1's with
         // =0's.  I will change the fortran code to
         // make it all run_fortran.sh replacements or
         // not for uniformity.
         proc topol() {
 // create comp[ 138] // note one greater than numcomp due to fortran indicies
  // last argument, parent location for connection
  // is overwritten to 1 for parents with connected children 
  // in below traub_connect proc calls
 traub_connect(this,  1,  132,   0.0796751205, 0)
 traub_connect(this,  1,  2,   0.0946071642, 1)
 traub_connect(this,  1,  15,   0.0946071642, 1)
 traub_connect(this,  1,  28,   0.0946071642, 1)
 traub_connect(this,  1,  41,   0.0946071642, 1)
 traub_connect(this,  1,  54,   0.0946071642, 1)
 traub_connect(this,  1,  67,   0.0946071642, 1)
 traub_connect(this,  1,  80,   0.0946071642, 1)
 traub_connect(this,  1,  93,   0.0946071642, 1)
 traub_connect(this,  1,  106,   0.0946071642, 1)
 traub_connect(this,  1,  119,   0.0946071642, 1)
 traub_connect(this,  2,  3,   0.0174185429,  1.)
 traub_connect(this,  2,  4,   0.0174185429,  1.)
 traub_connect(this,  2,  5,   0.0174185429,  1.)
 traub_connect(this,  3,  6,   0.00766658232, 1)
 traub_connect(this,  3,  7,   0.00766658232, 1)
 traub_connect(this,  3,  8,   0.00766658232, 1)
 traub_connect(this,  4,  9,   0.00766658232, 1)
 traub_connect(this,  4,  10,   0.00766658232, 1)
 traub_connect(this,  4,  11,   0.00766658232, 1)
 traub_connect(this,  5,  12,   0.00766658232, 1)
 traub_connect(this,  5,  13,   0.00766658232, 1)
 traub_connect(this,  5,  14,   0.00766658232, 1)
 traub_connect(this,  6,  7,   0.00598951744, 1)
 traub_connect(this,  6,  8,   0.00598951744, 1)
 traub_connect(this,  7,  8,   0.00598951744, 1)
 traub_connect(this,  9,  10,   0.00598951744, 1)
 traub_connect(this,  9,  11,   0.00598951744, 1)
 traub_connect(this,  10,  11,   0.00598951744, 1)
 traub_connect(this,  12,  13,   0.00598951744, 1)
 traub_connect(this,  12,  14,   0.00598951744, 1)
 traub_connect(this,  13,  14,   0.00598951744, 1)
 traub_connect(this,  15,  16,   0.0174185429,  1.)
 traub_connect(this,  15,  17,   0.0174185429,  1.)
 traub_connect(this,  15,  18,   0.0174185429,  1.)
 traub_connect(this,  16,  19,   0.00766658232, 1)
 traub_connect(this,  16,  20,   0.00766658232, 1)
 traub_connect(this,  16,  21,   0.00766658232, 1)
 traub_connect(this,  17,  22,   0.00766658232, 1)
 traub_connect(this,  17,  23,   0.00766658232, 1)
 traub_connect(this,  17,  24,   0.00766658232, 1)
 traub_connect(this,  18,  25,   0.00766658232, 1)
 traub_connect(this,  18,  26,   0.00766658232, 1)
 traub_connect(this,  18,  27,   0.00766658232, 1)
 traub_connect(this,  19,  20,   0.00598951744, 1)
 traub_connect(this,  19,  21,   0.00598951744, 1)
 traub_connect(this,  20,  21,   0.00598951744, 1)
 traub_connect(this,  22,  23,   0.00598951744, 1)
 traub_connect(this,  22,  24,   0.00598951744, 1)
 traub_connect(this,  23,  24,   0.00598951744, 1)
 traub_connect(this,  25,  26,   0.00598951744, 1)
 traub_connect(this,  25,  27,   0.00598951744, 1)
 traub_connect(this,  26,  27,   0.00598951744, 1)
 traub_connect(this,  28,  29,   0.0174185429,  1.)
 traub_connect(this,  28,  30,   0.0174185429,  1.)
 traub_connect(this,  28,  31,   0.0174185429,  1.)
 traub_connect(this,  29,  32,   0.00766658232, 1)
 traub_connect(this,  29,  33,   0.00766658232, 1)
 traub_connect(this,  29,  34,   0.00766658232, 1)
 traub_connect(this,  30,  35,   0.00766658232, 1)
 traub_connect(this,  30,  36,   0.00766658232, 1)
 traub_connect(this,  30,  37,   0.00766658232, 1)
 traub_connect(this,  31,  38,   0.00766658232, 1)
 traub_connect(this,  31,  39,   0.00766658232, 1)
 traub_connect(this,  31,  40,   0.00766658232, 1)
 traub_connect(this,  32,  33,   0.00598951744, 1)
 traub_connect(this,  32,  34,   0.00598951744, 1)
 traub_connect(this,  33,  34,   0.00598951744, 1)
 traub_connect(this,  35,  36,   0.00598951744, 1)
 traub_connect(this,  35,  37,   0.00598951744, 1)
 traub_connect(this,  36,  37,   0.00598951744, 1)
 traub_connect(this,  38,  39,   0.00598951744, 1)
 traub_connect(this,  38,  40,   0.00598951744, 1)
 traub_connect(this,  39,  40,   0.00598951744, 1)
 traub_connect(this,  41,  42,   0.0174185429,  1.)
 traub_connect(this,  41,  43,   0.0174185429,  1.)
 traub_connect(this,  41,  44,   0.0174185429,  1.)
 traub_connect(this,  42,  45,   0.00766658232, 1)
 traub_connect(this,  42,  46,   0.00766658232, 1)
 traub_connect(this,  42,  47,   0.00766658232, 1)
 traub_connect(this,  43,  48,   0.00766658232, 1)
 traub_connect(this,  43,  49,   0.00766658232, 1)
 traub_connect(this,  43,  50,   0.00766658232, 1)
 traub_connect(this,  44,  51,   0.00766658232, 1)
 traub_connect(this,  44,  52,   0.00766658232, 1)
 traub_connect(this,  44,  53,   0.00766658232, 1)
 traub_connect(this,  45,  46,   0.00598951744, 1)
 traub_connect(this,  45,  47,   0.00598951744, 1)
 traub_connect(this,  46,  47,   0.00598951744, 1)
 traub_connect(this,  48,  49,   0.00598951744, 1)
 traub_connect(this,  48,  50,   0.00598951744, 1)
 traub_connect(this,  49,  50,   0.00598951744, 1)
 traub_connect(this,  51,  52,   0.00598951744, 1)
 traub_connect(this,  51,  53,   0.00598951744, 1)
 traub_connect(this,  52,  53,   0.00598951744, 1)
 traub_connect(this,  54,  55,   0.0174185429,  1.)
 traub_connect(this,  54,  56,   0.0174185429,  1.)
 traub_connect(this,  54,  57,   0.0174185429,  1.)
 traub_connect(this,  55,  58,   0.00766658232, 1)
 traub_connect(this,  55,  59,   0.00766658232, 1)
 traub_connect(this,  55,  60,   0.00766658232, 1)
 traub_connect(this,  56,  61,   0.00766658232, 1)
 traub_connect(this,  56,  62,   0.00766658232, 1)
 traub_connect(this,  56,  63,   0.00766658232, 1)
 traub_connect(this,  57,  64,   0.00766658232, 1)
 traub_connect(this,  57,  65,   0.00766658232, 1)
 traub_connect(this,  57,  66,   0.00766658232, 1)
 traub_connect(this,  58,  59,   0.00598951744, 1)
 traub_connect(this,  58,  60,   0.00598951744, 1)
 traub_connect(this,  59,  60,   0.00598951744, 1)
 traub_connect(this,  61,  62,   0.00598951744, 1)
 traub_connect(this,  61,  63,   0.00598951744, 1)
 traub_connect(this,  62,  63,   0.00598951744, 1)
 traub_connect(this,  64,  65,   0.00598951744, 1)
 traub_connect(this,  64,  66,   0.00598951744, 1)
 traub_connect(this,  65,  66,   0.00598951744, 1)
 traub_connect(this,  67,  68,   0.0174185429,  1.)
 traub_connect(this,  67,  69,   0.0174185429,  1.)
 traub_connect(this,  67,  70,   0.0174185429,  1.)
 traub_connect(this,  68,  71,   0.00766658232, 1)
 traub_connect(this,  68,  72,   0.00766658232, 1)
 traub_connect(this,  68,  73,   0.00766658232, 1)
 traub_connect(this,  69,  74,   0.00766658232, 1)
 traub_connect(this,  69,  75,   0.00766658232, 1)
 traub_connect(this,  69,  76,   0.00766658232, 1)
 traub_connect(this,  70,  77,   0.00766658232, 1)
 traub_connect(this,  70,  78,   0.00766658232, 1)
 traub_connect(this,  70,  79,   0.00766658232, 1)
 traub_connect(this,  71,  72,   0.00598951744, 1)
 traub_connect(this,  71,  73,   0.00598951744, 1)
 traub_connect(this,  72,  73,   0.00598951744, 1)
 traub_connect(this,  74,  75,   0.00598951744, 1)
 traub_connect(this,  74,  76,   0.00598951744, 1)
 traub_connect(this,  75,  76,   0.00598951744, 1)
 traub_connect(this,  77,  78,   0.00598951744, 1)
 traub_connect(this,  77,  79,   0.00598951744, 1)
 traub_connect(this,  78,  79,   0.00598951744, 1)
 traub_connect(this,  80,  81,   0.0174185429,  1.)
 traub_connect(this,  80,  82,   0.0174185429,  1.)
 traub_connect(this,  80,  83,   0.0174185429,  1.)
 traub_connect(this,  81,  84,   0.00766658232, 1)
 traub_connect(this,  81,  85,   0.00766658232, 1)
 traub_connect(this,  81,  86,   0.00766658232, 1)
 traub_connect(this,  82,  87,   0.00766658232, 1)
 traub_connect(this,  82,  88,   0.00766658232, 1)
 traub_connect(this,  82,  89,   0.00766658232, 1)
 traub_connect(this,  83,  90,   0.00766658232, 1)
 traub_connect(this,  83,  91,   0.00766658232, 1)
 traub_connect(this,  83,  92,   0.00766658232, 1)
 traub_connect(this,  84,  85,   0.00598951744, 1)
 traub_connect(this,  84,  86,   0.00598951744, 1)
 traub_connect(this,  85,  86,   0.00598951744, 1)
 traub_connect(this,  87,  88,   0.00598951744, 1)
 traub_connect(this,  87,  89,   0.00598951744, 1)
 traub_connect(this,  88,  89,   0.00598951744, 1)
 traub_connect(this,  90,  91,   0.00598951744, 1)
 traub_connect(this,  90,  92,   0.00598951744, 1)
 traub_connect(this,  91,  92,   0.00598951744, 1)
 traub_connect(this,  93,  94,   0.0174185429,  1.)
 traub_connect(this,  93,  95,   0.0174185429,  1.)
 traub_connect(this,  93,  96,   0.0174185429,  1.)
 traub_connect(this,  94,  97,   0.00766658232, 1)
 traub_connect(this,  94,  98,   0.00766658232, 1)
 traub_connect(this,  94,  99,   0.00766658232, 1)
 traub_connect(this,  95,  100,   0.00766658232, 1)
 traub_connect(this,  95,  101,   0.00766658232, 1)
 traub_connect(this,  95,  102,   0.00766658232, 1)
 traub_connect(this,  96,  103,   0.00766658232, 1)
 traub_connect(this,  96,  104,   0.00766658232, 1)
 traub_connect(this,  96,  105,   0.00766658232, 1)
 traub_connect(this,  97,  98,   0.00598951744, 1)
 traub_connect(this,  97,  99,   0.00598951744, 1)
 traub_connect(this,  98,  99,   0.00598951744, 1)
 traub_connect(this,  100,  101,   0.00598951744, 1)
 traub_connect(this,  100,  102,   0.00598951744, 1)
 traub_connect(this,  101,  102,   0.00598951744, 1)
 traub_connect(this,  103,  104,   0.00598951744, 1)
 traub_connect(this,  103,  105,   0.00598951744, 1)
 traub_connect(this,  104,  105,   0.00598951744, 1)
 traub_connect(this,  106,  107,   0.0174185429,  1.)
 traub_connect(this,  106,  108,   0.0174185429,  1.)
 traub_connect(this,  106,  109,   0.0174185429,  1.)
 traub_connect(this,  107,  110,   0.00766658232, 1)
 traub_connect(this,  107,  111,   0.00766658232, 1)
 traub_connect(this,  107,  112,   0.00766658232, 1)
 traub_connect(this,  108,  113,   0.00766658232, 1)
 traub_connect(this,  108,  114,   0.00766658232, 1)
 traub_connect(this,  108,  115,   0.00766658232, 1)
 traub_connect(this,  109,  116,   0.00766658232, 1)
 traub_connect(this,  109,  117,   0.00766658232, 1)
 traub_connect(this,  109,  118,   0.00766658232, 1)
 traub_connect(this,  110,  111,   0.00598951744, 1)
 traub_connect(this,  110,  112,   0.00598951744, 1)
 traub_connect(this,  111,  112,   0.00598951744, 1)
 traub_connect(this,  113,  114,   0.00598951744, 1)
 traub_connect(this,  113,  115,   0.00598951744, 1)
 traub_connect(this,  114,  115,   0.00598951744, 1)
 traub_connect(this,  116,  117,   0.00598951744, 1)
 traub_connect(this,  116,  118,   0.00598951744, 1)
 traub_connect(this,  117,  118,   0.00598951744, 1)
 traub_connect(this,  119,  120,   0.0174185429,  1.)
 traub_connect(this,  119,  121,   0.0174185429,  1.)
 traub_connect(this,  119,  122,   0.0174185429,  1.)
 traub_connect(this,  120,  123,   0.00766658232, 1)
 traub_connect(this,  120,  124,   0.00766658232, 1)
 traub_connect(this,  120,  125,   0.00766658232, 1)
 traub_connect(this,  121,  126,   0.00766658232, 1)
 traub_connect(this,  121,  127,   0.00766658232, 1)
 traub_connect(this,  121,  128,   0.00766658232, 1)
 traub_connect(this,  122,  129,   0.00766658232, 1)
 traub_connect(this,  122,  130,   0.00766658232, 1)
 traub_connect(this,  122,  131,   0.00766658232, 1)
 traub_connect(this,  123,  124,   0.00598951744, 1)
 traub_connect(this,  123,  125,   0.00598951744, 1)
 traub_connect(this,  124,  125,   0.00598951744, 1)
 traub_connect(this,  126,  127,   0.00598951744, 1)
 traub_connect(this,  126,  128,   0.00598951744, 1)
 traub_connect(this,  127,  128,   0.00598951744, 1)
 traub_connect(this,  129,  130,   0.00598951744, 1)
 traub_connect(this,  129,  131,   0.00598951744, 1)
 traub_connect(this,  130,  131,   0.00598951744, 1)
 traub_connect(this,  132,  133,   0.0348744292,  1.)
 traub_connect(this,  133,  134,   0.0208024203, 1)
 traub_connect(this,  133,  136,   0.0208024203, 1)
 traub_connect(this,  134,  135,   0.01570795,  1.)
 traub_connect(this,  134,  136,   0.01570795, 1)
 traub_connect(this,  136,  137,   0.01570795,  1.)
 access comp[1] // handy statement if want to start gui's from nrnmainmenu
 }
         proc geom() {
 // the "traub level" subsets are created and defined below
 top_level =  4
 objref level[top_level+1]
 for i=0,top_level { level[i] = new SectionList() }
  
 comp[ 1] { level[ 1].append() L=  42. diam = 2*  10. }
 comp[ 2] { level[ 2].append() L=  20. diam = 2*  0.73 }
 comp[ 3] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 4] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 5] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 6] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 7] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 8] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 9] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 10] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 11] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 12] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 13] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 14] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 15] { level[ 2].append() L=  20. diam = 2*  0.73 }
 comp[ 16] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 17] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 18] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 19] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 20] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 21] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 22] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 23] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 24] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 25] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 26] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 27] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 28] { level[ 2].append() L=  20. diam = 2*  0.73 }
 comp[ 29] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 30] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 31] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 32] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 33] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 34] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 35] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 36] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 37] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 38] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 39] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 40] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 41] { level[ 2].append() L=  20. diam = 2*  0.73 }
 comp[ 42] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 43] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 44] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 45] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 46] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 47] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 48] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 49] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 50] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 51] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 52] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 53] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 54] { level[ 2].append() L=  20. diam = 2*  0.73 }
 comp[ 55] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 56] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 57] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 58] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 59] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 60] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 61] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 62] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 63] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 64] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 65] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 66] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 67] { level[ 2].append() L=  20. diam = 2*  0.73 }
 comp[ 68] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 69] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 70] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 71] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 72] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 73] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 74] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 75] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 76] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
       geom1() /* arbitrary subdivision of geom helps
     to large a function problem in tcr_template */
 }
         proc geom1() {
 comp[ 77] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 78] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 79] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 80] { level[ 2].append() L=  20. diam = 2*  0.73 }
 comp[ 81] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 82] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 83] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 84] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 85] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 86] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 87] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 88] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 89] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 90] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 91] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 92] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 93] { level[ 2].append() L=  20. diam = 2*  0.73 }
 comp[ 94] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 95] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 96] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 97] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 98] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 99] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 100] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 101] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 102] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 103] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 104] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 105] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 106] { level[ 2].append() L=  20. diam = 2*  0.73 }
 comp[ 107] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 108] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 109] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 110] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 111] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 112] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 113] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 114] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 115] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 116] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 117] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 118] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 119] { level[ 2].append() L=  20. diam = 2*  0.73 }
 comp[ 120] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 121] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 122] { level[ 3].append() L=  57.5 diam = 2*  0.584 }
 comp[ 123] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 124] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 125] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 126] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 127] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 128] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 129] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 130] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 131] { level[ 4].append() L=  57.5 diam = 2*  0.438 }
 comp[ 132] { level[ 0].append() L=  50. diam = 2*  0.8 }
 comp[ 133] { level[ 0].append() L=  50. diam = 2*  0.7 }
 comp[ 134] { level[ 0].append() L=  50. diam = 2*  0.5 }
 comp[ 135] { level[ 0].append() L=  50. diam = 2*  0.5 }
 comp[ 136] { level[ 0].append() L=  50. diam = 2*  0.5 }
 comp[ 137] { level[ 0].append() L=  50. diam = 2*  0.5 }
 } 
 // Here are some commonly used subsets of sections
         objref all
         proc subsets() { local i
           objref Soma, Dendrites, Soma_Dendrites, Axon
           objref all
           Soma = new SectionList()
           Dendrites = new SectionList()
           Soma_Dendrites = new SectionList()
           Axon = new SectionList()
           for i=1,top_level {
             forsec level[i] { // recall level 0 is axon, 1 is soma, higher are dends
               Soma_Dendrites.append()
                 if (i>1) {Dendrites.append()}
             }
           }
           forsec level[1] {
             Soma.append()
           }
           forsec level[0] { Axon.append() }
           all = new SectionList()
           for i=1, 137 comp[i] all.append()
          }
 
        proc shape() {
 
 /*      This section could contain statements like
 {pt3dclear() pt3dadd(-1,-1,0,1) pt3dadd(-1,-2,0,1)}
 These visual settings do not effect the electrical
 and chemical systems of equations.              */
 }
         proc biophys() {
 // 
 //       insert the mechanisms and assign max conductances
 // 
 forsec all { insert pas }   // g_pas has two values; soma-dend,axon
 forsec level[ 0] {
       insert naf_tcr
       gbar_naf_tcr =   0.4
       insert kdr
       gbar_kdr =   0.4
       insert ka
       gbar_ka =   0.001
       insert k2
       gbar_k2 =   0.0005
 }
 forsec level[ 1] {
       insert naf_tcr
       gbar_naf_tcr =   0.1
       insert napf_tcr
       gbar_napf_tcr =   0.0002
       insert kdr
       gbar_kdr =   0.075
       insert kc
       gbar_kc =   0.012
       insert ka
       gbar_ka =   0.03
       insert km
       gbar_km =   0 // 0.0005
       insert k2
       gbar_k2 =   0.002
       insert kahp_slower
       gbar_kahp_slower =   0 // 5.E-05
       insert cal
       gbar_cal =   0.0005
       insert cat
       gbar_cat =   0.0005
       insert ar
       gbar_ar =   0.00025
       insert cad
       // *** ca diffusion: beta=1/tau
       beta_cad  =   0.02
       // cafor(I) (FORTRAN) converted to phi (NEURON)
       phi_cad =   52000.
 }
 forsec level[ 2] {
       insert naf_tcr
       gbar_naf_tcr =   0.1
       insert napf_tcr
       gbar_napf_tcr =   0.0002
       insert kdr
       gbar_kdr =   0.05
       insert kc
       gbar_kc =   0.012
       insert ka
       gbar_ka =   0.03
       insert km
       gbar_km =   0 // 0.0005
       insert k2
       gbar_k2 =   0.002
       insert kahp_slower
       gbar_kahp_slower =   0 // 5.E-05
       insert cal
       gbar_cal =   0.0005
       insert cat
       gbar_cat =   0.005
       insert ar
       gbar_ar =   0.0005
       insert cad
       // *** ca diffusion: beta=1/tau
       beta_cad  =   0.05
       // cafor(I) (FORTRAN) converted to phi (NEURON)
       phi_cad =   104000.
 }
 forsec level[ 3] {
       insert naf_tcr
       gbar_naf_tcr =   0.005
       insert napf_tcr
       gbar_napf_tcr =   1.E-05
       insert kc
       gbar_kc =   0.02
       insert ka
       gbar_ka =   0.001
       insert km
       gbar_km =   0 // 0.0005
       insert k2
       gbar_k2 =   0.002
       insert kahp_slower
       gbar_kahp_slower =   0 // 5.E-05
       insert cal
       gbar_cal =   0.00025
       insert cat
       gbar_cat =   0.003
       insert ar
       gbar_ar =   0.0003
       insert cad
       // *** ca diffusion: beta=1/tau
       beta_cad  =   0.05
       // cafor(I) (FORTRAN) converted to phi (NEURON)
       phi_cad =   104000.
 }
 forsec level[ 4] {
       insert naf_tcr
       gbar_naf_tcr =   0.005
       insert napf_tcr
       gbar_napf_tcr =   1.E-05
       insert kc
       gbar_kc =   0.02
       insert ka
       gbar_ka =   0.001
       insert km
       gbar_km =   0 // 0.0005
       insert k2
       gbar_k2 =   0.002
       insert kahp_slower
       gbar_kahp_slower =   0 // 5.E-05
       insert cal
       gbar_cal =   0.00025
       insert cat
       gbar_cat =   0.0005
       insert ar
       gbar_ar =   0.0003
       insert cad
       // *** ca diffusion: beta=1/tau
       beta_cad  =   0.05
       // cafor(I) (FORTRAN) converted to phi (NEURON)
       phi_cad =   104000.
 }
 forsec all {
    cm =   0.9  // assign global specific capac.
 }
 // 
 //  passive membrane resistance (leak) and axial resistance
 // 
 forsec Soma_Dendrites {
    g_pas =   3.78787879E-05
    Ra =   175.
 }
 forsec Axon {
    g_pas =   0.001
    Ra =   100.
 }
 ceiling_cad = 1e6 //  nearly unlimited Ca concentration
 // print "made it to end of initialization from SCORTMAJ_FRB()"
 }  // end of biophys
 
 // Compartment Area: Dendritic.spines double area of
 // dend. membrane, which in Traubs method is equivalent to
 // only multiplying all dend. max conductances by two
 // (the area is doubled but the volume is const.)
 proc double_dend_cond() {
   spine_area_multiplier = 2
   forsec Dendrites {
        if (ismembrane("napf_tcr")) { gbar_napf_tcr *= spine_area_multiplier }
        if (ismembrane("napf_tcrf")) { gbar_napf_tcrf *= spine_area_multiplier }
        if (ismembrane("napf_tcrf_tcr")) { gbar_napf_tcrf_tcr *= spine_area_multiplier }
        if (ismembrane("naf_tcr")) { gbar_naf_tcr *= spine_area_multiplier }
        if (ismembrane("naf_tcr_tcr")) { gbar_naf_tcr_tcr *= spine_area_multiplier }
        if (ismembrane("naf_tcr2")) { gbar_naf_tcr2 *= spine_area_multiplier }
        if (ismembrane("kc")) { gbar_kc *= spine_area_multiplier }
        if (ismembrane("kc_fast")) { gbar_kc_fast *= spine_area_multiplier }
        if (ismembrane("kahp")) { gbar_kahp *= spine_area_multiplier }
        if (ismembrane("kahp_slower")) { gbar_kahp_slower *= spine_area_multiplier }
        if (ismembrane("km")) { gbar_km *= spine_area_multiplier }
        if (ismembrane("kdr")) { gbar_kdr *= spine_area_multiplier }
        if (ismembrane("kdr_fs")) { gbar_kdr_fs *= spine_area_multiplier }
        if (ismembrane("ka")) { gbar_ka *= spine_area_multiplier }
        if (ismembrane("ka_ib")) { gbar_ka_ib *= spine_area_multiplier }
        if (ismembrane("k2")) { gbar_k2 *= spine_area_multiplier }
        if (ismembrane("cal")) { gbar_cal *= spine_area_multiplier }
        if (ismembrane("cat")) { gbar_cat *= spine_area_multiplier }
        if (ismembrane("cat_a")) { gbar_cat_a *= spine_area_multiplier }
        if (ismembrane("ar")) { gbar_ar *= spine_area_multiplier }
        if (ismembrane("pas")) { g_pas *= spine_area_multiplier }
        cm = cm * spine_area_multiplier
   }
 }
 // double_dend_cond()  // run for cells w/ spines
 
 // The below is after doubling of dendritic area to
 // take into account the effect of spines
 // These areas were used in the FORTRAN code to 
 // compute the conductances from specific conductances.
 //  I AREA(I) (compartments and their areas)
 //  1   2638.9356
 //  2   91.734428
 //  3   210.989184
 //  4   210.989184
 //  5   210.989184
 //  6   158.241888
 //  7   158.241888
 //  8   158.241888
 //  9   158.241888
 //  10   158.241888
 //  11   158.241888
 //  12   158.241888
 //  13   158.241888
 //  14   158.241888
 //  15   91.734428
 //  16   210.989184
 //  17   210.989184
 //  18   210.989184
 //  19   158.241888
 //  20   158.241888
 //  21   158.241888
 //  22   158.241888
 //  23   158.241888
 //  24   158.241888
 //  25   158.241888
 //  26   158.241888
 //  27   158.241888
 //  28   91.734428
 //  29   210.989184
 //  30   210.989184
 //  31   210.989184
 //  32   158.241888
 //  33   158.241888
 //  34   158.241888
 //  35   158.241888
 //  36   158.241888
 //  37   158.241888
 //  38   158.241888
 //  39   158.241888
 //  40   158.241888
 //  41   91.734428
 //  42   210.989184
 //  43   210.989184
 //  44   210.989184
 //  45   158.241888
 //  46   158.241888
 //  47   158.241888
 //  48   158.241888
 //  49   158.241888
 //  50   158.241888
 //  51   158.241888
 //  52   158.241888
 //  53   158.241888
 //  54   91.734428
 //  55   210.989184
 //  56   210.989184
 //  57   210.989184
 //  58   158.241888
 //  59   158.241888
 //  60   158.241888
 //  61   158.241888
 //  62   158.241888
 //  63   158.241888
 //  64   158.241888
 //  65   158.241888
 //  66   158.241888
 //  67   91.734428
 //  68   210.989184
 //  69   210.989184
 //  70   210.989184
 //  71   158.241888
 //  72   158.241888
 //  73   158.241888
 //  74   158.241888
 //  75   158.241888
 //  76   158.241888
 //  77   158.241888
 //  78   158.241888
 //  79   158.241888
 //  80   91.734428
 //  81   210.989184
 //  82   210.989184
 //  83   210.989184
 //  84   158.241888
 //  85   158.241888
 //  86   158.241888
 //  87   158.241888
 //  88   158.241888
 //  89   158.241888
 //  90   158.241888
 //  91   158.241888
 //  92   158.241888
 //  93   91.734428
 //  94   210.989184
 //  95   210.989184
 //  96   210.989184
 //  97   158.241888
 //  98   158.241888
 //  99   158.241888
 //  100   158.241888
 //  101   158.241888
 //  102   158.241888
 //  103   158.241888
 //  104   158.241888
 //  105   158.241888
 //  106   91.734428
 //  107   210.989184
 //  108   210.989184
 //  109   210.989184
 //  110   158.241888
 //  111   158.241888
 //  112   158.241888
 //  113   158.241888
 //  114   158.241888
 //  115   158.241888
 //  116   158.241888
 //  117   158.241888
 //  118   158.241888
 //  119   91.734428
 //  120   210.989184
 //  121   210.989184
 //  122   210.989184
 //  123   158.241888
 //  124   158.241888
 //  125   158.241888
 //  126   158.241888
 //  127   158.241888
 //  128   158.241888
 //  129   158.241888
 //  130   158.241888
 //  131   158.241888
 //  132   251.3272
 //  133   219.9113
 //  134   157.0795
 //  135   157.0795
 //  136   157.0795
 //  137   157.0795
        proc position() { local i
 // comp switched to comp[1] since 0 deleted
         comp[1] for i = 0, n3d()-1 {
     pt3dchange(i, $1-x+x3d(i), \
      $2-y+y3d(i), $3-z+z3d(i),diam3d(i))
        }
         x=$1 y=$2 z=$3
        }
         proc connect2target() { 
  // $o1 targ point process, $o2 returned NetCon
           comp[presyn_comp] $o2 = new NetCon(&v(1),$o1)
	$o2.threshold = 0
         }
         objref syn_
         proc synapses() {
         // place for each compartment that has input
         // statements like 
 //comp[3] syn_=new AlphaSynKinT(1) synlist.append(syn_)
 //comp[4] syn_=new NMDA(1) synlist.append(syn_)
         }
 
 // is not an artificial cell:
      func is_art() { return 0 }
 
 
 
         proc more_adjustments() {
 forsec all {
    // global reversal potentials
    ek =  -95.
    e_pas =  -70.
    ena =   50.
    vca =   125.
    forsec all if (ismembrane("ar")) erev_ar =  -35.
    e_gaba_a =  -81.
 }
  // in FORTRAN do find values
 // i= 2
 // i= 15
 // i= 28
 // i= 41
 // i= 54
 // i= 67
 // i= 80
 // i= 93
 // i= 106
 // i= 119
 //extended initializations
   for i=1,137 {
     comp[i] if (ismembrane("ka")) {gbar_ka*=0.2}
   }
   for i = 132, 137 { // axon
     comp[i] gbar_kdr *= 0.45
   }
   comp[1]  gbar_kdr *= 0.45
   for (i = 2; i<=119; i += 13) {  // level 2
     comp[i] gbar_kdr *= 0.45
   }
 
    persistentNa_shift = 7
 // in the fortran code the napf_tcrf has a 10 mV shift
 // but uses the naf_tcr rates (apham_...) which were
 // created with a -3 mV shift for total 7 mV 
    forsec all { if (ismembrane("napf_tcr")){
                 fastNa_shift_napf_tcr = persistentNa_shift}
    }
 }
          proc set_doubler() {doubler=0}
          // this function sets doubler to 0 
          // because there are no spines
          // in the cell, replacing earlier fnc.
  endtemplate TCR

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