Increased computational accuracy in multi-compartmental cable models (Lindsay et al. 2005)

 Download zip file 
Help downloading and running models
Accession:129149
Compartmental models of dendrites are the most widely used tool for investigating their electrical behaviour. Traditional models assign a single potential to a compartment. This potential is associated with the membrane potential at the centre of the segment represented by the compartment. All input to that segment, independent of its location on the segment, is assumed to act at the centre of the segment with the potential of the compartment. By contrast, the compartmental model introduced in this article assigns a potential to each end of a segment, and takes into account the location of input to a segment on the model solution by partitioning the effect of this input between the axial currents at the proximal and distal boundaries of segments. For a given neuron, the new and traditional approaches to compartmental modelling use the same number of locations at which the membrane potential is to be determined, and lead to ordinary differential equations that are structurally identical. However, the solution achieved by the new approach gives an order of magnitude better accuracy and precision than that achieved by the latter in the presence of point process input.
Reference:
1 . Lindsay AE, Lindsay KA, Rosenberg JR (2005) Increased computational accuracy in multi-compartmental cable models by a novel approach for precise point process localization. J Comput Neurosci 19:21-38 [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):
Channel(s): I Na,t; I K;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; C or C++ program;
Model Concept(s): Methods;
Implementer(s):
Search NeuronDB for information about:  I Na,t; I K;
/
LindsayEtAl2005
readme.txt
03-192.pdf
AnalyseResults.c
BitsAndPieces.c
CellData.dat
CompareSpikeTrain.c
Ed04.tex
ExactSolution.dat
GammaCode
Gen.tex
Gen1.tex
Gen2.tex
Gen3.tex
Gen4.tex
Gen5.tex
Gen6.tex
GenCom.c
GenCom1.c
GenCom2.c
GenComExactSoln.c
GenerateInput.c
GenerateInputText.c
GenRan.ran
GetNodeNumbers.c
Info100.dat
Info20.dat
Info200.dat
Info30.dat
Info300.dat
Info40.dat
Info400.dat
Info50.dat
Info500.dat
Info60.dat
Info70.dat
Info80.dat
Info90.dat
InputCurrents.dat
InputDendrite.dat
JaySpikeTrain.c
JayTest1.dat
JayTest100.dat
KenSpikeTrain.c
KenTest1.dat *
KenTest10.dat
KenTest100.dat *
KenTest10p.dat
KenTest1p.dat *
KenTest2.dat
KenTest2p.dat
KenTest3.dat
KenTest3p.dat
KenTest4.dat
KenTest4p.dat
KenTest5.dat
KenTest5p.dat
KenTest6.dat
KenTest6p.dat
KenTest7.dat
KenTest7p.dat
KenTest8.dat
KenTest8p.dat
KenTest9.dat
KenTest9p.dat
LU.c
Mean50.dat
Mean500.dat
mosinit.hoc
NC.pdf
NC.tex
NC1.tex
NC2.tex
NC3.tex
NC4.tex
NC5.tex
NC6.tex
NCFig2.eps *
NCFig3.eps *
NCFig4.eps *
NCFig5a.eps *
NCFig5b.eps *
NCFig6.eps *
NCPics.tex
NeuronDriver.hoc
NewComExactSoln.c
NewComp.pdf
NewComp.ps
NewComp.tex
NewComp.toc
NewComp1.tex
NewComp2.tex
NewComp3.tex
NewComp4.tex
NewComp5.tex
NewComp6.tex
NewCompFig1.eps
NewCompFig2.eps *
NewCompFig3.eps *
NewCompFig4.eps *
NewCompFig5a.eps *
NewCompFig5b.eps *
NewCompFig6.eps *
NewCompPics.tex
NewComSpikeTrain.c
NewRes.dat
NewRes60.dat
NewRes70.dat
NewRes80.dat
NewSynRes40.dat
NewTestCell.d3
NResults.res
OldComExactSoln.c
out.res
principles_01.tex
rand
Ratio.dat
RelErr.dat
ReviewOfSpines.pdf
SpikeTimes.dat
TestCell.d3
TestCell1.d3
TestCell2.d3
TestCell3.d3
TestCell4.d3
testcellnew2.hoc
TestCGS.c
TestGen1.c
TestSim.hoc
TestSim020.hoc
TestSim030.hoc
TestSim040.hoc
TestSim050.hoc
TestSim060.hoc
TestSim070.hoc
TestSim080.hoc
TestSim090.hoc
TestSim1.hoc
TestSim100.hoc
TestSim200.hoc
TestSim300.hoc
TestSim400.hoc
TestSim500
TestSim500.hoc
                            
15
167
215
257
299
306
324
379
395
424
457
500
506
525
537
618
623
628
642
831
943
956
961
985
990
1035
1068
1115
1172
1192
1197
1202
1215
1311
1317
1323
1363
1367
1431
1509
1585
1612
1630
1654
1675
1714
1757
1764
1845
1897
1916
1939
2007
2130
2190
2202
2213
2321
2358
2365
2435
2450
2468
2529
2577
2588
2623
2629
2645
2657
2676
2706
2740
2755
2792
2798
2890
2930
2963
2983
3085
3142
3147
3164
3246
3286
3307
3318
3334
3347
3356
3381
3521
3575
3640
3657
3714
3719
3742
3808
3847
3897
3961
4043
4061
4148
4210
4228
4247
4251
4279
4342
4367
4385
4391
4450
4598
4608
4614
4763
4769
4842
4877
4933
4949
5037
5133
5201
5211
5256
5262
5308
5332
5337
5342
5378
5400
5434
5453
5473
5664
5706
5752
5757
5769
5788
5797
5810
5824
5849
5905
5917
5942
5982
5990
5997
6024
6056
6066
6120
6180
6230
6247
6301
6342
6347
6484
6532
6733
6741
6805
6826
6864
6910
6915
6978
7039
7136
7153
7191
7218
7231
7256
7357
7370
7431
7437
7451
7473
7563
7575
7643
7696
7717
7736
7775
7781
7797
7810
7867
7873
7895
7913
7969
8036
8069
8117
8157
8203
8252
8257
8315
8362
8418
8423
8560
8578
8593
8677
8692
8716
8888
8894
8936
8966
8984
9049
9080
9088
9135
9140
9196
9202
9217
9225
9263
9278
9290
9322
9333
9462
9476
9486
9559
9594
9649
9654
9702
9724
9767
9783
9793
9825
9848
9853
9900
9961
9990

Loading data, please wait...