Skip to main content
. 2018 Feb 21;596(9):1681–1697. doi: 10.1113/JP275240

Table 1.

Testing the algorithm with different target neuron population distributions

Population A Population C Population D
Target Estimated Target Estimated Target Estimated
Parameter
μK,lt (mS cm−2) 3 2.998 3 2.999 3 2.997
μ,K,A (mS cm−2) 4 4.002 4 4.003 4 4.003
ρ 0.00 0.00 0.60 0.61 −0.60 −0.60
Proportions
Tonic (T) 0.274 0.273 0.332 0.333 0.196 0.195
Single (S) 0.086 0.086 0.034 0.033 0.159 0.158
Delayed (D) 0.275 0.276 0.206 0.206 0.375 0.376
Gap (G) 0.351 0.351 0.390 0.390 0.268 0.268
Reluctant (R) 0.012 0.012 0.038 0.038 0.000 0.000
MaxError
From volume 0.001 0.001 0.001
n sample  = 200 0.0368 ± 0.0162 0.0261 ± 0.0142 0.0334 ± 0.0189
n sample  = 100 0.0445 ± 0.0126 0.0461 ± 0.0187 0.0330 ± 0.0133
n sample  = 50 0.0997 ± 0.0303 0.0692 ± 0.0237 0.0911 ± 0.0374
n sample  = 25 0.0915 ± 0.0349 0.1263 ± 0.0765 0.1112 ± 0.0931

Population A, C, and D refer to conditions shown in the corresponding panels of Fig. 5. MaxError values for target proportions based on random sampling are mean ± standard deviation based on five tests for each condition.