Dataset 1:
Dataset 2:
Dataset 3:
Three Point Process Datasets
Time (sec)
Poisson Likelihood
14 x 1023
12 10 8 6 4 2
0()
0 5 10 15 20 25 30 35 40 45 50
Lambda (Hz)
Likelihood
Dataset 1:
Dataset 2:
Dataset 3:
Spike Train Data
Time (sec)
Dataset 1:1 0.5
0 0
20 10
0 0 Dataset 3:1
0.5 0 0
0. 02
0. 04
0. 06
0. 08
0. 1
0. 12
0. 14
0. 16
0. 18
0. 2
Waiting Time Data
Dataset 2:
0. 02
0. 04
0. 06
0. 08
0. 1
0. 12
0. 14
0. 16
0. 18
0. 2
0. 02
0. 04
0. 06
0. 08
0. 1
0. 12
0. 14
0. 16
0. 18
0. 2
Time (sec)
Dataset 1:
Dataset 2: Dataset 3:
Waiting Time Histograms
0.04
Waiting Time (sec) Waiting Time (sec) Waiting Time (sec)
Counts
1 0.8 0.6 0.4 0.2 0
1 0.8 0.6 0.4 0.2 0
1 0.8 0.6 0.4 0.2 0
0
0.05 0.1 0.15 0.2 0.25
Empirical Distributions
0
0.05 0.1 0.15 0.2 0.25
0
0.05 0.1 0.15 0.2 0.25
Waiting Time (sec)
Dataset 1:
KS Plots
Dataset 2: Dataset 3:
Empirical CDF Empirical CDF
Empirical CDF
Model CDF
Dataset 1:
KS Plots
Dataset 2:
Dataset 3:
Empirical CDF
KS Stat = 0.126
Empirical CDF
KS Stat = 0.632
Empirical CDF
KS Stat = 0.312
Model CDF
Dataset 1:
QQ Plots
Dataset 2: Dataset 3:
Empirical Quantiles Empirical Quantiles Empirical Quantiles
Model Quantiles
Waiting Time Autocorrelation Functions
Dataset 1:
Dataset 2: Dataset 3:
Lag Lag Lag
Fano Factor (1 msec bins)
Time (sec)
FF1,FF2,FF3
Fano Factor (40 msec bins)
Time (sec)
FF2 FF1 FF3
Summary
Dataset 1
Dataset 2
Dataset 3
Hist
P
X
P
KS
P
X
X
QQ
P
All Quantiles 0.04
Off by Factor of 2
Fano Factor
P
X
P
ACF
P
X
P
Dataset 1:
Dataset 2:
Dataset 3:
Spike Train Data
Time (sec)