library(ERP);require(mnormt);require(fdrtool);library(ggplot2);library(dplyr)
library(erpR);require(akima);library(reshape2)
load("ERPdata.RData")
downsample <- function(data,datacol,window) {
dta <- data
dta_signal <- dta[,datacol]
dta_othvar <- dta[,-datacol]
num1 <- (dim(dta_signal)[2] - (dim(dta_signal)[2] %% window)) /window
num2 <- dim(dta_signal)[2] %% window
dta_downsample <- data.frame(melt(apply(dta_signal[,1:window],1,mean)))
for (i in 1 : num1-1){
dta_downsample <- cbind(dta_downsample,
melt(apply(dta_signal[,(i*window+1):((i+1)*window)],
1,mean)))
}
if (num2 == 1) {
dta_downsample <- cbind(dta_downsample,
value=dta_signal[,(num1*window+num2)])
###### notice
}
if (num2 > 1) {
dta_downsample <- cbind(dta_downsample,
melt(apply(dta_signal[,(num1*window+1):(num1*window+num2)],
1,mean)))
}
dta_downsample <- dta_downsample[,-1]
colnames(dta_downsample) <- paste("value",1:dim(dta_downsample)[2],sep=".")
dta_final <- cbind(dta_othvar,dta_downsample)
return(dta_final)
}
down1 <- downsample(ERPdata,2:427,
window = 5) # User could set the inetrval
head(down1) # for example : 426/5 = 85...1 so we have 86 column of signal data.
Channel Experiment Condition Subject AveRT IQ value.1 value.2
1 Fp1 Exp1 nonword subj1 0.01340599 65 -1.448747 -1.7538242
2 Fp2 Exp1 nonword subj1 0.01340599 65 -1.692416 -0.9664565
3 F3 Exp1 nonword subj1 0.01340599 65 -1.175065 -0.5153238
4 F4 Exp1 nonword subj1 0.01340599 65 -1.834995 -0.8219859
5 C3 Exp1 nonword subj1 0.01340599 65 -2.579629 0.1202357
6 C4 Exp1 nonword subj1 0.01340599 65 -1.553004 -1.4506531
value.3 value.4 value.5 value.6 value.7 value.8
1 1.134164 0.80144384 0.70334599 -0.3567182 1.96236380 1.6490498
2 2.051617 2.42060020 -0.03335814 -0.5458316 -0.01624169 1.7533806
3 1.217749 0.61868294 1.46582836 0.8527114 -0.41047561 0.7933332
4 2.305153 1.63440630 1.65139752 0.3961878 -1.78412652 -1.1265126
5 1.844356 -0.08172358 2.06588464 0.8231720 -1.54670163 0.3318666
6 2.787830 1.93426540 2.81333840 0.7773958 -3.28025060 -1.9622388
value.9 value.10 value.11 value.12 value.13 value.14
1 -0.8549273 -1.9128494 -2.5726444 -3.725500 -2.1484353 -0.03361206
2 -0.1969592 -2.3466926 -0.7740782 -3.461775 -3.5646776 -0.40566694
3 -2.5968079 -0.9892234 -1.1700941 -2.774526 -1.1286006 1.72282400
4 -1.6126458 0.6911760 -0.8643106 -3.196172 -1.4797098 1.27905308
5 -2.9984740 1.0362673 -0.9700335 -3.074641 -0.4259591 1.50068058
6 -1.4823824 0.9484215 -1.3520605 -2.371366 -1.2415273 0.76093456
value.15 value.16 value.17 value.18 value.19 value.20
1 -1.8770490 -2.7516338 -3.286598 -1.06203976 -0.4740878 -2.3734516
2 -0.6799441 -2.5654820 -4.190713 0.00225218 0.1610651 -2.6067860
3 1.3765581 -1.5721360 -1.416721 1.60484388 1.5366693 0.8138367
4 2.4633468 -0.6035304 -1.123729 1.43181476 2.1561994 0.6206483
5 1.1837472 -2.5834447 -2.426380 -0.82940374 -0.1476383 -0.5779011
6 2.5985648 -1.5645513 -3.728205 0.59414952 0.9413817 -0.8333557
value.21 value.22 value.23 value.24 value.25 value.26 value.27
1 -0.6853584 1.849019 3.953445 5.590909 2.723299 -2.6182804 -3.8690666
2 -1.4994937 1.784485 2.419897 5.084390 1.324254 -6.4218750 -5.8454046
3 0.1668152 4.438832 5.177569 10.383056 8.266289 -0.6428960 0.5663092
4 0.8104309 3.001927 5.123970 8.680744 5.512865 -0.9854499 -4.1610670
5 -1.9682714 -1.692854 -1.048127 6.790622 5.636051 -0.2069056 0.4477197
6 -1.1339352 -1.357287 2.754686 7.532309 5.802012 1.7407745 -2.1390346
value.28 value.29 value.30 value.31 value.32 value.33 value.34
1 -1.8171379 -0.2383801 -1.624216 -4.020267 -9.425918 -9.337044 -8.148736
2 -2.6761752 -1.8380918 -2.662908 -6.748132 -9.989245 -10.210981 -8.277543
3 1.9450149 2.1383375 2.929998 -2.589037 -7.907762 -7.867462 -6.081466
4 0.4191879 1.2782512 1.883469 -4.019071 -8.446374 -7.556438 -5.643897
5 1.4885026 1.1493104 1.559550 -3.723119 -6.555097 -7.410677 -5.213345
6 1.8558870 2.7625554 3.502428 -2.452246 -4.741951 -3.522885 -1.605532
value.35 value.36 value.37 value.38 value.39 value.40
1 -9.346954 -10.716282 -10.276734 -9.432706 -9.167833 -8.100433
2 -11.372970 -10.076708 -11.977748 -10.122959 -11.777400 -8.711346
3 -9.356433 -11.137325 -12.585742 -11.480466 -11.620868 -10.166828
4 -7.577705 -11.621401 -11.661146 -12.203332 -12.291080 -10.019409
5 -9.063214 -11.122525 -13.112678 -11.821600 -12.241514 -13.113000
6 -2.794482 -6.652242 -6.815498 -7.989619 -8.309580 -5.957148
value.41 value.42 value.43 value.44 value.45 value.46
1 -7.966888 -9.372070 -6.766884 -3.741432 -7.114272 -12.474926
2 -11.186584 -10.327722 -8.758178 -6.737978 -9.396002 -11.648142
3 -12.339812 -14.248570 -11.941942 -8.053010 -12.301272 -16.652444
4 -11.122702 -13.880626 -9.713423 -9.455841 -10.593926 -14.447150
5 -15.243192 -16.547436 -15.537534 -10.530953 -13.315684 -15.776982
6 -7.283215 -9.160451 -5.985533 -5.895020 -5.108330 -8.321269
value.47 value.48 value.49 value.50 value.51 value.52
1 -13.817684 -15.711532 -10.142309 -11.74451 -13.15383 -14.872548
2 -15.954562 -14.828780 -12.308018 -12.01656 -15.53538 -16.730518
3 -17.937564 -16.979322 -14.915682 -15.60719 -13.41077 -17.299080
4 -13.871522 -13.329192 -11.319212 -10.83332 -11.63636 -14.493164
5 -16.688462 -16.705808 -15.466620 -15.53270 -10.16532 -14.567330
6 -7.425714 -6.284681 -5.137081 -4.42446 -3.21544 -6.506553
value.53 value.54 value.55 value.56 value.57 value.58
1 -15.021524 -12.477028 -13.895214 -13.485986 -11.336758 -12.301046
2 -16.682534 -13.605562 -14.337934 -13.909754 -14.207624 -13.664496
3 -14.318568 -14.928766 -15.001966 -16.128166 -13.705782 -14.290724
4 -13.128240 -10.821440 -10.470508 -10.977070 -10.540644 -10.147554
5 -12.714844 -11.656268 -11.071652 -12.562792 -12.497106 -12.868318
6 -5.173615 -2.108494 -1.684439 -3.973362 -4.315637 -3.556963
value.59 value.60 value.61 value.62 value.63 value.64
1 -10.211424 -9.3199246 -11.58699 -13.605860 -12.71090 -11.767158
2 -12.052495 -10.7351656 -13.94126 -14.451856 -14.90064 -14.052704
3 -12.964292 -10.8632540 -14.12970 -16.641168 -14.10082 -13.836214
4 -8.625842 -5.4754962 -10.08696 -12.874730 -11.25396 -10.827104
5 -12.756150 -9.6768420 -12.00462 -15.184882 -13.92649 -15.654486
6 -2.476967 0.4899707 -3.79528 -6.289172 -4.93821 -5.473591
value.65 value.66 value.67 value.68 value.69 value.70
1 -11.035398 -9.547123 -9.871070 -9.555892 -9.463809 -12.13518
2 -14.946750 -13.757724 -9.822580 -11.334115 -12.780026 -13.45923
3 -13.643042 -10.829646 -13.272332 -14.565634 -13.189710 -15.33080
4 -10.696224 -8.798463 -9.512163 -9.744509 -10.924178 -12.03329
5 -13.338116 -10.976230 -13.592098 -16.866414 -15.264850 -18.43836
6 -5.398287 -3.720513 -4.851563 -6.060661 -7.947564 -8.67331
value.71 value.72 value.73 value.74 value.75 value.76 value.77
1 -10.243124 -13.23524 -16.93180 -20.69199 -24.94481 -29.07222 -30.68195
2 -15.025588 -15.60346 -21.30873 -24.85220 -29.59182 -34.58629 -38.08718
3 -12.891878 -16.81403 -15.88686 -19.98093 -20.42767 -21.51940 -22.91693
4 -12.111522 -14.06842 -15.66449 -18.79317 -18.55060 -21.59982 -22.16122
5 -16.446070 -18.94528 -18.59679 -21.59493 -20.69777 -21.91110 -21.16380
6 -9.326288 -10.00660 -11.94689 -13.44402 -11.61157 -14.90788 -13.64810
value.78 value.79 value.80 value.81 value.82 value.83 value.84
1 -33.00923 -34.61194 -36.29038 -35.33729 -35.62123 -37.75376 -40.56393
2 -38.76102 -39.88267 -43.43890 -42.10508 -44.05012 -46.50652 -47.89790
3 -23.67472 -24.32587 -22.90633 -19.73706 -18.48813 -19.25376 -20.49425
4 -21.12877 -22.23903 -21.69878 -19.70055 -19.31095 -20.35570 -20.82947
5 -22.50361 -23.45121 -21.78829 -19.40065 -18.06839 -18.02228 -18.91203
6 -12.63916 -14.20617 -14.02608 -13.91150 -11.91515 -11.94335 -13.67263
value.85 value.86
1 -44.67135 -34.21896
2 -51.00604 -38.39897
3 -22.86217 -17.73022
4 -25.31616 -19.93672
5 -19.65202 -15.05815
6 -15.87505 -12.32591
down2 <- downsample(ERPdata,2:427,
window = 50)
head(down2) # for example : 426/50=8...26 so we have 9 column of signal data.
Channel Experiment Condition Subject AveRT IQ value.1
1 Fp1 Exp1 nonword subj1 0.01340599 65 -0.007669898
2 Fp2 Exp1 nonword subj1 0.01340599 65 0.042764225
3 F3 Exp1 nonword subj1 0.01340599 65 -0.073859081
4 F4 Exp1 nonword subj1 0.01340599 65 -0.050194450
5 C3 Exp1 nonword subj1 0.01340599 65 -0.098474598
6 C4 Exp1 nonword subj1 0.01340599 65 -0.046727787
value.2 value.3 value.4 value.5 value.6 value.7
1 -2.03050522 0.3264233 -8.797291 -9.885251 -12.60753 -11.127938
2 -1.80858047 -1.0330922 -9.926503 -11.316253 -14.14615 -13.344688
3 -0.10073455 3.5369324 -9.079339 -14.097681 -14.29114 -13.953907
4 0.06836108 2.1564329 -9.103985 -11.856691 -10.63163 -10.675158
5 -0.83509743 1.2155598 -9.337677 -15.134537 -12.05366 -14.524654
6 -0.61960351 2.1320395 -5.084118 -6.502575 -3.25215 -5.714815
value.8 value.9
1 -24.97127 -38.61372
2 -30.11379 -46.00874
3 -20.13446 -20.07335
4 -18.80158 -21.05772
5 -20.70989 -18.66673
6 -12.57628 -13.41978