CBF: realignment parameters

[dalejn]

Use CBF time series to derive the global signal and the mean signals in wm and csf.
For motion parameters, extract the parameters of the even volumes (control volumes) after doing motion correction for the whole ASL time series. Maybe using the mean of the odd and even volumes is a better choice

[dalejn]

setwd("/Users/student/Desktop/dale/realignment")

# starting with each subject's 80x6 realignment.1D file
filenames <- list.files(pattern="realignment.1D")

# grab subject IDs and dates
names <- substr(filenames, 1, 33)

for(i in names){
  # read in the realignment files with 40 tag-control CBF pairs
  filepath <- file.path(paste(i,".1D",sep=""))
  assign(i, read.table(filepath, sep = "", header=FALSE, skip=0))

  # grab only odd rows, i.e. only the 40 tag images
  odd <- get(i)
  odd <- odd[seq(1, nrow(odd), 2), ]
  
  # grab only even rows, i.e. only the 40 control images
  even <- get(i)
  even <- even[seq(2, nrow(even), 2), ]
  
  # average to generate 40 averaged tag-control realignment parameters
  mean <- (odd + even)/2
  
  # write even/control image realignment parameters in new directory
  write.table(
    even, sep = "  ",
    file = paste("controlCBFonly/control",i,'1D',sep='.'),
    col.names = FALSE,
    row.names = FALSE)
 
  # write averaged tag-control realignment parameters in new directory
  write.table(
    mean, sep = "  ",
    file = paste("meanCBF/mean",i,'1D',sep='.'),
    col.names = FALSE,
    row.names = FALSE)
}