R notebook for analysis of frontal eye field coordinates in the sacc-tDCS dataset.
# Load some libraries
library(here) # file pathshere() starts at /Volumes/research$/reteig/sacc-tDCSlibrary(tidyverse) # importing, transforming, and visualizing data framesLoading tidyverse: ggplot2
Loading tidyverse: tibble
Loading tidyverse: tidyr
Loading tidyverse: readr
Loading tidyverse: purrr
Loading tidyverse: dplyr
Conflicts with tidy packages ---------------------------------------------------------------------------------
filter(): dplyr, stats
lag(): dplyr, statslibrary(knitr) # R markdown output (html, pdf, etc.)
# set default output and figure options
knitr::opts_chunk$set(message = FALSE, warning = FALSE, fig.width = 7, fig.asp = 0.618, out.width = "75%", fig.align = "center")
sessionInfo()R version 3.4.0 (2017-04-21)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: OS X El Capitan 10.11.6
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib
locale:
[1] C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] knitr_1.15.1 dplyr_0.5.0 purrr_0.2.2 readr_1.1.0 tidyr_0.6.1 tibble_1.3.0
[7] ggplot2_2.2.1 tidyverse_1.1.1 here_0.1
loaded via a namespace (and not attached):
[1] Rcpp_0.12.10 cellranger_1.1.0 compiler_3.4.0 plyr_1.8.4 forcats_0.2.0 tools_3.4.0
[7] jsonlite_1.4 lubridate_1.6.0 gtable_0.2.0 nlme_3.1-131 lattice_0.20-35 psych_1.7.3.21
[13] DBI_0.6-1 parallel_3.4.0 haven_1.0.0 xml2_1.1.1 stringr_1.2.0 httr_1.2.1
[19] hms_0.3 rprojroot_1.2 grid_3.4.0 R6_2.2.0 readxl_1.0.0 foreign_0.8-67
[25] reshape2_1.4.2 modelr_0.1.0 magrittr_1.5 backports_1.0.5 scales_0.4.1 rvest_0.3.2
[31] assertthat_0.2.0 mnormt_1.5-5 colorspace_1.3-2 stringi_1.1.5 lazyeval_0.2.0 munsell_0.4.3
[37] broom_0.4.2 List the subjects that were excluded in the eye data analyses.
subs2exclude <- c("S21","S25","S16","S22","S28")These were determined for each subject’s scan; see neuronav_notes.md for further info.
dataFile <- here("data", "FEF_coords_native.csv")
nativeCoords <- read_csv2(dataFile)
nativeCoords %>%
select(-folder, -scan) %>% # drop columns with folder and scan names
filter(!(subject %in% subs2exclude)) %>% # drop rows with excluded subjects
kable(.)| subject | native.X | native.Y | native.Z |
|---|---|---|---|
| S01 | 96 | 132 | 137 |
| S02 | 89 | 118 | 132 |
| S03 | 153 | 124 | 177 |
| S04 | 96 | 127 | 131 |
| S05 | 93 | 116 | 138 |
| S06 | 101 | 131 | 182 |
| S07 | 92 | 127 | 147 |
| S08 | 101 | 123 | 159 |
| S09 | 99 | 125 | 158 |
| S10 | 94 | 124 | 125 |
| S11 | 147 | 123 | 149 |
| S12 | 97 | 121 | 176 |
| S13 | 144 | 125 | 140 |
| S14 | 87 | 122 | 129 |
| S15 | 118 | 111 | 125 |
| S17 | 161 | 135 | 175 |
| S18 | 153 | 147 | 173 |
| S19 | 146 | 155 | 172 |
| S20 | 78 | 124 | 99 |
| S24 | 160 | 134 | 141 |
| S26 | 156 | 141 | 150 |
| S27 | 148 | 122 | 156 |
| S29 | 90 | 131 | 153 |
| S30 | 95 | 125 | 149 |
| S32 | 147 | 140 | 146 |
| S33 | 159 | 149 | 168 |
mni_coords.sh reads in the native coordinates, converts them to MNI space, and writes out a .csv of the same format as for the native coordinates.
Under # FSL setup, replace FSLDIR with the directory path you installed FSL to.
Arguments:
all as a 3rd argument first (re)runs skull stripping and registration to the MNI template.# FSL Setup
FSLDIR=/usr/local/fsl
PATH=${FSLDIR}/bin:${PATH}
export FSLDIR PATH
. ${FSLDIR}/etc/fslconf/fsl.sh
# Run shell script to compute MNI coordinates
bash src/func/mni_coords.sh data/FEF_coords_native.csv data/FEF_coords_MNI.csv allLoad in the MNI coordinates that were written to a .csv file by the shell script.
dataFile <- here("data", "FEF_coords_MNI.csv")
mniCoords <- read_delim(dataFile, ";")
mniCoords <- filter(mniCoords, !(subject %in% subs2exclude)) # exclude subjects
mniCoords %>%
select(-folder, -scan) %>% # drop columns with folder and scan names
kable(.)| subject | MNI_X | MNI_Y | MNI_Z |
|---|---|---|---|
| S01 | 29.4081 | 1.069700 | 54.8724 |
| S02 | 33.0338 | -2.245090 | 50.4239 |
| S03 | 30.5837 | -1.480360 | 50.5881 |
| S04 | 25.7061 | -3.761730 | 56.3648 |
| S05 | 29.7780 | -5.201110 | 55.8046 |
| S06 | 29.7783 | -1.120820 | 58.2622 |
| S07 | 38.1233 | 2.975730 | 45.9613 |
| S08 | 31.5014 | 0.526375 | 45.6200 |
| S09 | 28.5103 | 3.632940 | 51.2804 |
| S10 | 28.1080 | -1.933630 | 50.7210 |
| S11 | 30.5811 | -3.787490 | 51.9535 |
| S12 | 36.5129 | -0.386049 | 46.7630 |
| S13 | 26.2263 | -1.069220 | 54.7079 |
| S14 | 37.5005 | -1.588150 | 52.5889 |
| S15 | 31.8188 | -8.357000 | 58.9671 |
| S17 | 31.0229 | -5.121250 | 54.3116 |
| S18 | 34.9669 | 8.390570 | 49.8188 |
| S19 | 28.0703 | -3.834910 | 52.7607 |
| S20 | 41.2127 | -1.745790 | 47.5514 |
| S24 | 37.3474 | -0.862753 | 43.4371 |
| S26 | 34.3288 | -2.861210 | 49.1761 |
| S27 | 27.6566 | -10.061100 | 50.9743 |
| S29 | 30.3161 | -5.272910 | 55.2661 |
| S30 | 26.8320 | -3.868670 | 54.5619 |
| S32 | 29.0049 | 4.888810 | 49.1404 |
| S33 | 30.3099 | -3.897600 | 50.9083 |
Calculate statistics over subjects:
mniCoords %>%
gather(dimension, coord, MNI_X:MNI_Z) %>%
group_by(dimension) %>%
summarise(average = mean(coord), standard.deviation = sd(coord), minimum = min(coord), maximum = max(coord)) %>%
kable(.)| dimension | average | standard.deviation | minimum | maximum |
|---|---|---|---|---|
| MNI_X | 31.470735 | 4.036810 | 25.7061 | 41.21270 |
| MNI_Y | -1.806643 | 3.931623 | -10.0611 | 8.39057 |
| MNI_Z | 51.645608 | 3.922225 | 43.4371 | 58.96710 |
Write a new `.csv’ file with MNI coordinates, without the coordinates from the excluded subjects.
exclMNI <- here("data", "FEF_coords_MNI_excl.csv")
write_delim(mniCoords, exclMNI, delim = ";")
Sys.setenv(exclMNI = exclMNI) # port variable with csv file name to bashThe coords can be very nicely visualized with Surf Ice by running the plot_coords.m script (requires MATLAB)
Alternatively, fef_rois.sh takes the MNI coordinates and adds spherical masks, centered around each subjects FEF coordinate, to the MNI template.
Under # FSL setup, replace FSLDIR with the directory path you installed FSL to.
Arguments:
MNI_152_1mm template with spherical ROI around each subject’s frontal eye field# FSL Setup
FSLDIR=/usr/local/fsl
PATH=${FSLDIR}/bin:${PATH}
export FSLDIR PATH
. ${FSLDIR}/etc/fslconf/fsl.sh
# Run shell script to make spherical ROIs
bash src/func/fef_rois.sh $exclMNI neuronav/FEF_ROIs_bigspheres.nii.gz 2