Jonathan Power
  • Papers
    • 2020 Respiratory Patterns
    • 2020 fMRI denoising events
    • 2019 Respiratory Measures
    • 2019 PNAS reply to Spreng
    • 2019 Respiratory Motion
    • 2018 Glasser comment
    • 2018 Head molds
    • 2018 PNAS multiecho
    • 2017 TiCS response
    • 2017 PLOS ONE Despiking
    • 2017 NI Global signals
    • 2017 NI The Plot
    • 2015 NI Motion Review
    • 2014 Neuron RSFC Primer
    • 2014 PNAS lesion
    • 2014 HBM task censoring
    • 2014 NI motion #2
    • 2013 Neuron hubs
    • 2013 NI comment
    • 2013 CONEUR
    • 2012 NI motion #1
    • 2011 Neuron bigbrain
    • 2010 Neuron devo review
  • Contact
  • Resources
  • Positions
  

Temporal interpolation alters motion in fMRI scans: magnitudes and consequences for artifact detection
Jonathan Power, Mark Plitt, Prantik Kundu, Peter Bandettini, Alex Martin
PLoS One. 2017 Sep 7; 12(9):e0182939
PubMed link
Figures (.ppt)
Processing scripts (.zip)
WU120: resting state fMRI datasets hosted at OpenfMRI under accession number ds000243

Below are movies associated with the article "Temporal interpolation alters motion in fMRI scans: magnitudes and consequence for artifact detection". All movies are 1080p and will look best at full-screen resolutions. The movies stream from YouTube and are organized as playlists. You can select cohort (ME, WU, or NIH) or subject from the playlist drop down menu at upper left of the movies (the three horizontal bars). Click on links next to the captions to download the movies. Files to download are hosted on Dropbox Pro; if the links don't work our traffic has exceeded its 200GB/day limit and the links will be re-enabled the following day.

Video 1 (.movs - 60MB):
This video shows versions of Figures 1and S1 for each subject of the ME, WU, and NIH cohorts. For single echo datasets, instead of contrasting echo times in the upper right panel, reference volumes from other runs are contrasted with reference volumes within runs. See Video 2 for detailed xyzPRY plots in these cohorts.
​


Video 2 (.movs - 480MB):
​This video shows FD plots at top and the individual xyzPRY traces, making it easier to see where the motions and changes in motion are occurring.



Video 3: (.movs - 20GB total, see subgroup links for smaller 10-subject groupings of ~650MB each)
ME:   1-10  11-20  21-30  31-40  41-50  51-60  61-70  71-80  81-89
WU:  1-10  11-20  21-30  31-40  41-50  51-60  61-70  71-80  81-90  91-100  101-110  111-120
NIH:  1-10  11-20  21-30  31-40  41-50  51-60  61-70  71-80  81-91

These videos show xyzPRY and FD traces at top, then slices from raw data, realigned data, and realigned data with the voxelwise mean and trend terms removed. These slices let you see the actual motion in the images and whether the realigned data exhibit residual misalignment. The surfaces draw their signals from the realigned data with mean and trend terms removed, and are moved by the realignment parameters estimated in the appropriate kind of data (the xyzPRY traces in the top panel). The bottom panel shows the time series of 264 ROIs in realigned data with mean and trend terms removed. Slices and surfaces continuously represent raw, despiked, and time shifted data, whereas the panels at top and bottom usually display raw data but intermittently show despiked and/or time shifted data (this will make sense as soon as you play a movie, watch the data labels). It is convenient to stream the movies, but we find these videos to be most useful when downloaded so you can flip back and forth between frames with arrow keys to compare images in detail. Because YouTube playlists can only contain 200 videos, the top playlist contains ME and WU subjects, and the bottom playlist contains NIH subjects.
​



Video 3 "Best of": (.mov - 170MB)
This video selects a few dozen instances from the ~300 subjects in the videos above where brain motion in the field of view differs across processing (i.e., between raw, despiked, and time shifted data). These examples are fairly obvious; many other instances exist and could have been chosen.
​

If you like these videos, they are not too hard to create. All the pieces you need are in demos on this website. See the movie creation demo, the grayplot creation demo,  the slice creation demo, and the demo for generating Caret/WB surface pictures. You'll want a cluster for more than a few subjects.
​