MRI
A longitudinal neuroimaging dataset on language processing in children ages 5, 7, and 9 years old

OpenNeuro Accession Number: ds003604Files: 16639Size: 714.28GB

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A longitudinal neuroimaging dataset on language processing in children ages 5, 7, and 9 years old
A longitudinal neuroimaging dataset on language processing in children ages 5, 7, and 9 years old
  •   .bidsignore
  •   CHANGES
  •   dataset_description.json
  •   participants.json
  •   participants.tsv
  •   README
  •   task-Gram_bold.json
  •   task-Gram_events.json
  •   task-Phon_bold.json
  •   task-Phon_events.json
  •   task-Plaus_bold.json
  •   task-Plaus_events.json
  •   task-Sem_bold.json
  •   task-Sem_events.json
  • code
  • derivatives
  • phenotype
  • stimuli
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README

Known Issues

  • BIDS validator warns that some stimuli files are not included in events.tsv. This is due to the extra 2 circle figures, which were used to keep participants' attention and remind them to respond timely.
  • BIDS validator warns that inconsistent subjects and missing sessions because not all subjects could attend all tasks and all sessions.
  • BIDS validator warns that we missed magnitude files. This is due to the fact that we did not collect magnitude images during the fieldmap scan. We only collected phasediff images.
  • BIDS validator warns that not all subjects/sessions/runs have the same scanning parameters. This is mainly due to the fact that we added 6 volumes to the end of the functional runs after a small subset of initial participants. There are a few t1 weighted images with varied resolution, but they were all within +-0.05mm. A few diffusion weighted images have 69 or 65 volumes in contrast to standard 70 volumes. These differences are likely due to occasional scanner updates at the scanning center.
  • We manually created json files for 29 functional runs and 4 anatomical runs because we converted them using spm8 but then the original DICOMs were lost. ./sub-5085/ses-5/anat/sub-5085_ses-5_acq-D1S1_T1w.json ./sub-5085/ses-5/anat/sub-5085_ses-5_acq-D1S3_T1w.json ./sub-5085/ses-5/anat/sub-5085_ses-5_acq-D1S2_T1w.json ./sub-5347/ses-5/anat/sub-5347_ses-5_acq-D1S1_T1w.json ./sub-5085/ses-5/func/sub-5085_ses-5_task-Phon_acq-D1S4_run-01_bold.json ./sub-5085/ses-5/func/sub-5085_ses-5_task-Phon_acq-D1S5_run-02_bold.json ./sub-5032/ses-7/func/sub-5032_ses-7_task-Phon_acq-D2S5_run-01_bold.json ./sub-5365/ses-9/func/sub-5365_ses-9_task-Phon_acq-D1S4_run-01_bold.json ./sub-5365/ses-9/func/sub-5365_ses-9_task-Phon_acq-D1S3_run-02_bold.json ./sub-5211/ses-9/func/sub-5211_ses-9_task-Phon_acq-D1S5_run-02_bold.json ./sub-5211/ses-9/func/sub-5211_ses-9_task-Phon_acq-D1S6_run-01_bold.json ./sub-5085/ses-5/func/sub-5085_ses-5_task-Sem_acq-D3S4_run-02_bold.json ./sub-5085/ses-5/func/sub-5085_ses-5_task-Sem_acq-D3S3_run-01_bold.json ./sub-5061/ses-5/func/sub-5061_ses-5_task-Sem_acq-D3S4_run-02_bold.json ./sub-5061/ses-5/func/sub-5061_ses-5_task-Sem_acq-D3S3_run-01_bold.json ./sub-5061/ses-5/func/sub-5061_ses-5_task-Sem_acq-D3S7_run-02_bold.json ./sub-5347/ses-5/func/sub-5347_ses-5_task-Sem_acq-D1S6_run-01_bold.json ./sub-5347/ses-5/func/sub-5347_ses-5_task-Sem_acq-D1S5_run-02_bold.json ./sub-5085/ses-5/func/sub-5085_ses-5_task-Gram_acq-D1S7_run-02_bold.json ./sub-5085/ses-5/func/sub-5085_ses-5_task-Gram_acq-D1S6_run-01_bold.json ./sub-5085/ses-5/func/sub-5085_ses-5_task-Gram_acq-D3S5_run-02_bold.json ./sub-5032/ses-7/func/sub-5032_ses-7_task-Gram_acq-D2S4_run-02_bold.json ./sub-5032/ses-7/func/sub-5032_ses-7_task-Gram_acq-D2S3_run-01_bold.json ./sub-5211/ses-9/func/sub-5211_ses-9_task-Gram_acq-D1S3_run-02_bold.json ./sub-5211/ses-9/func/sub-5211_ses-9_task-Gram_acq-D1S4_run-01_bold.json ./sub-5365/ses-9/func/sub-5365_ses-9_task-Gram_acq-D1S6_run-01_bold.json ./sub-5365/ses-9/func/sub-5365_ses-9_task-Gram_acq-D1S5_run-02_bold.json ./sub-5085/ses-5/func/sub-5085_ses-5_task-Plaus_acq-D2S3_run-01_bold.json ./sub-5085/ses-5/func/sub-5085_ses-5_task-Plaus_acq-D2S4_run-02_bold.json ./sub-5061/ses-5/func/sub-5061_ses-5_task-Plaus_acq-D3S5_run-01_bold.json ./sub-5061/ses-5/func/sub-5061_ses-5_task-Plaus_acq-D3S6_run-02_bold.json ./sub-5347/ses-5/func/sub-5347_ses-5_task-Plaus_acq-D1S4_run-01_bold.json ./sub-5347/ses-5/func/sub-5347_ses-5_task-Plaus_acq-D1S3_run-02_bold.json

  • The calculation of reaction time (rt) and accuracy (acc) for each condition within each run for each participant is documented in ./derivatives/func_mv_acc_rt/Acc_RT_Calculation.doc

Comments

Please sign in to contribute to the discussion.
By braindevelopmentlaboratory@gmail.com - about 1 year ago
complete version
By smeisler@g.harvard.edu - 10 months ago
Hi,

May I ask why some subjects have multiple DWI scans? Based on looking at the gradient tables and QA metrics, it doesn't seem like it's necessarily the case that one acquisition is incomplete or poor quality, which are usually reasons to repeat a scan.

Thanks,
Steven
By braindevelopmentlaboratory@gmail.com - 9 months ago
Hi, Steven,

Thank you for your question. It was because we sometimes forgot that we had already collected DTI during the previous session and DTI data were usually collected when we had extra scanning time. Hope it helps.

Best,
Jin
By rbelisle4@g.ucla.edu - 4 months ago
Hi,

For handedness, does the number on participants.tsv reflect the number of actions out of the total 5 actions that were performed with the right hand?

Thank you,
Becky
By wangjin@utexas.edu - 4 months ago
Yes. That's correct Becky.

Best,
Jin