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MRI
DMCC55B

OpenNeuro Accession Number: ds003465Files: 3368Size: 456.23GB

BIDS Validation

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DMCC55B
DMCC55B
  •   CHANGES
  •   dataset_description.json
  •   participants.tsv
  •   README
  • code
  • derivatives
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README

Introduction ------------ The DMCC55B dataset is a subset of the task fMRI runs collected in the ongoing Dual Mechanisms of Cognitive Control project (DMCC). DMCC55B is described in detail in "The Dual Mechanisms of Cognitive Control dataset: A theoretically-guided within-subject task fMRI battery" (https://doi.org/10.1101/2021.05.28.446178) by Joset A. Etzel, Rachel E. Brough, Michael C. Freund, Alexander Kizhner, Yanli Lin, Matthew F. Singh, Rongxiang Tang, Allison Tay, Anxu Wang, and Todd S. Braver. Accompanying analysis scripts and details are at https://osf.io/vqe92/.

Further information about the DMCC project as a whole is at https://www.biorxiv.org/content/10.1101/2020.09.18.304402v1, http://sites.wustl.edu/dualmechanisms/, and https://osf.io/6jd9e/, with additional processing and analysis code at https://github.com/ccplabwustl/dualmechanisms. Please contact Jo Etzel (jetzel@wustl.edu) or Todd Braver (tbraver@wustl.edu) with questions and comments, including about access to additional data.

Acquisition and Analysis Notes ------------------------------ This subset has data for 55 of the DMCC participants, all unrelated. 31 of these people were also participants in the Young Adult HCP project (https://www.humanconnectome.org/study/hcp-young-adult); the subject key that maps the subject IDs used here to the HCP IDs is available in the HCP ConnectomeDB, titled "DMCC (Dual Mechanisms of Cognitive Control) subject key".

The full DMCC protocol contains three scanning sessions (baseline, proactive, reactive), with task details varying somewhat between the sessions. This dataset (DMCC55B) contains the first (baseline) session only ("bas" in the ses- part of the BIDS filenames; B in DMCC55B for "baseline"), so only the baseline versions of each task are briefly described here. Some participants are invited back for additional scanning waves, but all DMCC55B data is from the first wave only.

All scans were collected on a 3T Siemens Prisma with a 32-channel head coil, without in-plane acceleration (iPat = none). CMRR multiband sequences were used, multiband factor 4, 2.4 mm isotropic voxels, 1.2 s TR. The physio recordings were made with Siemens equipment (finger plethysmograph and respiration belt); the recordings were extracted using https://github.com/CMRR-C2P/MB/blob/master/readCMRRPhysio.m then converted to plain text and reformatted for BIDS; no filtering or other processing was performed. All available recordings are included here (several are missing due to equipment or software errors), regardless of quality or number of channels; they should be examined carefully (including onset and trigger times), as the signal quality varies substantially between participants and runs.

Functional runs were collected with both A to P and P to A encoding directions ("AP" and "PA", respectively, included in the acq name fields); run 1 is the first run of each task each session and is AP; the second (run 2) is always PA. The two runs of each task were performed together (i.e., Stroop run 1 is always followed by Stroop run 2), but the order of the four tasks was randomly assigned to each person (counter-balanced; i.e., one participant might complete Stroop first, then Cuedts, then Axcpt, and finally Sternberg; another participant might complete Sternberg first).

Each task scanning run followed a mixed, block/event-related structure (e.g., Petersen & Dubis, 2011 Neuroimage), in which each of three task blocks was preceded and followed by a 30-second fixation block. Each task block lasted approximately 180 seconds, with the task trials within each separated by varying inter-trial intervals to facilitate event-related estimation. The standard DMCC GLMs model both the event and block (sustained) effects. Briefly, event-related analyses were carried out with an FIR-type estimation approach using AFNI software (TENTzero function), estimating "knot" (beta coefficients) for every TR. The number of estimated knots varied across the different tasks, following each task's trial duration (plus 14 s). It is of course not necessary to model both the blocks and events (e.g., modeling the events only with a canonical HRF may work well, particularly for short events such as Stroop and button presses).

We defined a particular condition and part ("target period") of each task as requiring "high" and "low" cognitive control demands, as described below. Trial types, response times, and response accuracies are listed in the events.tsv file for each run. All tasks were programmed in Eprime; the full Eprime output contains additional information (e.g., trial stimulus), and is available in the derivatives.

Task Description: AX-CPT (Axcpt) -------------------------------- The baseline version of the DMCC AX-CPT task (http://sites.wustl.edu/dualmechanisms/axcpt-task) uses letter stimuli (press button 2 only if the current letter is X and the previous letter was A, press button 1 in all other cases and stimuli), with numbers as a no-go condition (i.e., withhold a button press to these stimuli). We consider "BX" trials (first letter not A, but second X) as requiring "high" cognitive control and "BY" trials (neither first nor second letter indicate a target response) as "low". The target period for high > low is 8 TRs (9.6 s) after trial onset.

Task Description: Cued Task-Switching (Cuedts) ---------------------------------------------- The DMCC Cued task-switching task (http://sites.wustl.edu/dualmechanisms/task-switching) included trial pre-cues that indicated to either "Attend Number" or "Attend Letter" as the task for the upcoming target. Target stimuli were composed of a letter-digit pair presented side-by-side. If the cue was "Attend Number", the task was to make an odd/even discrimination (press button 1 if even, button 2 if odd). If the cue was "Attend Letter" the task was to make a vowel/consonant discrimination (press button 1 if vowel, button 2 if consonant). All baseline trials were performed without reward or punishment incentives. Incongruent trials (those in which the stimulus combination requires different responses, depending on whether it is Letter or Number task; e.g., A 1 or B 2) are considered "high"; congruent trials (the stimulus combination would lead to the same response irrespective of the task; e.g., A 2 or B 1) are considered "low". The target period for high > low is 8 TRs (9.6 s) after trial onset.

Task Description: Sternberg (Stern) ----------------------------------- The DMCC (http://sites.wustl.edu/dualmechanisms/sternberg-task) uses the "recent probes" variant of the Sternberg task (Jonides & Nee 2006, PMID: 16337090, DOI: 10.1016/j.neuroscience.2005.06.042). On each trial, a memory set consisting of a word list (ranging from 5 to 8 items) is presented, followed by a short delay period (retention interval), and then a single probe item, which requires a target (probe was in the memory set) or nontarget response (probe was not in the memory set). For the high - low cognitive control contrast, only trials with 5 words are used, with "RN" trials ("recent negative": the probe item was not in the memory set of the current trial, but was in the memory set of the previous trial) as "high" and "NN" trials ("novel negative": the probe was not present in the current or any previous trial memory sets) as "low". The target period for high > low is 12 TRs (14.4 s) after trial onset.

Task Description: Stroop (Stroop) --------------------------------- The DMCC Stroop task (http://sites.wustl.edu/dualmechanisms/stroop), is the color/word Stroop, with responses (color names) spoken aloud in the scanner. Incongruent trials (word and color do not match) are considered "high", congruent trials (word and color match) are considered "low". The target period for high > low is 4 TRs (4.8 s) after event onset.

Derivatives Description: questionnaires --------------------------------------- The derivatives/questionnaires/ directory contains scores for the DMCC55B participants on 28 different psychological questionnaires. These files follow the format and naming used by the NIMH Data Archive (https://nda.nih.gov/), except that the DMCC release subject IDs are used (not GUIDs or regular DMCC IDs), only DMCC55B participants are included (not all collected participants or sessions), and some demographic details are omitted for privacy. All DMCC questionnaire data is being submitted to the NDA, and will be made public through that site in the future.

The Data Expected tab of the DMCC's NDA page (https://nda.nih.gov/edit_collection.html?id=2970) lists the full names of each questionnaire, with links to the corresponding data dictionary for each. For example, the Positive and Negative Affect Schedule results are in the panas01_DMCC55B.csv file, and the fields and scoring described at https://nda.nih.gov/data_structure.html?short_name=panas01.

Comments

Please sign in to contribute to the discussion.
By jetzel@wustl.edu - over 1 year ago
first release.
By jetzel@wustl.edu - over 1 year ago
first *full* release.

Authors

Todd S. Braver, Alexander Kizhner, Rongxiang Tang, Michael C. Freund, Joset A. Etzel

Available Modalities

MRI

Versions

1.0.4
Created: 2021-06-30
Versions

Tasks

Axcpt, Cuedts, Stern, Stroop

Uploaded by

Ben Wang on 2021-01-08 - over 1 year ago

Last Updated

2021-06-30 - about 1 year ago

Sessions

3

Participants

55

Dataset DOI

doi:10.18112/openneuro.ds003465.v1.0.4

License

CC0

How To Cite

Copy
Todd S. Braver and Alexander Kizhner and Rongxiang Tang and Michael C. Freund and Joset A. Etzel (2021). DMCC55B. OpenNeuro. [Dataset] doi: 10.18112/openneuro.ds003465.v1.0.4
More citation info

Acknowledgements

We thank Rachel Brough, Maria Gehred, Erin Gourley, Leah Newcomer, Kevin Oksanen, Allison Tay, and Anxu Wang for assistance with data collection and processing. We thank Nicholas Bloom, Mitch Jeffers, and Carolina Ramirez for assistance with pipeline programming and dataset managment.

How to Acknowledge

https://www.biorxiv.org/content/10.1101/2020.09.18.304402v1

Funding

This research was supported by NIH R37MH066078 and NIH R21AG058206 to Todd Braver.Image acquisition is partially supported by Mallinckrodt Institute of Radiology, Washington University in St. Louis.

References and Links

https://sites.wustl.edu/ccplab/https://sites.wustl.edu/dualmechanismshttps://github.com/ccplabwustl/dualmechanismshttps://nda.nih.gov/edit_collection.html?id=2970https://osf.io/6jd9e/

Ethics Approvals

All participants provided written informed consent in accordance with the Institutional Review Board at Washington University, St. Louis (USA).
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