Trial level behavioral performance during task-based fMRI

Domain overview

To facilitate use of trial-level behavioral performance data from the different task-based fMRI a set of pre-processing steps that can be applied to the stimulus event timing and behavioral performance files was developed for ABCD.The code used to implement these pre-processing steps has been made publicly available on the ABCD Study’s GitHub page. The input E-prime files are available in the sourcedata BIDS structure (see MRI Raw Data File Sharing Data Documentation). The E-prime task files used for ABCD are available at https://abcdstudy.org/scientists/abcd-fmri-tasks-and-tools. The tasks and the summary behavioral performance measures extracted from the E-prime files and included in the tabulated data are described in the Behavioral Performance Data Documentation. The processing and analysis of the associated fMRI data is described in Task-Based fMRI Data Documentation. The behavioral performance review is part of the ABCD Study QC procedures and recommended imaging inclusion criteria (see MRI Quality Control Data Documentation).

Responsible Use Warning: Trial-Level Data

Using open-access datasets like ABCD requires responsible conceptualization and use of the data, including being mindful of variations in experience that impact performance. Below are specific considerations:

Cognitive task performance can be influenced by various environmental and personal factors, including participant health, attention, nutrition, fatigue, or other transient conditions.Cognitive task performance has been shown to correlate strongly with a variety of socio-economic factors. Attention and other performance factors can also be confounded by transient factors influenced by low SES, such as fatigue, poor nutrition, or environmental stressors.
Although the ABCD protocol captures several environmental and personal variables that may influence performance (e.g., potential covariates), it is unlikely that all relevant factors have been measured.Although the ABCD protocol captures several SES-related variables (e.g. for use as potential covariates), it is unlikely that the ABCD dataset captures all of them.

Trial-Level Behavioral Data

Monetary Incentive Delay (MID) Task

The following table provides the column names that are contained within the MID pre-processed behavioral data files, as well as a brief description of the variable and what type of data it contains.

Column name	Description
`task`	Behavioral task completed
`subject`	Subject ID ashow it’s defined in lab/project
`eventname`	The event name for which the data was collected
`site`	Data collection site ID
`date`	Date of data collection (month/day/year)
`time`	Time that data was collected (hours/minutes/seconds)
`mid_run`	Which run the task data corresponds to `mid_trialnum`
`mid_anticipationtype`	The type of anticipation for that trial
`mid_anticipationonset`	The time that the anticipation phase started
`mid_anticipationduration`	The length of time that the anticipation phase lasted
`mid_feedbacktype`	The type of feedback received based on the subject’s performance `mid_feedbackonset`
`mid_feedbackduration`	The length of time that the feedback phase lasted
`mid_acc`	Accuracy of the subject’s performance for that trial
`mid_resp`	Whether or not the subject provided a response for that `trialmid_rt`
`mid_rttime`	The timepoint in the task when the participant responded
`mid_trialmoney`	The money resulting from the subject’s performance on that trial

The following information pertains to the variables:

mid_anticipationonset
mid_anticipationduration
mid_feedbackonset
mid_feedbackduration
mid_rt
mid_rttime

All times have already been corrected and represent the actual start time of the task.

In other words, as this task was carried out as an fMRI task, the “PrepTime” times for each of the runs has already been subtracted out, producing the times contained in the pre-processed behavioral data files. These times are consistent with those produced by the abcd_extract_eprime scripts, which are publicly-available in the ABCD study’s GitHub page.
If you are analyzing these behavioral data with the MID fMRI data and you do not plan on removing any initial frames prior to analysis, you must adjust the mid_anticipationonset, mid_feedbackonset, and mid_rttime variables in the following way:
- Siemens/Philips Scanners: Add 6400 ms
- GE DV25: Add 4000 ms
- GE DV26: Add 12,800 ms

All times are presented in milliseconds

Stop Signal Task (SST)

The following table provides the column names that are contained within the SST pre-processed behavioral data files, as well as a brief description of the variable and what type of data it contains.

Column name	Description
`task`	Behavioral task completed
`src_subject_id`	Subject IDeventname
`site`	Data collection site ID
`date`	Date at which the data were collected
`time`	Local time at which the data were collected
`sst_run`	Whether the trial occurred on the first or second run of the task
`sst_trialnum`	E-Prime-labeled trial number within each run (note: these numbers are generated by E-Prime and do not necessarily correspond with the absolute trial number; e.g., the first trial in a run may be labeled as number 3)
`sst_stimonset`	Variable constructed by the trial-level task force (see Appendix B) that indicates the global onset time of each trial
`sst_beginfix_starttime`	Global “start time” (when an E-Prime slide is scheduled to be presented) for the fixation slide that began each run; this time should correspond to the beginning of fMRI data collection for the run
`sst_beginfix_onsettime`	Global “onset time” (when an E-Prime slide actually begins to be presented) for the fixation slide that began each run
`sst_stim`	Variable constructed by the trial-level task force (see Appendix B) that indicates the choice stimulus presented for the trial (right- or left-facing arrow)
`sst_stimfile`	Name of the .bmp file for the presented choice stimulus, which was used to compute the “sst_stim” variable
`sst_primaryresp`	Variable constructed by the trial-level task force (see Appendix B) that indicates the first response the participant made on each trial (right- or left-facing arrow)
`sst_primaryrt`	Variable constructed by the trial-level task force (see Appendix B) that indicates the response time for the first response the participant made on each trial
`sst_go_onsettime`	Global onset time for “go” slidessst_go_resp
`sst_go_rt`	Response times locked to the beginning of “go” slides
`sst_go_rttime`	Global timing of responses to “go” slides
`sst_ssd_onsettime`	Global onset time for “ssd” `slidessst_ssd_resp`
`sst_ssd_rt`	Response times locked to the beginning of “ssd” slides
`sst_ssd_rttime`	Global timing of responses to “ssd” slides
`sst_ssd_dur`	Duration of the stop-signal delay (SSD) for STOP trials
`sst_stopsignal_onsettime`	Global onset time for “stopsignal” `slidessst_stopsignal_resp`
`sst_stopsignal_rt`	Response times locked to the beginning of “stopsignal” slides
`sst_stopsignal_rttime`	Global timing of responses to “stopsignal” slides
`sst_fix_onsettime`	Global onset time for “fix” `slidessst_fix_resp`
`sst_fix_rt`	Response times locked to the beginning of “fix” slides (note: the global timing of responses to “fix” slides was not recorded by the task)
`sst_leftarrow`	Variable that maps participants’ button press responses to the “left arrow” response
`sst_rightarrow`	Variable that maps participants’ button press responses to the “right arrow” response
`sst_expcon`	Whether the trial was in the GO or STOP condition
`sst_choiceacc`	Variable constructed by the trial-level task force (see Appendix B) for whether participants’ response to the choice task (left- vs. right-facing arrow) was accurate (1) or inaccurate (0)
`sst_inhibitacc`	Variable constructed by the trial-level task force (see Appendix B) indicating, for STOP trials, whether participants successfully inhibited (1) or failed to inhibit (0)

Concerns regarding ABCD SST task

Bissett et al. (2020) raised several concerns about the design and data recording procedures of the ABCD SST. Trial-level data users are encouraged to read this manuscript, as well as our response Garavan et al. (2020)), and the outline (see Appendix A below) of how each identified concern affects the trial-level data in this release. Two of the concerns raised have particularly important implications for the inclusion of individual subjects:

The fact that a subset of individuals display response time (RT) data that cannot be explained by the standard SST Independent Race Model (mean failed STOP RT > mean GO RT)
A data recording glitch, which occurs when a participant makes a fast (<50ms) response on a STOP trial with a 50ms stop-signal delay and which causes all subsequent STOP trials to be incorrectly recorded as failures to stop with the same RT, altering the tracking algorithm. Therefore, in addition to the standard ABCD performance exclusion criteria outlined above, users interested in applying race models of inhibition to the trial-level data are encouraged to exclude participants from analysis who have the following flags:

Participants with mean STOP RT > mean GO RT, indicating clear violations of Independent Race Model assumptions (tfmri_sst_beh_violatorflag)
Participants who display evidence of the recording glitch, as outlined in Appendix A (tfmri_sst_beh_glitchflag)

However, if users are primarily interested in analyzing features of performance on the GO choice task (e.g., GO RT variability), such exclusions may not be necessary.

Task trials involved the presentation of stimuli on several different slides in E-Prime: GO trials involved the presentation of a “go” slide with the choice stimulus for 1000ms, or until a participant responded, followed by a “fix” slide which presented a fixation cross for the remaining duration of the 1000ms trial and jittered intertrial interval; STOP trials involved the presentation of a “ssd” slide with the choice stimulus for the duration of the variable stop-signal delay on that trial, followed by a “stopsignal” slide that presented the stop signal (upward facing arrow) for 300ms, and finally by a “fix” slide which presented a fixation cross for the remaining duration of the 1000ms trial plus the duration of the jittered intertrial interval. The recording of RTs and responses was linked to the individual slide, rather than being locked to the onset of the trial.

To facilitate use of the trial-level data, the ABCD trial-level behavioral data (TLBD) task force applied minimal pre-processing steps (outlined in Appendix B) to determine the first response a participant made on each trial (sst_primaryresp variable), which in standard research contexts is treated as the participant’s main response, and accurately estimates the RT for this response (sst_primaryresp variable). However, all relevant response, RT and onset timing variables from the individual slides have been retained, as described below, which will allow other researchers to compute response and RT variables using their own methods, if desired.

When possible, participants who were unable to complete the task in the scanner, completed the task behaviorally outside the scanner on a laptop computer. Whether a participant performed the SST in the scanner or on a laptop is indicated by the following variable in the main tabulated data: mr_y_adm__nts__tfmri__sst_indicator. For more details, see the MRI Scanning Checklist and Notes instrument.

Appendix A

Details on the specific issues raised in the “Cautionary Note” manuscript by Bisset et al, and how they affect the use of these trial-level data.

As noted above, a manuscript entitled “A cautionary note on stop-signal data from the Adolescent Brain Cognitive Development [ABCD] study” (Bissett et al. (2020)) raised several concerns about the ABCD SST’s design and data recording procedures. Users of the trial-level data are encouraged to read this manuscript and any associated commentaries prior to analyzing these data. For clarity, this section provides a brief summary of each concern and the specific implications that these concerns present for analysis of the trial-level data included in this release.

1. Different “go” choice stimulus presentation durations across trials.

Summary:

On GO trials, the choice stimulus (a right- or left-facing arrow) is presented on screen until the participant responds or until a 1000ms window passes, whichever occurs first. However, on STOP trials, the visual stop signal (an upward facing arrow) replaces the “go” choice stimulus following the stop-signal delay. This causes the presentation time of the choice stimulus to be substantially shorter, on average, for STOP trials than for GO trials, which likely makes the choice task more difficult in the STOP condition. The increase in difficulty likely yields slower and less accurate choice responses in this condition (particularly for STOP trials with relative short stop-signal delays). The Independent Race Model, which is the dominant framework for estimating the main index of inhibition on the SST (stop-signal reaction time; SSRT) assumes context independence, which means that the “go” choice process and its average finishing time are not affected by the presentation of the stop signal (i.e., that the “go” process is identical between GO and STOP trials). As context independence is essential for accurate estimation of SSRT in the race model, and as the choice stimulus presentation durations of the ABCD SST likely cause violations of the context independence assumption, especially at short stop-signal delays, SSRT estimates drawn from applications of the race model to these data could be inaccurate.