6.0 data release

Sample

The 6.0 data release includes data from 11,868 participants, representing the full ABCD cohort (N = 11,880) except for 12 participants who withdrew consent to share their data, and 13 events. Data is considered complete through the 4-year follow-up and nearly complete for the 5-year follow-up, with varying numbers of missed visits per event. The 5.5-year and 6-year follow-up events were still ongoing when the data were frozen (cutoff date: January 15, 2025), so these events include only participants who had assented by the cutoff date. No data are included from events after the 6-year follow-up to ensure sufficient event completion.

The following table shows the number of participants per core study event¹:

Session/event ID	Session/event label	n
ses-00S	Screener	11868
ses-00A	Baseline	11868
ses-00M	0.5 Year	11389
ses-01A	1 Year	11219
ses-01M	1.5 Year	11084
ses-02A	2 Year	10973
ses-02M	2.5 Year	10256
ses-03A	3 Year	10450
ses-03M	3.5 Year	9574
ses-04A	4 Year	9739
ses-04M	4.5 Year	7164
ses-05A	5 Year	8885
ses-05M	5.5 Year	6323
ses-06A	6 Year	5056

The ABCD 6.0 Data Release also includes data from associated substudies—Social Development, Endocannabinoids, Hurricane Irma, COVID-19, and MR Spectroscopy. Some of these substudy assessments are done during the same visits as the main study, others have their own, independent event structure.

The following table shows the number of participants with data per substudy event:

Substudy	Session/event ID	Session/event label	n
COVID-19	ses-C01	COVID Wave 1	11187
COVID-19	ses-C02	COVID Wave 2	11208
COVID-19	ses-C03	COVID Wave 3	11153
COVID-19	ses-C04	COVID Wave 4	11107
COVID-19	ses-C05	COVID Wave 5	11051
COVID-19	ses-C06	COVID Wave 6	10842
COVID-19	ses-C07	COVID Wave 7	10854
Social Development	ses-S01	SDev Wave 1	2426
Social Development	ses-S02	SDev Wave 2	2129
Social Development	ses-S03	SDev Wave 3	1942
Social Development	ses-S04	SDev Wave 4	1842
Social Development	ses-S05	SDev Wave 5	1384

Curation & structure

In preparation for the 6.0 data release, the ABCD Study implemented new curation standards to improve the consistency, transparency, and usability of the release dataset. The curation standards and their implementation are described in more detail in the Curation & structure pages of the documentation. A high-level overview of the changes is provided below.

BIDS file structure and identifier columns

The ABCD 6.0 data release includes a variety of data types and file formats, including tabulated data and file-based data. Where possible, the data are organized in accordance with the Brain Imaging Data Structure (BIDS) standard, with some modifications to meet the specific needs of the ABCD Study®. BIDS is a widely adopted standard for organizing and formatting neuroimaging data, facilitating data sharing, processing, and analysis across various platforms and tools. We hope that this standardization will enhance the usability of the data and make it easier for researchers to work with the dataset.

As part of the BIDS standardization, we implemented the following changes to the names and values of the identifier columns used across the ABCD data resource:

Identifier Column Names:
- participant_id (replacing src_subject_id from previous releases)
- session_id (replacing eventname from previous releases)
Identifier Column Values:
- Use BIDS-specific prefixes (sub- for participant and ses- for session/event identifiers).
- participant_id values no longer include the NDAR_INV prefix (e.g., sub-ABCD1234 instead of NDAR_INVABCD1234).
- session_id values are BIDS-compliant (e.g., without underscores) and standardized (see here for more details).

Naming convention

For the 6.0 data release, the complete ABCD tabulated data resource has been re-curated using a standardized naming convention. This convention implements a keyword system that maps variables to summary scores, indicates branching logic and versioning, and links concepts across domains.

A description of the new variable naming convention can be found here.
A keyword glossary can be found here.

General design of the naming convention

dm_s_tab_item

Variable names consist of four main components, each separated by a single underscore:

Domain
Source/Recipient
Table
Item

The table and item components may include additional subcomponents, which are separated by multiple underscores to indicate nesting within the four main components.

For detailed information about each component of the naming convention, please refer to the documentation here.

As a result, all variables in the tabulated dataset have been renamed according to this new convention. To facilitate the transition of existing workflows, we have retained the mapping to previously used variable and table names in the data dictionary (see here for more details).

We recognize that this change will necessitate adjustments to current analysis pipelines and may introduce some initial friction. However, we believe that this recuration effort will ultimately benefit all users of the ABCD tabulated data resource. The new curation standard resolves many inconsistencies from previous releases and offers a clearer structure that is easier to search and process across the entire dataset.

Curation standards

As part of the recuration effort, we further standardized and improved the accompanying metadata.

A general overview of the curation standards can be found here.
Table-level standards, including participant and session/event IDs as well as collection timestamps and ages are described here.
Variable-level standards, including the systematic encoding of variable and data types, measurement levels, units, variable labels, and coding standards are described here.
Label standards that were implemented to de-duplicate existing labels and ensure that the label for each variable can be understood on its own are described here. Additionally, the Spanish versions of labels were broken out into a separate column in the data dictionary for improved readability.

Additional metadata

The data documentation website has been redesigned to better support responsible and informed data use. Notably, warnings that provide critical context for interpreting the data—such as potential quality concerns and guidance on appropriate usage—have been added throughout the website (see the Responsible Use page for more details).

To integrate the data dictionary more closely with the information provided in the documentation, it now includes additional metadata. This metadata offers hyperlinks to responsible data use and data quality warnings, as well as links to the documentation pages for each table and any applicable summary score documentation for a given variable (see here for more details).

Re-coding of categorical variables

As part of the recuration process, we implemented consistent coding standards for all categorical variables in the tabulated data resource. This included standardizing the coded values for binary responses (e.g., “Yes”/“No” or “True”/“False”) and non-responses (e.g., “Don’t know” or “Decline to answer”). Additionally, we made changes to the coded values of some ordinal and semantic categories—such as grade levels, Likert scales, frequency responses, and income brackets—to create a more logical and intuitive order.

These updates ensure that researchers can more reliably interpret coded values for categorical variables across instruments and domains. Full details on the coding standards for binary and non-responses are provided here. The table below lists all previously released variables that have been affected by these changes to help researchers adjust any existing analysis scripts accordingly.

Re-coded categorical variables

Administration timestamps and ages

In previous ABCD releases through the NIMH Data Archive (NDA), each table included an interview_date column. While the column name suggested that the data was collected on that date, it actually represented the start date of a visit and was duplicated across all tables. This approach did not account for multiday visits or other out-of-sync administrations.

For the 6.0 release, we introduced table-specific administration timepoint variables {table_name}_dtt, which reflect the actual date and time when the forms were administered, when available. This change allows for more precise temporal alignment. Additionally, based on these variables, we provide table-specific age variables {table_name}_age to enhance age-related analyses (see here for more details).

Summary scores

In an effort to correct errors, improve algorithms based on advancements in the relevant fields, increase consistency across measures and domains, and enhance transparency for users, all summary scores computed by the DAIRC² were re-developed for the 6.0 release. This includes both previously released summary scores and new scores developed since the last release.

The code to compute the various scores has been published as an R package called ABCDscores on GitHub and is accompanied by a documentation website. The goal of making the package public is to support transparency and reproducibility of ABCD release data by providing the exact algorithms and code used to compute the released summary scores. This allows users to tie a specific data release version to the corresponding version of the codebase (see also here for the rationale behind creating this R package).

The re-development aimed to implement consistent standards across domains. For example, a maximum of 20% missing ingoing items was established, and wherever possible, (prorated) sums were replaced with means. Additionally, variables reporting the total number of items in a score were removed, as they represent redundant information that does not vary between participants.

Due to the significant changes made to many summary scores included in previous releases, we did not maintain the mapping between current and legacy variable names (see here). This decision was made to indicate to users who may have used those variables in previous analyses that the contents may differ significantly in the 6.0 dataset. Direct comparisons should only be made after consulting ABCDscores and the accompanying documentation to understand the new algorithms.

Other general data changes

During the recuration process, we made several general changes to the data structure and content to improve usability and consistency across the dataset. These changes include:

In previous releases, variables that captured the same concept were sometimes named differently across different events. To reduce redundancy and confusion, these variables have been collapsed into a single variable.
Previously, all variables were associated with a longitudinal event. Static variables (such as race, ethnicity, genetic PCs, etc.) were typically linked to the baseline event. In the 6.0 release, static variables are now provided in static data tables—tables that do not include the session/event column session_id (see here for more details on the identifier columns). This change facilitates easier linking of static variables to the longitudinal data tables.

Core domains

ABCD (General)

Standard variables tables

The 6.0 release includes two new tables that contain important variables likely to be of interest for a wide range of analyses. These tables include static variables (ab_g_stc) and dynamic/longitudinal variables (ab_g_dyn) that are not specific to any particular domain. Examples of these variables include visit-level information, design/nesting variables, and variables useful for describing the cohort.

School and district IDs

For the 6.0 release, school and district IDs were amended due to the following changes. Please note that these changes are specific to the pseudo school ID ab_g_dyn__design_id__district and ab_g_dyn__design_id__school and do not impact the linked SEDA data:

Additional data were recovered from earlier data collection interfaces. These data were used to recalculate available data as prior data releases had applied a filter restricting inclusion to cases with >= 10 pseudo IDs.
Private schools without an NCES ID were inaccurately assigned an anonymized district ID. These district IDs were removed for the 6.0 release.
In prior releases, when an informant reported that a participant was homeschooled, school_id was recoded to ‘0.’ However, in the 6.0 release, participants who were homeschooled were not given a ab_g_dyn__design_id__school/ab_g_dyn__design_id__district unless their homeschooling was associated with an NCES school/district identification number.

Family and birth IDs

In the 6.0 release, we corrected a small number of errors in the ab_g_stc__design_id__fam and ab_g_stc__design_id__birth variables to more accurately reflect sibling relationships between participants. Please disregard data from the rel_family_id and rel_birth_id variables in prior releases in favor of the 6.0 release data.

Site ID

In the 6.0 release, we corrected a small number of errors in the site ID variable, ab_g_dyn__design_site. Please disregard information about sites in prior releases in favor of the 6.0 release data. The site ID is now provided as a categorical variable that lists the site names (e.g., "1"=‘Children’s Hospital Los Angeles’) instead of a coded variable (e.g., "site01").

Ethno-racial identity

Several new ethno-racial identity summary score variables are available in the data release, capturing ethnicity and race based on baseline and longitudinal responses from youth and parents:

ab_g_stc__cohort_ethn: Hispanic vs. non-Hispanic classification
ab_g_stc__cohort_ethnrace__leg: 6-level legacy classification prioritizing Hispanic ethnicity
ab_g_stc__cohort_ethnrace__mblack: 8-level classification highlighting Black identity in multiracial endorsements
ab_g_stc__cohort_ethnrace__mhisp: 8-level classification highlighting Hispanic identity in multiracial endorsements
ab_g_stc__cohort_ethnrace__meim: 15-level classification based on MEIM responses
ab_g_stc__cohort_race__nih: 7-level classification based on NIH standards

Some of these variables are newly introduced in Release 6.0. More detail on how they are computed is available in the ABCDscores package.

Household income

A new household income variable (ab_g_dyn__cohort_income__hhold__3lvl) was created with three distinct levels (as well as "999"=‘Do not know’ and "777"=‘Decline to answer’):

<$50,000
$50,000 to <$100,000
>=$100,000

This variable was developed to offer a convenient categorization of household income, reflecting a common practice among researchers using ABCD data. The selection of cut-offs for each income level was informed by an analysis of alternative categorization methods and a careful examination of cell sizes across all study time points. The goal was to ensure sufficient representation within each level while maintaining the meaningfulness of the income brackets.

This new variable is intended to facilitate ease of use in analysis, particularly for studies where more granular detail is not required. However, more detailed versions of the household income variable also remain available in the dataset (e.g. a variable with 5 levels, ab_g_dyn__cohort_income__hhold__5lvl).

Anonymized Date of Birth

We changed the algorithm for how anonymized birthdates are computed in the 6.0 release. In previous releases, the algorithm always used the 15th day of the month in which a participant was born (for example, if a participant was born on April 18th, 2010, their anonymized birthdate was set to April 15th, 2010).

In the new algorithm, we first determine whether a participant’s birthday falls in the first half (1st–15th) or second half (16th–end) of the month. Then, for each birthday, we randomly select a new day within the same half of the month.

Friends, Family, & Community

This domain was previously referred to as “Culture and Environment”. Detailed information about the instruments, the constructs they are intended to measure, and relevant citations for each measure are provided in the Data Documentation.

Peer Behavior Profile (PBP) summary scores

The workgroup decided that Peer Behavior Profile (PBP) summary scores would not be included in this release, as the available items do not map clearly onto validated subscales. Researchers interested in using these data are encouraged to create their own summary scores using the individual pbp items that best suit their specific analyses.

Values Scale summary scores

The Values Scale currently lacks a summary score for the familism subscale, which will be included in a future data release. The familism construct is computed as follows:

Baseline through 5-Year event: mean of the 17 items from the three scales:
- “Family Support”
- “Family Referent”
- “Family Obligation”
Starting 6-Year event: mean of the 11 items from the two scales:
- “Family Support”
- “Family Referent”

The summary score computation will be included soon in the ABCDscores package and can be used in analyses of 6.0 data.

Genetics

Consistent with the rest of the 6.0 data release, the NDAR_INV prefix has been removed from all subject identifiers in files. Four individuals were also removed from files due to withdrawal of consent or familial genetic relatedness inconsistency. These individuals can be found in the file /dairc/concat/genetics/genotype_microarray/smokescreen/removed_individuals.txt available in the file-based data.

Genetically derived family and birth IDs

In the 6.0 data release, 200 individuals have still not been genotyped from the full enrolled sample and so gn_y_genrel_id__fam and gn_y_genrel_id__birth are not defined for these individuals.

In previous data releases, family relatedness was captured by rel_family_id, this variable is now named gn_y_genrel_id__fam in the genetics table and crosslisted as ab_g_stc__design_id__fam__gen in the ab_g_stc table.

TOPMED imputed data shared as VCFs

TOPMED imputed data is now shared as VCFs (Variant Call File) instead of as PLINK files; this facilitates the inclusion of imputation INFO scores which indicate the quality of imputation and enables the inclusion of multiallelic variants.

To generate PLINK Files from VCFs, please download PLINK2 and run the following commands (in bash shell):

for CHR in {1..23}; do
  plink2 --vcf chr${CHR}_dose.vcf.gz --double-id --import-dosage-certainty 0.9 --make-bed --out chr${CHR}_best_guess
done

ls chr*_best_guess.bed | sed 's/.[^.]*$//' > merge_list.txt

plink2 --pmerge-list merge_list.txt bfile ---make-bed ---out merged_chroms

Linked External Data

School Information

In the 6.0 data release, we have subdivided the SEDA tables into logical subdivisions. Please note the table name changes in Data Documentation.

Data collection process

The original address data collection processes in ABCD relied on a point-in-time capture of residential addresses rather than recording longitudinal residential history. As such addresses reflect participants’ addresses at baseline (e.g., addr1 is primary address at baseline, addr2 secondary address at baseline, addr3 tertiary address at baseline).

We recognize this limitation and the LED Environment and Policy Workgroup has improved the collection of residential history data for more temporal and geographic accuracy of participants’ reported addresses. Future releases will incorporate more comprehensive and accurate address data, but until then, users should be mindful of the limitations of currently available data.

Responsible use warning: Linked External Data

When state-level linkage variables were created, data were inadvertantly linked based on the state of the study site, rather than particiants’ primary residential address.

Users should refer to the private data documentation here for a list of participant_ids that should be excluded from analysis, because their residential address and study site do not coincide, leading to misclassification.

Mental Health

KSADS

As part of the 6.0 curation efforts, ABCD merged data from KSADS 1.0 and 2.0 in order to combine all equivalent symptoms and diagnoses across the two assessment versions into singular variables. However, we were unable to complete this process for the item-level KSADS data. As a result, the 6.0 release does not include individual items, but these will be included in a future release.

Additionally, the symptoms and diagnoses have been moved from a ‘summary scores’ table into their respective module’s table.

KSADS eating disorders

The Mental Health Workgroup did an extensive review of the criteria used for all previously released eating disorder diagnoses in KSADS. The group agreed that the criterion were more restrictive than necessary, and thus underestimated the rates of eating disorder diagnoses. Thus, they determined these diagnoses should be removed from the 6.0 release and recommend users should create their own diagnoses summary scores using the symptom data.

In the meantime, the Mental Health Workgroup is working with KSADS to create more accurate diagnoses, which we hope to include in the 7.0 data release.

KSADS-COMP Updates to 2.0

There was a diagnostic algorithm error detected in 2023 (update pending 7.0):

Diagnoses	Modifications Required
Oppositional Defiant Disorder	Current disorder had allowed for presence of current or past symptoms – current diagnosis will be updated such that only current symptoms can be counted toward current diagnosis.

Life Events (PhenX)

In order to account for changes over time to the Life Events (PhenX) measures it was necessary to develop muliple versions of summary scores. This allows for the summary scores to be computed based on the specific questions asked at each event.

Documentation on youth scores can be found here: Life Events (Youth) Documentation for parent scores can be found here: Life Events (Parent).

Neurocognition

In the 6.0 data release we removed the neurocognition administration table and added all relevant variables specific to a task’s administration to the tables themselves. All such variables related to administration (e.g., visit type, device information, etc.) are indicated by their variable names, in accordance with our new variable naming convention (e.g. dm_s_tab_adm, dm_s_tab_dev, etc.)

Novel Technologies

Screen time questionnaire

The following variables contain non-integer value codes for categorical levels:

nt_y_stq__screen__wkdy_001
nt_y_stq__screen__wkdy_002
nt_y_stq__screen__wkdy_003
nt_y_stq__screen__wkdy_004
nt_y_stq__screen__wkdy_005
nt_y_stq__screen__wkdy_006
nt_y_stq__screen__wknd_001
nt_y_stq__screen__wknd_002
nt_y_stq__screen__wknd_003
nt_y_stq__screen__wknd_004
nt_y_stq__screen__wknd_005
nt_y_stq__screen__wknd_006

These non-integer value prevents these variables to be exported to Stata files when exporting data from DEAP. As a result, they will be excluded from Stata datasets in the current release. This issue will be corrected in the 7.0 data release.

EARS

For ABCD Release 6.0, Ksana Health reprocessed all participant features using improved algorithms. This also led to recomputed summary scores for everyone. The overall scores remain very similar to prior data releases.

Fitbit summary scores

Fitbit summary scores will not be released with the 6.0 data due to calculation errors. The Novel Technologies workgroup is working with the DAIRC to resolve the issues with these scores and they will be made available in a future release.

Fitbit raw data files

Please note that the raw Fitbit data files being released as individual-level csv files in the file-based data contain some known issues:

Device data for some participants was assigned to the wrong session_id. This misassignment may affect analyses that rely on session-level analyses or analyses that depend on temporal accuracy. Authorized users should see the private data documentation for a list of specific participant_ids and session_ids requiring correction. Users can consult this list and apply the necessary adjustments using tools we provide in the NBDCtools package.
sleep-30 second data (files with suffix: _fitbSlp30s_beh.tsv):
- All variables with levels: awake, restless, asleep should be removed.
METs data (files with suffix: _fitbMETs1m_beh.tsv):
- Values are multiplied by 10. Please divide values by 10 to get accurate METs values
sleep-60 second data (files with suffix: _fitbSlp1m_beh.tsv):
- There are inconsistencies in the values and labelling, and the following mapping should be applied:
  - deep –> asleep
  - light –> asleep
  - rem –> asleep
  - restless –> awake
  - wake –> awake

Physical Health

Sexual behavior, orientation, and communication

In the 6.0 data release, variables related to sexual behavior, orientation and communication are available in the “Physical Health” domain, under the Sex subdomain. Relevant variables from other ABCD domains have also been cross-listed in the ph_p_sex and ph_y_sex tables (duplicated from their original tables). Cross-listed variables retain keyword prefixes from their original tables (e.g. kbi for items from the “KSADS Background Items” measure and eut for items from the “Experiences with Unfair Treatment” measure).

Sleep Disturbance Scale for Children (SDS) summary scores

All summary scores were re-calculated for the 6.0 data release. However, SDS summary scores were not included in the development plan and were therefore not ready in time for this release.

The ABCDscores R package will soon be updated to include these scores. Once the updated package has been published, users will be able to compute the scores using the SDS item-level data released in 6.0. The SDS scores will also be included in the 7.0 release.

Substance Use

TLFB corrections

The following corrections have been made ahead of the 6.0 release:

There was an error discovered (12/2022) where repeated substance use events on the TLFB were only recorded once in the individual day-level data files utilized for the calendar scoring; this was corrected in the day-level and calculated data for all waves.
Reports of edibles and MJ concentrates measured in mg have been converted to occasions for consistency across data waves.
In the original TLFB application (prior to 9/2023), errors were noted counting some estimated periods as detailed periods; this was fixed in the current release and any data collected >12 months from SU interview were coded as estimated period.
Maximum daily standard unit dose limits were instituted on the TLFB across all waves to date to reduce outlier events.

6.0 data release known issues:

There is missing TLFB data for some youth participants; some is due to COVID-19 related administration in the home and privacy concerns; others are missing due to research assistant (RA) error (i.e., youth reported using a drug, but RA did not launch TLFB to measure detailed dose/patterns). See su_y_tlfb_adm for SU interview completion details, and variables starting with su_y_tlfb_adm__rmt for details on remote visits.
Some youth have 0’s in their individual TLFB summary data, this occurred rarely if an RA launched the TLFB, put in an initial date of use but did not record any standard units (denoted as N/A in day-level data; this occurred rarely when a youth initially reported using, but then denied use). This issue issue is corrected with the new TLFB app.

We discovered an error in the formula used to calculate all “3-month use days” variables (suffix _3mo_ud). The formula incorrectly used 60 days instead of 90, meaning these variables reflect the last 60 days of use rather than the intended last 90 days. This can be easily corrected using the ABCDscores R Package. To apply the correction:

# Install ABCDscores package
if (!requireNamespace("remotes", quietly = TRUE)) {
  install.packages("remotes")
}
remotes::install_github("nbdc-datahub/ABCDscores")

# Load package
library(ABCDscores)

# Correct TLFB configuration
tlfb_config_3mo <- tlfb_config |>
  dplyr::filter(
    stringr::str_detect(name, "_3mo_")
  ) |>
  dplyr::mutate(
    days = 90
  )

# Compute all _3mo summary scores in the ABCD data resource
data_tlfb_3mo_ss <- purrr::map(
  tlfb_config_3mo$call,
  ~ eval(parse(text = .x))
) |>
  purrr::reduce(
    full_join,
    by = join_by(
      participant_id,
      session_id
    )
  )

The R package will be updated to fix this error. The corrected variables will be included in the 7.0 release, but users can apply the above correction to the 6.0 data release to obtain the correct values.

Imaging Data

New data types

The 6.0 release contains new imaging data types:

Concatenated imaging files (see here).
Raw data files in BIDS format (see here).
Freesurfer derivatives files (see here).

ABCD-BIDS Community Collection (ABCC)

The ABCD-BIDS Community Collection (ABCC) is now included as part of the ABCD releases. To learn more, see the ABCC documentation.

Task-based fMRI

Event timing offset for GE scanners

There was previously a discrepancy in how stimulus times were modeled relative to the end of the calibration/dummy volumes in the image acquisition that affects GE scanners. The issue is related to how the E-prime tasks were programmed for GE scanners that resulted in an unexpected timing offset of 800 msec or less.

We modified our code for extracting event timing information from ABCD E-prime files (https://github.com/ABCD-STUDY/abcd_extract_eprime.git). Rather than rely on the first fixation event (e.g., CueFix.OnsetTime) the modified code now uses the timing data from the initial and or final trigger events (e.g., GetReady.RTTime) to determine the reference time that represents the start of the first non-dummy image volume. We also modified the number of initial volumes discarded prior to task fMRI time series analysis for GE scanners, with 4 volumes removed for GE DV26 and 15 volumes removed for GE DV26 and later.

E-Prime timing errors for GE scanners

In a relatively small, though substantial, subset of task fMRI acquisitions collected on GE scanners (~9% of runs), the time between the 1st and 16th trigger pulse sent from the scanner does not match the expected 12 seconds.

We modified our task fMRI analysis pipeline to calculate trigger pulse timing discrepancies to identify E-prime runs for which the delay between the first trigger pulse and last recorded trigger pulse does not match the expectation (12 seconds for GE scanners). In cases where the discrepancy was either 0.8, 1.6, or 2.4 seconds (or within 0.01 seconds of those values), indicating missed (undetected) trigger pulses (~3% of runs), we adjusted the start time (used as the reference for subsequent events) by subtracting the discrepancy. We further modified the task fMRI analysis pipeline to exclude from processing any other runs that had a start time discrepancy (absolute difference from expectation relative to initial trigger pulse) larger than 0.5 seconds (~6% of runs), as such cases reflect irregular trigger timing and make it difficult or impossible to be sure when the stimulus run started relative to the imaging scan. For imaging visits with no valid task fMRI runs due to timing discrepancies, no derived results will be produced, and the imaging inclusion flags for the corresponding task will be set to 0. See Data Documentation.

We also sought to identify runs for which the delay between the start of the run and the onset of the first fixation does not match the expectation (500 msec for 1st nBack run on GE scanners, 0 msec otherwise). Runs with an onset time delay greater than 5 seconds were excluded from processing. Smaller discrepancies (i.e., up to 5 seconds) were allowed for this type of delay, because they do not introduce an error in the time series analysis, like an unknown delay between the start of the scan and the start of the run would. Instead, there is merely a shift in the timing of events relative to the start of the run, which can be correctly modeled.

Column misnaming in rsfMRI network to subcortical ROI correlation tabulated data

The column names in the table mr_y_rsfmri__corr__gpnet__aseg, which contains the tabulated imaging data for rsfMRI correlations between networks and subcortical ROIs, were corrected in the current release. In previous releases, columns were systematically misnamed. That is, the ordering of the column names did not match the ordering of the values of the columns. This problem was caused by swapping the inner and outer loops when iterating over networks and subcortical ROIs while constructing the column names. For example, to correctly match the data, instead of all ROIs for the first network having been listed first, all networks for the first ROI should have been listed first.

Table providing mapping between wrong and corrected names

The table below provides the mapping between column names included in the 6.0 release with the incorrect column names that were included in the 5.1 and prior releases, along with the correct column names that should have been used previously.

Substudies

Magnetic Resonance Spectroscopy (MRS)

Data from the ABCD Magnetic Resonance Spectroscopy (MRS) Substudy data is now available in the 6.0 Release. Tabulated data is provided in the mrs_y_2dj and mrs_y_hermes tables. File-based data for participants of the MRS Substudy are available in the imaging sourcedata/ directory. See here for more information about the MRS substudy.

Footnotes

Please note that the event identifier has been changed to be compatible with the BIDS standard; read more here.↩︎
The dataset includes other summary scores, such as proprietary scores or summary scores imported from external sources.↩︎