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Filter Cart

The Filter Cart provides a way to query and access data for which you may be interested.  There are multiple places to go query and Add to Filter Cart (Sometimes called Download).  

A few points related to the filter cart are important to understand with the NDA Query/Filter implementation: 

First, the filter cart is populated asyncronously.  So, when you add subjects, sometimes it may take a few minutes to populate.  You can continue to do other things during this time. 

When you are adding your first filter, all data associated with your query will be added to the filter cart (whether it be a collection, a concept, a study, a data structure/elment or subjects). Not all data available for the subjects selected will necessarily be displayed.  For example, if you select the NDA imaging structure image03, and further restrict that query to scan_type fMRI, only fMRI images will appear and only the image03 structure will be available.  However, if you want to see all of the clinical and phenotype, then select, "Find All Subject Data" to see all the data avaialble for those subjects.  

when a secord or third filter is applied, an AND condition is used to determine the subjects that are exist in all filters.  If the subject does not appear in any filter, that subjects data will be excluded from your filter cart. Given the sparcity of data in the NDA, it is possible for no subjects to appear across filters.  If that happens, clear your filter cart, and start over.  

The NDA is looking to enhance query/filtering.  Until additional tools become available, it is best to package more data than you need and then package and download the data and use other tools to further restrict and analyze the data.  If you have any questions on data access, are interested in using avaialble web services or need help accessing data, please contact us for assistance.  

Frequently Asked Questions

Glossary

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NDAR provides a single access to de-identified autism research data. For permission to download data, you will need an NDAR account with approved access to NDAR or a connected repository (AGRE, IAN, or the ATP). For NDAR access, you need to be a research investigator sponsored by an NIH recognized institution with federal wide assurance. See Request Access for more information.

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The filters you have selected from various query interfaces will be stored here, in the 'Filter Cart'. The database will be queried using filters added to your 'Filter Cart', when multiple filters are defined, each will be executed using 'AND' logic, so with each filter that is applied the result set gets smaller.

From the 'Filter Cart' you can inspect each of the filters that have been defined, and you also have the option to remove filters. The 'Filter Cart' itself will display the number of filters applied along with the number of subjects that are identified by the combination of those filters. For example a GUID filter with two subjects, followed by a GUID filter for just one of those subjects would return only data for the subject that is in both GUID filters.

If you have a question about the filter cart, or underlying filters please contact the help desk at The NDA Help Desk

Description
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Notes
Data Structures with shared data
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ABCD MRI Behavior SST

abcd_sst

01

Download Definition as
Download Submission Template as
Element NameData TypeSizeRequiredDescriptionValue RangeNotesAliases
subjectkeyGUIDRequiredThe NDAR Global Unique Identifier (GUID) for research subjectNDAR*
src_subject_idString20RequiredSubject ID how it's defined in lab/projectbeh_sst_subj_id
interview_dateDateRequiredDate on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYYRequired field
interview_ageIntegerRequiredAge in months at the time of the interview/test/sampling/imaging.0 :: 1260Age is rounded to chronological month. If the research participant is 15-days-old at time of interview, the appropriate value would be 0 months. If the participant is 16-days-old, the value would be 1 month.
genderString20RequiredBlock Brief 2000: Sex of the subjectM;FM = Male; F = Female
eventnameString60RequiredThe event name for which the data was collected
beh_sst_visit_idString30RecommendedBaseline visit
beh_sst_switch_flagIntegerRecommendedBox was switched
beh_sst_go_totalIntegerRecommendedTotal number of "Go" trials
beh_sst_stop_totalIntegerRecommendedTotal number of "Stop" trials
beh_sst_totalIntegerRecommendedTotal number of trials
beh_sst_go_total_run_1IntegerRecommendedTotal number of "Go" trials in run 1
beh_sst_stop_total_run_1IntegerRecommendedTotal number of "Stop" trials in run 1
beh_sst_go_total_run_2IntegerRecommendedTotal number of "Go" trials in run 2
beh_sst_stop_total_run_2IntegerRecommendedTotal number of "Stop" trials in run 2
bs_cor_go_counts_totalIntegerRecommendedTotal number of correct "Go" trialsbeh_sst_cor_go_counts_total
bs_cor_go_counts_run_1IntegerRecommendedTotal number of correct "Go" trials in run 1beh_sst_cor_go_counts_run_1
bs_cor_go_counts_run_2IntegerRecommendedTotal number of correct "Go" trials in run 2beh_sst_cor_go_counts_run_2
bs_cor_go_percent_totalFloatRecommendedPercentage of correct "Go" trials (cor_go_counts_total / go_total)beh_sst_cor_go_percent_total
bs_cor_go_percent_run_1FloatRecommendedPercentage of correct "Go" trials in run 1(cor_go_counts_run_1 / go_total_run_1)beh_sst_cor_go_percent_run_1
bs_cor_go_percent_run_2FloatRecommendedPercentage of correct "Go" trials in run 2(cor_go_counts_run_2 / go_total_run_2)beh_sst_cor_go_percent_run_2
bs_cor_go_rt_totalFloatRecommendedMean response time for all correct "Go" trialsbeh_sst_cor_go_rt_total
bs_cor_go_rt_std_totalFloatRecommendedStandard deviation of response times for all correct "Go" trialsbeh_sst_cor_go_rt_std_total
bs_cor_go_rt_run_1FloatRecommendedMean response time for all correct "Go" trials in run 1beh_sst_cor_go_rt_run_1
bs_cor_go_rt_std_run_1FloatRecommendedStandard deviation of response times for all correct "Go" trials in run 1beh_sst_cor_go_rt_std_run_1
bs_cor_go_rt_run_2FloatRecommendedMean response time for all correct "Go" trials in run 2beh_sst_cor_go_rt_run_2
bs_cor_go_rt_std_run_2FloatRecommendedStandard deviation of response times for all correct "Go" trials in run 2beh_sst_cor_go_rt_std_run_2
bs_corlate_go_counts_totalIntegerRecommendedTotal number of "Go" trials that were correctly answered late (after the response window passed)beh_sst_corlate_go_counts_total
bs_corlate_go_counts_run_1IntegerRecommendedTotal number of "Go" trials that were correctly answered late in run 1beh_sst_corlate_go_counts_run_1
bs_corlate_go_counts_run_2IntegerRecommendedTotal number of go trials that were correctly answered late in run 2beh_sst_corlate_go_counts_run_2
bs_corlate_go_percent_totalFloatRecommendedPercentage of correct "Go" trials answered late (corlate_go_counts_total/go_total)beh_sst_corlate_go_percent_total
bs_corlate_go_percent_run_1FloatRecommendedPercentage of correct "Go" trials answered late (corlate_go_counts_run_1/go_total_run_1)beh_sst_corlate_go_percent_run_1
bs_corlate_go_percent_run_2FloatRecommendedPercentage of correct "Go" trials answered late (corlate_go_counts_run_2/go_total_run_2)beh_sst_corlate_go_percent_run_2
bs_corlate_go_rt_totalFloatRecommendedMean response time for all correct but late "Go" trialsbeh_sst_corlate_go_rt_total
bs_corlate_go_rt_std_totalFloatRecommendedStandard deviation of response times for all correct but late "Go" trialsbeh_sst_corlate_go_rt_std_total
bs_corlate_go_rt_run_1FloatRecommendedMean response time for all correct but late "Go" trials in run 1beh_sst_corlate_go_rt_run_1
bs_corlate_go_rt_std_run_1FloatRecommendedStandard deviation of response times for all correct but late "Go" trials in run 1beh_sst_corlate_go_rt_std_run_1
bs_corlate_go_rt_run_2FloatRecommendedMean response time for all correct but late "Go" trials in run 2beh_sst_corlate_go_rt_run_2
bs_corlate_go_rt_std_run_2FloatRecommendedStandard deviation of response times for all correct but late "Go" trials in run 2beh_sst_corlate_go_rt_std_run_2
bs_incor_go_counts_totalIntegerRecommendedTotal number of "Go" trials that were answered incorrectlybeh_sst_incor_go_counts_total
bs_incor_go_counts_run_1IntegerRecommendedTotal number of "Go" trials that were answered incorrectly in run 1beh_sst_incor_go_counts_run_1
bs_incor_go_counts_run_2IntegerRecommendedTotal number of "Go" trials that were answered incorrectly in run 2beh_sst_incor_go_counts_run_2
bs_incor_go_percent_totalFloatRecommendedPercentage of "Go" trials that were answered incorrectly (incor_go_counts_total/go_total)beh_sst_incor_go_percent_total
bs_incor_go_percent_run_1FloatRecommendedPercentage of "Go" trials that were answered incorrectly in run 1 (incor_go_counts_run_1/go_total_run_1)beh_sst_incor_go_percent_run_1
bs_incor_go_percent_run_2FloatRecommendedPercentage of "Go" trials that were answered incorrectly in run 2 (incor_go_counts_run_2/go_total_run_2)beh_sst_incor_go_percent_run_2
bs_incor_go_rt_totalFloatRecommendedMean response time for all incorrect "Go" trialsbeh_sst_incor_go_rt_total
bs_incor_go_rt_std_totalFloatRecommendedStandard deviation of response times for all incorrect "Go" trialsbeh_sst_incor_go_rt_std_total
bs_incor_go_rt_run_1FloatRecommendedMean response time for all incorrect "Go" trials in run 1beh_sst_incor_go_rt_run_1
bs_incor_go_rt_std_run_1FloatRecommendedStandard deviation of response times for all incorrect "Go" trials in run 1beh_sst_incor_go_rt_std_run_1
bs_incor_go_rt_run_2FloatRecommendedMean response time for all incorrect "Go" trials in run 2beh_sst_incor_go_rt_run_2
bs_incor_go_rt_std_run_2FloatRecommendedStandard deviation of response times for all incorrect "Go" trials in run 2beh_sst_incor_go_rt_std_run_2
bs_incorlate_go_counts_totalIntegerRecommendedTotal number of "Go" trials that were correctly answered incorrectly and latebeh_sst_incorlate_go_counts_total
bs_incorlate_go_counts_run_1IntegerRecommendedTotal number of "Go" trials that were answered incorrectly and late in run 1beh_sst_incorlate_go_counts_run_1
bs_incorlate_go_counts_run_2IntegerRecommendedTotal number of "Go" trials that were answered incorrectly and late in run 2beh_sst_incorlate_go_counts_run_2
bs_incorlate_go_percent_totalFloatRecommendedPercentage of incorrect and late go trials (incorlate_go_counts_total/go_total)beh_sst_incorlate_go_percent_total
bs_incorlate_go_percent_run_1FloatRecommendedPercentage of incorrect and late "Go" trials (incorlate_go_counts_run_1/go_total_run_1)beh_sst_incorlate_go_percent_run_1
bs_incorlate_go_percent_run_2FloatRecommendedPercentage of incorrect and late "Go" trials (incorlate_go_counts_run_2/go_total_run_2)beh_sst_incorlate_go_percent_run_2
bs_incorlate_go_rt_totalFloatRecommendedMean response time for all incorrect and late "Go" trialsbeh_sst_incorlate_go_rt_total
bs_incorlate_go_rt_std_totalFloatRecommendedStandard deviation of response times for all incorrect but late "Go" trialsbeh_sst_incorlate_go_rt_std_total
bs_incorlate_go_rt_run_1FloatRecommendedMean response time for all incorrect and late "Go" trials in run 1beh_sst_incorlate_go_rt_run_1
bs_incorlate_go_rt_std_run_1FloatRecommendedStandard deviation of response times for all incorrect but late "Go" trials in run 1beh_sst_incorlate_go_rt_std_run_1
bs_incorlate_go_rt_run_2FloatRecommendedMean response time for all incorrect and late "Go" trials in run 2beh_sst_incorlate_go_rt_run_2
bs_incorlate_go_rt_std_run_2FloatRecommendedStandard deviation of response times for all incorrect and late "Go" trials in run 2beh_sst_incorlate_go_rt_std_run_2
bs_noresp_go_counts_totalIntegerRecommendedTotal number of "Go" trials unansweredbeh_sst_noresp_go_counts_total
bs_noresp_go_counts_run_1IntegerRecommendedTotal number of "Go" trials unanswered in run 1beh_sst_noresp_go_counts_run_1
bs_noresp_go_counts_run_2IntegerRecommendedTotal number of "Go" trials unanswered in run 2beh_sst_noresp_go_counts_run_2
bs_noresp_go_percent_totalFloatRecommendedPercentage of "Go" trials unanswered (noresp_go_counts_total/go_total)beh_sst_noresp_go_percent_total
bs_noresp_go_percent_run_1FloatRecommendedPercentage of "Go" trials unanswered in run 1 (noresp_go_counts_run_1/go_total_run_1)beh_sst_noresp_go_percent_run_1
bs_noresp_go_percent_run_2FloatRecommendedPercentage of "Go" trials unanswered in run 2 (noresp_go_counts_run_2/go_total_run_2)beh_sst_noresp_go_percent_run_2
bs_cor_stop_counts_totalIntegerRecommendedTotal number of correct "Stop" trialsbeh_sst_cor_stop_counts_total
bs_cor_stop_counts_run_1IntegerRecommendedTotal number of correct "Stop" trials in run 1beh_sst_cor_stop_counts_run_1
bs_cor_stop_counts_run_2IntegerRecommendedTotal number of correct "Stop" trials in run 2beh_sst_cor_stop_counts_run_2
bs_cor_stop_percent_totalFloatRecommendedPercentage of correct "Stop" trials (cor_stop_counts_total/stop_total)beh_sst_cor_stop_percent_total
bs_cor_stop_percent_run_1FloatRecommendedPercentage of correct "Stop" trials in run 1 (cor_stop_counts_run_1/stop_total_run_1)beh_sst_cor_stop_percent_run_1
bs_cor_stop_percent_run_2FloatRecommendedPercentage of correct "Stop" trials in run 2 (cor_stop_counts_run_2/stop_total_run_2)beh_sst_cor_stop_percent_run_2
bs_incor_stop_counts_totalIntegerRecommendedTotal number of "Stop" trials answered incorrectlybeh_sst_incor_stop_counts_total
bs_incor_stop_counts_run_1IntegerRecommendedTotal number of "Stop" trials answered incorrectly in run 1beh_sst_incor_stop_counts_run_1
bs_incor_stop_counts_run_2IntegerRecommendedTotal number of "Stop" trials answered incorrectly in run 2beh_sst_incor_stop_counts_run_2
bs_incor_stop_percent_totalFloatRecommendedPercentage of "Stop" trials answered incorrectly(incor_stop_counts_total/stop_total)beh_sst_incor_stop_percent_total
bs_incor_stop_percent_run_1FloatRecommendedPercentage of "Stop" trials answered incorrectly in run 1 (incor_stop_counts_run_1/stop_total_run_1)beh_sst_incor_stop_percent_run_1
bs_incor_stop_percent_run_2FloatRecommendedPercentage of "Stop" trials answered incorrectly in run 2 (incor_stop_counts_run_2/stop_total_run_2)beh_sst_incor_stop_percent_run_2
bs_incor_stop_rt_totalFloatRecommendedMean response time for all incorrect "Stop" trialsbeh_sst_incor_stop_rt_total
bs_incor_stop_rt_std_totalFloatRecommendedStandard deviation of response times for all incorrect "Stop" trialsbeh_sst_incor_stop_rt_std_total
bs_incor_stop_rt_run_1FloatRecommendedMean response time for all incorrect "Stop" trials in run 1beh_sst_incor_stop_rt_run_1
bs_incor_stop_rt_std_run_1FloatRecommendedStandard deviation of response times for all incorrect "Stop" trials in run 1beh_sst_incor_stop_rt_std_run_1
bs_incor_stop_rt_run_2FloatRecommendedMean response time for all incorrect "Stop" trials in run 2beh_sst_incor_stop_rt_run_2
bs_incor_stop_rt_std_run_2FloatRecommendedStandard deviation of response times for all incorrect "Stop" trials in run 2beh_sst_incor_stop_rt_std_run_2
bs_ssd_stop_counts_totalIntegerRecommendedTotal number of "Stop" trials that were answered before the "Stop" signal was presentedbeh_sst_ssd_stop_counts_total
bs_ssd_stop_counts_run_1IntegerRecommendedTotal number of "Stop" trials that were answered before the "Stop" signal was presented in run 1beh_sst_ssd_stop_counts_run_1
bs_ssd_stop_counts_run_2IntegerRecommendedTotal number of "Stop" trials that were answered before the "Stop" signal was presented in run 2beh_sst_ssd_stop_counts_run_2
bs_ssd_stop_percent_totalFloatRecommendedPercentage of "Stop" trials that were answered before the "Stop" signal was presented (ssd_stop_counts_total/stop_total)beh_sst_ssd_stop_percent_total
bs_ssd_stop_percent_run_1FloatRecommendedPercentage of "Stop" trials that were answered before the "Stop" signal was presented in run 1 (ssd_stop_counts_run_1/stop_total_run_1)beh_sst_ssd_stop_percent_run_1
bs_ssd_stop_percent_run_2FloatRecommendedPercentage of "Stop" trials that were answered before the "Stop" signal was presented in run 2 (ssd_stop_counts_run_2/stop_total_run_2)beh_sst_ssd_stop_percent_run_2
beh_sst_ssd_mean_totalFloatRecommendedMean stop signal delay for all "Stop" trials
beh_sst_ssrt_mean_totalFloatRecommendedMean stop signal reaction time (cor_go_rt_total-ssd_mean_total)
beh_mid_perform_flagIntegerRecommendedWhether the participant had an acceptable performance in the task; all trial types must yield more than 3 events for both positive and negative feedback0;11= acceptable = 0= not acceptablebeh_sst_perform_flag
beh_mid_nrunsIntegerRecommendedNumber of valid runs in the filebeh_sst_nruns
Data Structure

This page displays the data structure defined for the measure identified in the title and structure short name. The table below displays a list of data elements in this structure (also called variables) and the following information:

  • Element Name: This is the standard element name
  • Data Type: Which type of data this element is, e.g. String, Float, File location.
  • Size: If applicable, the character limit of this element
  • Required: This column displays whether the element is Required for valid submissions, Recommended for valid submissions, Conditional on other elements, or Optional
  • Description: A basic description
  • Value Range: Which values can appear validly in this element (case sensitive for strings)
  • Notes: Expanded description or notes on coding of values
  • Aliases: A list of currently supported Aliases (alternate element names)
  • For valid elements with shared data, on the far left is a Filter button you can use to view a summary of shared data for that element and apply a query filter to your Cart based on selected value ranges

At the top of this page you can also:

  • Use the search bar to filter the elements displayed. This will not filter on the Size of Required columns
  • Download a copy of this definition in CSV format
  • Download a blank CSV submission template prepopulated with the correct structure header rows ready to fill with subject records and upload

Please email the The NDA Help Desk with any questions.

Distribution for DataStructure: abcd_sst01 and Element:
Chart Help

Filters enable researchers to view the data shared in NDA before applying for access or for selecting specific data for download or NDA Study assignment. For those with access to NDA shared data, you may select specific values to be included by selecting an individual bar chart item or by selecting a range of values (e.g. interview_age) using the "Add Range" button. Note that not all elements have appropriately distinct values like comments and subjectkey and are not available for filtering. Additionally, item level detail is not always provided by the research community as indicated by the number of null values given.

Filters for multiple data elements within a structure are supported. Selections across multiple data structures will be supported in a future version of NDA.