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Viewable at the top right of NDA pages, the Filter Cart is a temporary holder for filters and data they select. Filters are added to the Workspace first, before being submitted to The Filter Cart. Data selected by filters in the Filter Cart can be added to a Data Package or an NDA Study from the Data Packaging Page, by clicking the 'Create Data Package / Add Data to Study' button.

The filter cart supports combining multiple filters together, and depending on filter type will use "AND" or "OR"  when combining filters.

Multiple selections from the same filter type will result in those selections being applied with an ‘OR’ condition. For example, if you add an NDA Collection Filter with selections for both collections 2112 and 2563 to an empty Workspace, the subjects from NDA Collection 2112 ‘OR’ NDA Collection 2563 will be added to your Workspace even if a subject is in both NDA Collections. You can then add other NDA Collections to your Workspace which further extends the ‘OR’ condition.

If a different filter type is added to your Workspace, or a filter has already been submitted to the Filter Cart, the operation then performs a logical ‘AND’ operation. This means that given the subjects returned from the first filter, only those subjects that matched the first filter are returned by the second filter (i.e., subjects that satisfied both filters). Note that only the subjects specific to your filter will be added to your Filter Cart and only on data shared with the research community. Other data for those same subjects may exist (i.e., within another NDA Collection, associated with a data structure that was not requested in the query, etc.). So, users should select ‘Find all Subjects Data’ to identify all data for those specific subjects. 

Additional Tips:

  • You may query the data without an account, but to gain access you will need to create an NDA user account and apply for access.  Most data access requires that you or your lab are sponsored by an NIH recognized institution with Federal Wide Assurance (FWA).  Without access, you will not be able to obtain individual-level data. 

    Once you have selected data of interest you can:
  • Create a data package - This allows you to specify format for access/download
  • Assign to Study Cohort - Associate the data to an NDA Study allowing for a DOI to be generated and the data to be linked directly to a finding, publication, or data release. 
  • Find All Subject Data - Depending on filter types being used, not all data associated with a subject will be selected.  Data may be restricted by data structure, NDA Collection, or outcome variables (e.g., NDA Study). ‘Find All Data’ expands the fliter criteria by replacing all filters in your Filter Cart with a single Query by GUID filter for all subjects selected by those filters.

    Please Note:
  • When running a query, it may take a moment to populate the Filter Cart. Queries happen in the background so you can define other queries during this time. 
  • When you add your first filter, all data associated with your query will be added to the Filter Cart (e.g., a Concept, an NDA Collection, a Data Structure/Element, etc.). As you add additional filters, they will also display in the Filter Cart. Only the name of filter will be shown in the Filter Cart, not the underlying structures. 
  • Information about the contents of the Filter Cart can be seen by clicking "Edit”.
  • Once your results appear in the Filter Cart, you can create a data package or assign subjects to a study by selecting the 'Package/Assign to Study' option. You can also 'Edit' or 'Clear' filters.
     

Frequently Asked Questions

  • The Filter Cart currently employs basic AND/OR Boolean logic. A single filter may contain multiple selections for that filter type, e.g., a single NDA Study filter might contain NDA Study 1 and NDA Study 2. A subject that is in EITHER 1 OR 2 will be returned.  Adding multiple filters to the cart, regardless of type, will AND the result of each filter.  If NDA Study 1 and NDA Study 2 are added as individual filters, data for a subject will only be selected if the subject is included in  BOTH 1 AND 2.

  • Viewable at the top right of NDA pages, the Filter Cart is a temporary holder of data identified by the user, through querying or browsing, as being of some potential interest. The Filter Cart is where you send the data from your Workspace after it has been filtered.

  • After filters are added to the Filter Cart, users have options to ‘Create a Package’ for download, ‘Associate to Study Cohort’, or ‘Find All Subject Data’. Selecting ‘Find All Subject Data’ identifies and pulls all data for the subjects into the Filter Cart. Choosing ‘Create a Package’ allows users to package and name their query information for download. Choosing ‘Associate to Study Cohort’ gives users the opportunity to choose the Study Cohort they wish to associate this data.

Glossary

  • Once your filter cart contains the subjects of interest, select Create Data Package/Assign to Data Study which will provide options for accessing item level data and/or assigning to a study.  

  • Once queries have been added to your workspace, the next step is to Submit the Filters in the workspace to the Filter Cart.  This process runs the queries selected, saving the results within a filter cart attached to your account.  

  • The Workspace within the General Query Tool is a holding area where you can review your pending filters prior to adding them to Filter Cart. Therefore, the first step in accessing data is to select one or more items and move it into the Workspace. 

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Data Structures with shared data
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ABCD Task fMRI REC Behavior

8,974 Shared Subjects

Behavioral performance measures for nBack task fMRI (post-scan recall)
Clinical Assessments
Task Based
06/29/2018
mribrec02
06/26/2020
View Change History
02
Query Element Name Data Type Size Required Description Value Range Notes Aliases
subjectkey GUID Required The NDAR Global Unique Identifier (GUID) for research subject NDAR*
src_subject_id String 20 Required Subject ID how it's defined in lab/project
interview_date Date Required Date on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYY Required field
interview_age Integer Required Age in months at the time of the interview/test/sampling/imaging. 0 :: 1260 Age 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.
sex String 20 Required Sex of the subject M;F; O; NR M = Male; F = Female; O=Other; NR = Not reported gender
eventname String 60 Required The event name for which the data was collected
tfmri_rec_beh_visitid String 60 Recommended Visit name tfmri_rec_beh_visitid
Query tfmri_rec_beh_switchflag Integer Recommended Whether the button box responses were switched 0;1 1= switch; 0= no switch tfmri_rec_beh_switch.flag
Query tfmri_rec_all_beh_newnf_hr Float Recommended Hit rate of new neutral faces correctly recognized tfmri_rec_all_beh_new.neut.face_hr, tfmri_rec_all_beh_newneutface_hr
Query tfmri_rec_all_beh_newnf_fa Float Recommended False alarm of new neutral faces shown tfmri_rec_all_beh_new.neut.face_fa, tfmri_rec_all_beh_newneutface_fa
Query tfmri_rec_all_beh_newpl_hr Float Recommended Hit rate of new place correctly recognized tfmri_rec_all_beh_new.place_hr, tfmri_rec_all_beh_newplace_hr
Query tfmri_rec_all_beh_newpl_fa Float Recommended False alarm of new place shown tfmri_rec_all_beh_new.place_fa, tfmri_rec_all_beh_newplace_fa
Query tfmri_rec_all_beh_newposf_hr Float Recommended Hit rate of new positive face correctly recognized tfmri_rec_all_beh_new.pos.face_hr, tfmri_rec_all_beh_newposface_hr
Query tfmri_rec_all_beh_newposf_fa Float Recommended False alarm of new positive faces shown tfmri_rec_all_beh_new.pos.face_fa, tfmri_rec_all_beh_newposface_fa
Query tfmri_rec_all_beh_newnegf_hr Float Recommended Hit rate of new negative face correctly recognized tfmri_rec_all_beh_new.neg.face_hr, tfmri_rec_all_beh_newnegface_hr
Query tfmri_rec_all_beh_newnegf_fa Float Recommended False alarm of new negative faces shown tfmri_rec_all_beh_new.neg.face_fa, tfmri_rec_all_beh_newnegface_fa
Query tfmri_rec_all_beh_oldposf_hr Float Recommended Hit rate of positive faces shown in the N-back task correctly recognized tfmri_rec_all_beh_old.pos.face_hr, tfmri_rec_all_beh_oldposface_hr
Query tfmri_rec_all_beh_oldposf_fa Float Recommended False alarm of positive faces shown in the n-back task tfmri_rec_all_beh_old.pos.face_fa, tfmri_rec_all_beh_oldposface_fa
Query tfmri_rec_all_beh_oldposf2b_hr Float Recommended Hit rate of positive faces shown in the n-back task and in a 2-back block correctly recognized tfmri_rec_all_beh_old.pos.face.2.back_hr, tfmri_rec_all_beh_oldposface2back_hr
Query tfmri_rec_all_beh_oldposf2b_fa Float Recommended False alarm of positive faces shown in the n-back task and in a 2-back block tfmri_rec_all_beh_old.pos.face.2.back_fa, tfmri_rec_all_beh_oldposface2back_fa
Query tfmri_rec_all_beh_oldposf0b_hr Float Recommended Hit rate of positive faces shown in the n-back task and in a 0-back block correctly recognized tfmri_rec_all_beh_old.pos.face.0.back_hr, tfmri_rec_all_beh_oldposface0back_hr
Query tfmri_rec_all_beh_oldposf0b_fa Float Recommended False alarm of positive faces shown in the n-back task and in a 0-back block tfmri_rec_all_beh_old.pos.face.0.back_fa, tfmri_rec_all_beh_oldposface0back_fa
Query tfmri_rec_all_beh_oldpl_hr Float Recommended Hit rate of places shown in the N-back task correctly recognized tfmri_rec_all_beh_old.place_hr, tfmri_rec_all_beh_oldplace_hr
Query tfmri_rec_all_beh_oldpl_fa Float Recommended False alarm of places shown in the n-back task tfmri_rec_all_beh_old.place_fa, tfmri_rec_all_beh_oldplace_fa
Query tfmri_rec_all_beh_oldpl2b_hr Float Recommended Hit rate of places shown in the n-back task and in a 2-back block correctly recognized tfmri_rec_all_beh_old.place.2.back_hr, tfmri_rec_all_beh_oldplace2back_hr
Query tfmri_rec_all_beh_oldpl2b_fa Float Recommended False alarm of placesshown in the n-back task and in a 2-back block tfmri_rec_all_beh_old.place.2.back_fa, tfmri_rec_all_beh_oldplace2back_fa
Query tfmri_rec_all_beh_oldpl0b_hr Float Recommended Hit rate of places shown in the n-back task and in a 0-back block correctly recognized tfmri_rec_all_beh_old.place.0.back_hr, tfmri_rec_all_beh_oldplace0back_hr
Query tfmri_rec_all_beh_oldpl0b_fa Float Recommended False alarm of placesshown in the n-back task and in a 0-back block tfmri_rec_all_beh_old.place.0.back_fa, tfmri_rec_all_beh_oldplace0back_fa
Query tfmri_rec_all_beh_oldnegf_hr Float Recommended Hit rate of negative faces shown in the N-back task correctly recognized tfmri_rec_all_beh_old.neg.face_hr, tfmri_rec_all_beh_oldnegface_hr
Query tfmri_rec_all_beh_oldnegf_fa Float Recommended False alarm of negative faces shown in the n-back task tfmri_rec_all_beh_old.neg.face_fa, tfmri_rec_all_beh_oldnegface_fa
Query tfmri_rec_all_beh_oldnegf2b_hr Float Recommended Hit rate of negative faces shown in the n-back task and in a 2-back block correctly recognized tfmri_rec_all_beh_old.neg.face.2.back_hr, tfmri_rec_all_beh_oldnegface2back_hr
Query tfmri_rec_all_beh_oldnegf2b_fa Float Recommended False alarm of negative faces shown in the n-back task and in a 2-back block tfmri_rec_all_beh_old.neg.face.2.back_fa, tfmri_rec_all_beh_oldnegface2back_fa
Query tfmri_rec_all_beh_oldnegf0b_hr Float Recommended Hit rate of negative faces shown in the n-back task and in a 0-back block correctly recognized tfmri_rec_all_beh_old.neg.face.0.back_hr, tfmri_rec_all_beh_oldnegface0back_hr
Query tfmri_rec_all_beh_oldnegf0b_fa Float Recommended False alarm of positive faces shown in the n-back task and in a 0-back block tfmri_rec_all_beh_old.neg.face.0.back_fa, tfmri_rec_all_beh_oldnegface0back_fa
Query tfmri_rec_all_beh_oldnf_hr Float Recommended Hit rate of neutral faces shown in the N-back task correctly recognized tfmri_rec_all_beh_old.neut.face_hr, tfmri_rec_all_beh_oldneutface_hr
Query tfmri_rec_all_beh_oldnf_fa Float Recommended False alarm of neutral faces shown in the n-back task tfmri_rec_all_beh_old.neut.face_fa, tfmri_rec_all_beh_oldneutface_fa
Query tfmri_rec_all_beh_oldnf2b_hr Float Recommended Hit rate of neutral faces shown in the n-back task and in a 2-back block correctly recognized tfmri_rec_all_beh_old.neut.face.2.back_hr, tfmri_rec_all_beh_oldneutface2back_hr
Query tfmri_rec_all_beh_oldnf2b_fa Float Recommended False alarm of neutral faces shown in the n-back task and in a 2-back block tfmri_rec_all_beh_old.neut.face.2.back_fa, tfmri_rec_all_beh_oldneutface2back_fa
Query tfmri_rec_all_beh_oldnf0b_hr Float Recommended Hit rate of neutral faces shown in the n-back task and in a 0-back block correctly recognized tfmri_rec_all_beh_old.neut.face.0.back_hr, tfmri_rec_all_beh_oldneutface0back_hr
Query tfmri_rec_all_beh_oldnf0b_fa Float Recommended False alarm of neutral faces shown in the n-back task and in a 0-back block tfmri_rec_all_beh_old.neut.face.0.back_fa, tfmri_rec_all_beh_oldneutface0back_fa
Query tfmri_rec_all_beh_posface_pr Float Recommended Corrected accuracy for positive faces computed as tfmri_rec_all_beh_old.pos.face_hr-tfmri_rec_all_beh_new.pos.face_fa tfmri_rec_all_beh_pos.face_pr
Query tfmri_rec_all_beh_posface_br Float Recommended Response bias for positive faces computed as (tfmri_rec_all_beh_new.pos.face_fa/(1-(tfmri_rec_all_beh_old.pos.face_hr - tfmri_rec_all_beh_new.pos.face_fa))) - 0.5 tfmri_rec_all_beh_pos.face_br
Query tfmri_rec_all_beh_posf_dpr Float Recommended D-prime computed as norminv(tfmri_rec_all_beh_old.pos.face_hr) - norminv(tfmri_rec_all_beh_new.pos.face_fa); norminv normal inverse cumulative distribution function; in case of hr or fa equal to 0 or 1, use 1/(2N) for 0 and (1 - 1/(2N)) for 1; N total number of trials tfmri_rec_all_beh_pos.face_dprime, tfmri_rec_all_beh_posface_dprime
Query tfmri_rec_all_beh_neutface_pr Float Recommended Corrected accuracy for neutral faces computed as tfmri_rec_all_beh_old.neut.face_hr-tfmri_rec_all_beh_new.neut.face_fa tfmri_rec_all_beh_neut.face_pr
Query tfmri_rec_all_beh_neutface_br Float Recommended Response bias for neutral faces computed as (tfmri_rec_all_beh_new.neut.face_fa/(1-(tfmri_rec_all_beh_old.neut.face_hr - tfmri_rec_all_beh_new.neut.face_fa))) - 0.5 tfmri_rec_all_beh_neut.face_br
Query tfmri_rec_all_beh_neutf_dp Float Recommended D-prime computed as norminv(tfmri_rec_all_beh_old.pos.face_hr) - norminv(tfmri_rec_all_beh_new.pos.face_fa); norminv normal inverse cumulative distribution function; in case of hr or fa equal to 0 or 1, use 1/(2N) for 0 and (1 - 1/(2N)) for 1; N total number of trials tfmri_rec_all_beh_neut.face_dprime, tfmri_rec_all_beh_neutface_dprime
Query tfmri_rec_all_beh_negface_pr Float Recommended Corrected accuracy for negative faces computed as tfmri_rec_all_beh_old.neg.face_hr-tfmri_rec_all_beh_new.neg.face_fa tfmri_rec_all_beh_neg.face_pr
Query tfmri_rec_all_beh_negface_br Float Recommended Response bias for negative faces computed as (tfmri_rec_all_beh_new.neg.face_fa/(1-(tfmri_rec_all_beh_old.neg.face_hr - tfmri_rec_all_beh_new.neg.face_fa))) - 0.5 tfmri_rec_all_beh_neg.face_br
Query tfmri_rec_all_beh_negf_dp Float Recommended D-prime computed as norminv(tfmri_rec_all_beh_old.neg.face_hr) - norminv(tfmri_rec_all_beh_new.neg.face_fa); norminv normal inverse cumulative distribution function; in case of hr or fa equal to 0 or 1, use 1/(2N) for 0 and (1 - 1/(2N)) for 1; N total number of trials tfmri_rec_all_beh_neg.face_dprime, tfmri_rec_all_beh_negface_dprime
Query tfmri_rec_all_beh_place_pr Float Recommended Corrected accuracy for places computed as tfmri_rec_all_beh_old.place_hr-tfmri_rec_all_beh_new.place_fa tfmri_rec_all_beh_place_pr
Query tfmri_rec_all_beh_place_br Float Recommended Response bias for places computed as (tfmri_rec_all_beh_new.place_fa/(1-(tfmri_rec_all_beh_old.place_hr-tfmri_rec_all_beh_new.place_fa))) - 0.5 tfmri_rec_all_beh_place_br
Query tfmri_rec_all_beh_place_dp Float Recommended D-prime computed as norminv(tfmri_rec_all_beh_old.neg.face_hr) - norminv(tfmri_rec_all_beh_new.place_fa); norminv normal inverse cumulative distribution function; in case of hr or fa equal to 0 or 1, use 1/(2N) for 0 and (1 - 1/(2N)) for 1; N total number of trials tfmri_rec_all_beh_place_dprime
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.