Reset Password

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.

Warning Notice

This is a U.S. Government computer system, which may be accessed and used only for authorized Government business by authorized personnel. Unauthorized access or use of this computer system may subject violators to criminal, civil, and/or administrative action.

All information on this computer system may be intercepted, recorded, read, copied, and disclosed by and to authorized personnel for official purposes, including criminal investigations. Such information includes sensitive data encrypted to comply with confidentiality and privacy requirements. Access or use of this computer system by any person, whether authorized or unauthorized, constitutes consent to these terms. There is no right of privacy in this system.

You have logged in with a temporary password. Please update your password. Passwords must contain 8 or more characters and must contain at least 3 of the following types of characters:

Subscribe to our mailing list

Mailing List(s)
Email Format

You are now leaving the National Database for Autism Research (NDAR) web site to go to:

Click on the address above if the page does not change within 10 seconds.


NDAR is not responsible for the content of this external site and does not monitor other web sites for accuracy.

Selected Filters
No filters selected

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

Value Range
Data Structures with shared data
No filters have been selected

1 Numbers reported are subjects by age
New Trial
New Project

Format should be in the following format: Activity Code, Institute Abbreviation, and Serial Number. Grant Type, Support Year, and Suffix should be excluded. For example, grant 1R01MH123456-01A1 should be entered R01MH123456

Please select an experiment type below

New Documentation

Please enter the name of the data structure to search or if your definition does not exist, please upload that definition so that it can be appropriately defined for submission. Multiple data structures may be associated with a single Data Expected entry. Please add only one data structure per assessment.

Please provide a reason for the requested submission exemption and the
time-frame during which the exemption will be active.

Collection Owners and those with Collection Administrator permission, may edit a collection. The following is currently available for Edit on this page:


Title, investigators, and Collection Description may be edited along with the Collection Phase. For Collection Phase, the options Pre-enrollment, Enrollment, and Completed can be chosen allowing the Collection Owner to indicate the stage of data collection.

Funding Source

The ability to associate the funding source for the project is provided. For NIH funded grants, linkage to Project Reporter information (e.g. R01MH123456) is supported. Projects funded by others, including the URL of the project, are listed. Non NIH funded projects will become available here to link that data with the appropriate funding agency.

Supporting Documentation

Any documents related to the project may be uploaded clarifying the data or acquisition methods used may be uploaded and made available here. The default is to share these documents to the general public. An option to share only to qualified Researchers is also an option.

Clinical Trials

For clinical trials, the option to link to the clinical trial in clinicaltrials.gov is optionally provided.

Collection Summary Collection Charts
Collection Title Collection Investigators Collection Description
The Neural Substrates of Higher-Level Learning in Autism
Marjorie Solomon 
Individuals with ASD display a unique pattern of abilities and disabilities in learning and memory. They exhibit intact lower-level learning of items, facts, details, and routines. However, they manifest impairments in higherlevel learning involving abstraction, problem solving, using information that must be organized with selfgenerated conceptual schemas, and generalizing learning. This uneven and situation-focused learning profile has a profound impact on the academic, social, and adaptive functioning of those with ASD. Furthermore, while consistent with other neurocognitive theories of ASD, a learning-based approach offers clearer links to animal and computational model systems, thus enhancing its potential to illuminate pathophysiological mechanisms. In this application, I attempt to clarify the neural mechanisms underlying higher-level learning deficits, and help identify their precise effects on the day-to-day functioning of adolescents with ASD. Experiments will include behavioral and fMRI studies in a well-characterized group of adolescents aged 12-17 years, 11 months with ASD (n=40), and age, IQ, and gender-matched control participants with typical development (TYP; n=40).The first Aim, investigates the neural circuitry underlying higher-level learning deficits in adolescents with ASD using fMRI and a transitive inference paradigm which includes testing on lower-level trained and higher-level abstracted relationships between stimuli. This Aim employs a rapid eventrelated fMRI study which is interpreted in the context of our recent behavioral study of transitive inference learning in young adults, and two prominent mechanistic learning models. We predict that individuals with ASD will demonstrate reduced frontal functioning and functional connectivity during higher-level inferences. In the second Aim, we investigate how behavioral and neural indices of lower and higher-level learning relate to academic performance, social problem solving, and restricted and repetitive behaviors using regression analyses to examine how reading, writing, math, and social problem solving abilities, and restricted interests and repetitive behaviors, are predicted by neurocogntive measures of abstract reasoning and generalization,and neural indices of transitive inference. This work proposes a new mechanistic model of ASD; attempts to link neurocognition to real life problems; focuses on the understudied adolescent population during a potentially effective window for intervention; advances the search for psychopharmacological, psychosocial, and neural retraining remediation strategies for these individuals who are extremely able, but experience higher-level learning problems that limit their human potential; uses Bayesian state-space quantitative methods to closely examine the emergence of learning; and establishes a conceptual basis for future investigation of generalization of learning in mice through the development of parallel tasks in mouse models of ASD that can be used as preclinical assays for dopaminergic and other pharmacological treatments for cognitive deficits.
Loading Chart...
NIH - Extramural None

R21MH099250-01 The Neural Substrates of Higher-Level Learning in Autism 09/15/2012 05/31/2014 0 71 UNIVERSITY OF CALIFORNIA AT DAVIS $414,260.00

Collection Owners and those with Collection Administrator permission, may edit a collection. The following is currently available for Edit on this page:


To create a new Omics, eye tracking, fMRI, or EEG experiment, press the "+ New Experiment" button. Once an experiment is created, then raw files for these types of experiments should be provided, associating the experiment – through Experiment_ID – with the metadata defined in the experiments interface.

IDNameCreated DateStatusType
297Ovals Transitive Inference Task04/10/2015ApprovedfMRI

Collection Owners and those with Collection Administrator permission, may edit a collection. The following is currently available for Edit on this page:

Shared Data

Data structures with the number of subjects submitted and shared are provided.

Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 3 Clinical Assessments 20
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 4 Clinical Assessments 13
BASC Parent Rating Scale Adolescent Clinical Assessments 65
BASC Self Report Adolescent Clinical Assessments 65
California Verbal Learning Test Clinical Assessments 65
Delis-Kaplan Executive Function System Clinical Assessments 65
Image Imaging 64
Means-Ends Problem Solving Test (MEPS) Revised Clinical Assessments 61
Repetitive Behavior Scale - Revised (RBS-R) (2000) Clinical Assessments 65
Research Subject Clinical Assessments 65
Social Communication Questionnaire (SCQ) - Lifetime Clinical Assessments 64
WASI-2 Clinical Assessments 65
Wechsler Individual Achievement Test Third Edition. Part I Clinical Assessments 65

Collection Owners and those with Collection Administrator permission, may edit a collection. The following is currently available for Edit on this page:


Publications relevant to NDAR data are listed below. Most displayed publications have been associated with the grant within Pubmed. Use the "+ New Publication" button to add new publications. Publications relevant/not relevant to data expected are categorized. Relevant publications are then linked to the underlying data by selecting the Create Study link. Study provides the ability to define cohorts, assign subjects, define outcome measures and lists the study type, data analysis and results. Analyzed data and results are expected in this way.

PubMed IDStudyTitleJournalAuthorsDateStatus
26506585Create StudyAtypical Learning in Autism Spectrum Disorders: A Functional Magnetic Resonance Imaging Study of Transitive Inference.Journal of the American Academy of Child and Adolescent PsychiatrySolomon M, Ragland JD, Niendam TA, Lesh TA, Beck JS, Matter JC, Frank MJ, Carter CSNovember 2015Not Determined
26418313Create StudyClinical and Cognitive Characteristics Associated with Mathematics Problem Solving in Adolescents with Autism Spectrum Disorder.Autism research : official journal of the International Society for Autism ResearchOswald TM, Beck JS, Iosif AM, Mccauley JB, Gilhooly LJ, Matter JC, Solomon MApril 2016Not Determined
23413037Create StudyOxytocin and vasopressin in children and adolescents with autism spectrum disorders: sex differences and associations with symptoms.Autism research : official journal of the International Society for Autism ResearchMiller M, Bales KL, Taylor SL, Yoon J, Hostetler CM, Carter CS, Solomon MApril 2013Not Determined
23239098Create StudyMeasuring changes in social behavior during a social skills intervention for higher-functioning children and adolescents with autism spectrum disorder.Journal of autism and developmental disordersMcMahon CM, Vismara LA, Solomon MAugust 2013Not Determined
21656344Create StudyTransitive inference in adults with autism spectrum disorders.Cognitive, affective & behavioral neuroscienceSolomon M, Frank MJ, Smith AC, Ly S, Carter CSSeptember 2011Not Determined

Relevant Publications
PubMed IDStudyTitleJournalAuthorsDate
No records found.
Data Expected
Data ExpectedTargeted EnrollmentInitial SubmissionSubjects SharedStatus
Research Subject and Pedigree info iconApproved
Behavior Assessment System for Children (BASC) info iconApproved
Social Communication Questionnaire (SCQ) info iconApproved
ADOS info iconApproved
Wechsler Abbreviated Scale of Intelligence (WASI) info iconApproved
Imaging (Structural, fMRI, DTI, PET, microscopy) info iconApproved
Means-Ends Problem Solving Test (MEPS) info iconApproved
Transitive Inference Task info iconApproved
Repetitive Behavior Scale - Revised (RBS-R) info iconApproved
Auditory Verbal Learning Task info iconApproved
Delis-Kaplan Executive Function System (D-KEFS) info iconApproved
Wechsler Individual Achievement Test info iconApproved
Structure not yet defined

Collection Owners and those with Collection Administrator permission, may edit a collection. The following is currently available for Edit on this page:

Associated Studies

Studies that have been defined using data from a Collection are important criteria to determine the value of data shared. The number of subjects column displays the counts from this Collection that are included in a Study, out of the total number of subjects in that study. The Data Use column represents whether or not the study is a primary analysis of the data or a secondary analysis. State indicates whether the study is private or shared with the research community.

Study Name Description Number of Subjects
Collection / Total
Data Use State
Derivation of Brain Structure Volumes from MRI Neuroimages hosted by NDAR using C-PAC pipeline and ANTs An automated pipeline was developed to reference Neuroimages hosted by the National Database for Autism Research (NDAR) and derive volumes for distinct brain structures using Advanced Normalization Tools (ANTs) and the Configurable-Pipeline for the Analysis of Connectomes (C-PAC) platform. This pipeline utilized the ANTs cortical thickness methodology discuessed in "Large-Scale Evaluation of ANTs and Freesurfer Cortical Tchickness Measurements" [http://www.ncbi.nlm.nih.gov/pubmed/24879923] to extract a cortical thickness volume from T1-weighted anatomical MRI data gathered from the NDAR database. This volume was then registered to an stereotaxic-space anatomical template (OASIS-30 Atropos Template) which was acquired from the Mindboggle Project webpage [http://mindboggle.info/data.html]. After registration, the mean cortical thickness was calculated at 31 ROIs on each hemisphere of the cortex and using the Desikan-Killiany-Tourville (DKT-31) cortical labelling protocol [http://mindboggle.info/faq/labels.html] over the OASIS-30 template. **NOTE: This study is ongoing; additional data my be available in the future.** As a result, each subject that was processed has a cortical thickness volume image and a text file with the mean thickness ROIs (in mm) stored in Amazon Web Services (AWS) Simple Storage Service (S3). Additionally, these results were tabulated in an AWS-hosted database (through NDAR) to enable simple, efficient querying and data access. All of the code used to perform this analysis is publicly available on Github [https://github.com/FCP-INDI/ndar-dev]. Additionally, as a computing platform, we developed an Amazon Machine Image (AMI) that comes fully equipped to run this pipeline on any dataset. Using AWS Elastic Cloud Computing (EC2), users can launch our publicly available AMI ("C-PAC with benchmark", AMI ID: "ami-fee34296", N. Virginia region) and run the ANTs cortical thickness pipeline. The AMI is fully compatible with Sun Grid Engine as well; this enables users to perform many pipeline runs in parallel over a cluster-computing framework. 8 / 1540 Secondary Analysis Shared
Revising the Social Communication Questionnaire scoring procedures for Autism Spectrum Disorder and potential Social Communication Disorder In analyzing data from the National Database for Autism Research, we examine revising the Social Communication Questionnaire (SCQ), a commonly used screening instrument for Autism Spectrum Disorder. A combination of Item Response Theory and Mokken scaling techniques were utilized to achieve this and abbreviated scoring of the SCQ is suggested. The psychometric sensitivity of this abbreviated SCQ was examined via bootstrapped Receiver Operator Characteristic (ROC) curve analyses. Additionally, we examined the sensitivity of the abbreviated and total scaled SCQ as it relates to a potential diagnosis of Social (Pragmatic) Communication Disorder (SCD). As SCD is a new disorder introduced with the fifth edition of the Diagnostic and Statistical Manual (DSM-5), we identified individuals with potential diagnosis of SCD among individuals with ASD via mixture modeling techniques using the same NDAR data. These analyses revealed two classes or clusters of individuals when considering the two core areas of impairment among individuals with ASD: social communication and restricted, repetitive patterns of behavior. 2 / 1021 Secondary Analysis Shared
* Data not on individual level