NIMH Data Archive (NDA) Neuroimaging Collections

This repository hosts derived neuroimaging data (.fz/.dz) from multiple projects in the National Institute of Mental Health Data Archive (NDA), spanning prenatal development, infancy, childhood/adolescence, and adult psychiatric disorders. All datasets here are derived files only; access to raw or restricted-level images and phenotypes requires an approved Data Use Agreement (DUA) from NDA.

Derived files in this repository follow a CC BY-NC-SA license. Underlying data remain governed by NDA policies and each project’s original terms.

For each collection below:

• nda-XXXX.gqi.dz / nda-XXXX.dti.dz: group-level diffusion derivatives
• *.fz: subject-level tractography-ready files
• qc.tsv: basic quality control metrics

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Early Brain Development in Twins (Collection ID: 1974)

Twin designs are critical for teasing apart genetic vs. environmental influences on early brain development and risk for neurodevelopmental and psychiatric disorders. This project focuses on the neonatal period, which has historically been under-sampled in twin imaging work.

Design & current findings

• 100 twin pairs with prenatal ultrasound and neonatal MRI

• Prenatal brain size discordance is similar in monozygotic (MZ) and dizygotic (DZ) twins
• By ~1 month of age, MZ twins show smaller discordance in total brain volume than DZ twins
• Global tissue volumes in neonates are highly heritable, matching findings in older samples
• Gray matter heritability is slightly lower at birth, with density correlations dropping across the first year of life
• White matter volumes show strong heritability, but DTI metrics of specific tracts are much less heritable

Next phase

• Expand the twin cohort and follow children to age 6 with:
  • Structural MRI
  • DTI
  • Developmental assessments
• Aim: clarify how genes and environment jointly shape early brain organization and early psychiatric risk.

Investigator: John Gilmore (UNC Chapel Hill)
Assets in this repo: 459

Download (Linux/macOS — bash)

curl -s https://api.github.com/repos/data-nih/nda/releases/tags/nda-1974 | jq -r '.assets[].browser_download_url' | xargs -n1 -P4 curl -LO

Download (Windows PowerShell 5.x)

(Invoke-RestMethod "https://api.github.com/repos/data-nih/nda/releases/tags/nda-1974").assets | % { Invoke-WebRequest $_.browser_download_url -OutFile (Split-Path $_.browser_download_url -Leaf) }

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Longitudinal MRI Study of Infants at Risk for Autism (IBIS; Collection ID: 19)

This dataset comes from the IBIS Autism Project, part of the Autism Centers of Excellence (ACE) Network, with collaboration across UNC, UW, WU, Yale, and the MNI DCC.

Design

• High-risk infants: younger siblings of children with ASD

• Longitudinal MRI/DTI + behavioral assessments at:

  • 6 months
  • 12 months
  • 24 months
• Multi-site, harmonized protocols across ACE sites

Goals

• Characterize how early brain structure and connectivity develop in infants at elevated genetic risk for ASD
• Seek early biomarkers of autism, supporting earlier detection and intervention
• Link trajectories of structural/white matter development to emerging behavioral phenotypes

Investigator: Joe Piven (UNC Chapel Hill) Assets in this repo: 871

Download (Linux/macOS — bash)

curl -s https://api.github.com/repos/data-nih/nda/releases/tags/nda-19 | jq -r '.assets[].browser_download_url' | xargs -n1 -P4 curl -LO

Download (Windows PowerShell 5.x)

(Invoke-RestMethod "https://api.github.com/repos/data-nih/nda/releases/tags/nda-19").assets | % { Invoke-WebRequest $_.browser_download_url -OutFile (Split-Path $_.browser_download_url -Leaf) }

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Fetal Programming of the Newborn and Infant Human Brain (Collection ID: 1890)

A prospective, longitudinal follow-up of children whose mothers participated in an NIH pregnancy study focused on biological and behavioral processes.

Design & focus

• Population-based cohort followed from intrauterine life through birth and infancy
• Serial maternal–placental–fetal endocrine and immune/inflammatory measures during pregnancy
• Newborn and infant brain imaging linked to these prenatal exposures

Goals

• Determine how prenatal environmental factors (hormonal, immune, inflammatory) shape early brain development
• Elucidate pathways from prenatal exposures to later neurodevelopmental and psychiatric outcomes

Investigators: Claudia Buss, Pathik D. Wadhwa (UC Irvine) Assets in this repo: 87

Download (Linux/macOS — bash)

curl -s https://api.github.com/repos/data-nih/nda/releases/tags/nda-1890 | jq -r '.assets[].browser_download_url' | xargs -n1 -P4 curl -LO

Download (Windows PowerShell 5.x)

(Invoke-RestMethod "https://api.github.com/repos/data-nih/nda/releases/tags/nda-1890").assets | % { Invoke-WebRequest $_.browser_download_url -OutFile (Split-Path $_.browser_download_url -Leaf) }

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Longitudinal Neuroimaging and Neurocognitive Assessment Across the Schizophrenia Spectrum (Collection ID: 3445)

This study uses Schizotypal Personality Disorder (SPD) as an intermediate SZ-spectrum phenotype to understand risk and protective factors across the schizophrenia spectrum, without the confounds of chronic antipsychotic treatment or hospitalization.

Participants (18–40 yrs)

• 80 Healthy Controls (no Axis I or personality disorders)
• 80 SPD (unmedicated, no Axis I disorders)
• 80 early-onset SZ (first 2 years of illness)
• Timepoints: baseline, 9-month, 18-month

Multimodal imaging

• Structural MRI
• DTI
• Resting-state fMRI
• Task fMRI (nonverbal working memory at baseline and 18 months)

Assessments & analysis

• Neurocognitive and clinical assessments at all timepoints
• Dynamic causal modeling (DCM) for frontotemporal circuitry
• Machine learning to integrate multimodal imaging + cognition + clinical features

Objectives

• Map trajectories of frontotemporal abnormalities across SZ-spectrum groups
• Track longitudinal evolution of cognition, symptoms, and functioning
• Identify combinations of neural and behavioral factors that confer risk vs. resilience

Investigator: Erin Hazlett (Icahn School of Medicine at Mount Sinai) Assets in this repo: 211

Download (Linux/macOS — bash)

curl -s https://api.github.com/repos/data-nih/nda/releases/tags/nda-3445 | jq -r '.assets[].browser_download_url' | xargs -n1 -P4 curl -LO

Download (Windows PowerShell 5.x)

(Invoke-RestMethod "https://api.github.com/repos/data-nih/nda/releases/tags/nda-3445").assets | % { Invoke-WebRequest $_.browser_download_url -OutFile (Split-Path $_.browser_download_url -Leaf) }

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Mechanisms Underlying Resilience to Neighborhood Disadvantage (Collection ID: 2818)

Not all youth in disadvantaged neighborhoods develop psychopathology. This project focuses on those who show adaptive competence, aiming to uncover multilevel pathways that promote resilience.

Participants

• 500 adolescent twin pairs (ages 11–16)
• Previously assessed at ages 6–10
• All from modestly-to-severely disadvantaged neighborhoods

Imaging & constructs

• Structural MRI
• DTI
• Resting-state and task-based fMRI

• Focus on:

  • Resilience (good adaptation, minimal psychopathology)
  • Protective processes (family and community supports)

Goals

• Identify neural markers and synergistic networks associated with resilience
• Use genetically informed (twin) design to dissect genetic, epigenetic, and environmental influences
• Test how positive parenting and community resources support normative brain architecture under adversity

Investigator: S. Burt (Michigan State University) Assets in this repo: 564

Download (Linux/macOS — bash)

curl -s https://api.github.com/repos/data-nih/nda/releases/tags/nda-2818 | jq -r '.assets[].browser_download_url' | xargs -n1 -P4 curl -LO

Download (Windows PowerShell 5.x)

(Invoke-RestMethod "https://api.github.com/repos/data-nih/nda/releases/tags/nda-2818").assets | % { Invoke-WebRequest $_.browser_download_url -OutFile (Split-Path $_.browser_download_url -Leaf) }

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Integration of Neural Networks and Attachment in Human Infants (Collection ID: 2690)

This project links maternal caregiving, attachment security, and early brain network development.

Longitudinal design

• Infant scans at 3 and 12 months during natural sleep:

  • Resting-state fMRI
  • DTI

• Mother–infant interactions at 3, 6, and 9 months, including:

  • Structured lab tasks
  • Automated naturalistic home-environment capture

• Attachment at 12 months via the Strange Situation Procedure

Network analysis

• Intra- and inter-network connectivity
• Dynamic, whole-brain, data-driven analytic approaches

Goals

• Trace how caregiving and infant behavior shape evolving brain networks
• Understand pathways from early caregiving to socio-emotional and neural outcomes
• Identify targets for early intervention promoting healthy attachment and network integration

Investigator: Nancy McElwain (University of Illinois at Urbana–Champaign) Assets in this repo: 111

Download (Linux/macOS — bash)

curl -s https://api.github.com/repos/data-nih/nda/releases/tags/nda-2690 | jq -r '.assets[].browser_download_url' | xargs -n1 -P4 curl -LO

Download (Windows PowerShell 5.x)

(Invoke-RestMethod "https://api.github.com/repos/data-nih/nda/releases/tags/nda-2690").assets | % { Invoke-WebRequest $_.browser_download_url -OutFile (Split-Path $_.browser_download_url -Leaf) }

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Cincinnati MR Imaging of Neurodevelopment (C-MIND; Collection ID: 2329)

Part of the Pediatric Functional Neuroimaging Research Network, led by Cincinnati Children’s Hospital Medical Center with partners at LONI (USC), UCLA, Children’s Hospital of Pittsburgh, and the University of Michigan.

Aims

• Standardize recruitment, scanning, and processing protocols across pediatric sites
• Characterize brain development from infancy through adolescence

Imaging

• 3D T1- and T2-weighted anatomical scans
• BOLD-fMRI
• DTI
• ASL perfusion
• A concurrent ASL/BOLD-fMRI dataset for neurovascular coupling

Cohort

• 200 typically developing children (cross-sectional)

• Longitudinal subsets:

  • ~40 infants/toddlers (0–3 years)
  • ~30 children (7–9 years)

Focus

• Maturation of white/gray matter, structural/functional connectivity
• Neurovascular coupling and its relationship to cognition and behavior

Investigators: Scott Holland, Jennifer Vannest (CCHMC) Assets in this repo: 567

Download (Linux/macOS — bash)

curl -s https://api.github.com/repos/data-nih/nda/releases/tags/nda-2329 | jq -r '.assets[].browser_download_url' | xargs -n1 -P4 curl -LO

Download (Windows PowerShell 5.x)

(Invoke-RestMethod "https://api.github.com/repos/data-nih/nda/releases/tags/nda-2329").assets | % { Invoke-WebRequest $_.browser_download_url -OutFile (Split-Path $_.browser_download_url -Leaf) }

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Integrity and Dynamic Processing Efficiency of Networks in ASD (Collection ID: 2285)

This study integrates fcMRI, DTI, and MEG to understand network-level abnormalities in Autism Spectrum Disorders (ASD).

Participants

• 60 adolescents with ASD
• 60 matched typically developing controls

Methods

• fMRI during lexical-semantic decision to define nodes in a VLSEM circuit:

  • Visual, Lexico-Semantic, Executive, Motor components
• DTI to measure structural connections among VLSEM nodes
• MEG to examine temporal dynamics and processing efficiency

Goals

• Identify and characterize the VLSEM network in ASD
• Combine structural, functional, and dynamic measures to map how circuit-level disruptions relate to cognitive and socio-communicative impairments

Investigator: Ralph-Axel Mueller (San Diego State University) Assets in this repo: 145

Download (Linux/macOS — bash)

curl -s https://api.github.com/repos/data-nih/nda/releases/tags/nda-2285 | jq -r '.assets[].browser_download_url' | xargs -n1 -P4 curl -LO

Download (Windows PowerShell 5.x)

(Invoke-RestMethod "https://api.github.com/repos/data-nih/nda/releases/tags/nda-2285").assets | % { Invoke-WebRequest $_.browser_download_url -OutFile (Split-Path $_.browser_download_url -Leaf) }

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Taste Reward Circuits and Prediction Error in Eating Disorders (Collection ID: 2138)

An RDoC-inspired study of anorexia nervosa (AN) and bulimia nervosa (BN) using Prediction Error as the organizing construct.

Participants

• Adolescents and young adults (16–29 years), at high risk for severe ED outcomes

Aims

1. Functional reward circuits (fMRI)

   • Taste-reward prediction error responses in:

     • Anteroventral striatum
     • Insula
     • Anterior cingulate cortex (ACC)

   • Hypothesis: lower BMI associates with heightened ACC responses to reward-predicting cues.

2. Structural MRI & DTI

   • Quantify gray/white matter volumes and white matter integrity
   • Hypothesis: severe ED behaviors relate to reduced caudate/insula volumes and altered connectivity.

3. RDoC-based clustering

   • Cluster individuals by prediction-error signatures, comparing to DSM categories
   • Hypothesis: prediction-error profiles better organize ED-relevant behaviors than diagnoses alone.

Investigator: Joel Stoddard (University of Colorado) Assets in this repo: 67

Download (Linux/macOS — bash)

curl -s https://api.github.com/repos/data-nih/nda/releases/tags/nda-2138 | jq -r '.assets[].browser_download_url' | xargs -n1 -P4 curl -LO

Download (Windows PowerShell 5.x)

(Invoke-RestMethod "https://api.github.com/repos/data-nih/nda/releases/tags/nda-2138").assets | % { Invoke-WebRequest $_.browser_download_url -OutFile (Split-Path $_.browser_download_url -Leaf) }

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Effects of Poverty on Affective Development (Collection ID: 2106)

A multi-level, longitudinal study of how poverty-related stress becomes biologically embedded and increases risk for anxiety and depression.

Sample

• Teens drawn from the Fragile Families and Child Wellbeing Study (FFCWS)
• Rich developmental data from birth to age 15, with follow-up at age 17
• Predominantly low-income families

Assessments at age 15

• fMRI: emotional faces tasks targeting amygdala–vmPFC circuitry
• DTI: structural connectivity
• HPA axis: cortisol and DHEA responses to stress
• Cognitive/behavioral tasks (attention bias, etc.)
• Self- and parent-report measures of negative affect, anxiety, and depression

Goals

• Understand how chronic exposure to danger, conflict, instability, and neglect alters:

  • HPA axis regulation
  • Amygdala reactivity and prefrontal regulation

• Map pathways from poverty to affective psychopathology, using the rich FFCWS context.

Investigator: Christopher Monk (University of Michigan) Assets in this repo: 385

Download (Linux/macOS — bash)

curl -s https://api.github.com/repos/data-nih/nda/releases/tags/nda-2106 | jq -r '.assets[].browser_download_url' | xargs -n1 -P4 curl -LO

Download (Windows PowerShell 5.x)

(Invoke-RestMethod "https://api.github.com/repos/data-nih/nda/releases/tags/nda-2106").assets | % { Invoke-WebRequest $_.browser_download_url -OutFile (Split-Path $_.browser_download_url -Leaf) }

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Multidimensional Investigation of Cognitive Control Deficits in Psychopathology (Collection ID: 2102)

This project investigates psychotic spectrum disorders (PSD)—schizophrenia, schizoaffective disorder, bipolar disorder with psychotic features—through the lens of cognitive control impairments, which strongly predict real-world functioning yet remain hard to treat.

Participants

• ~175 PSD patients, continuously recruited

Data

• Extensive clinical and cognitive batteries

• Multimodal neuroimaging:

  • Task and resting-state fMRI
  • DTI for white matter integrity/connectivity
• Cognitive control tasks with strong ecological relevance

Analysis & goals

• Derive neurophysiologically based cluster metrics indexing circuit-level pathology in the cognitive control network (dmPFC, lateral PFC, caudate)
• Use k-means clustering and cross-validation to define biologically meaningful PSD subgroups

• Examine relationships between:

  • Neurophysiological profiles
  • Genetic variation (SNPs, CNVs in dopamine, glutamate, GABA, synaptic pathways)
  • Cognitive control and functional outcomes

Investigator: Andrew Robert Mayer (Mind Research Network) Assets in this repo: 183

Download (Linux/macOS — bash)

curl -s https://api.github.com/repos/data-nih/nda/releases/tags/nda-2102 | jq -r '.assets[].browser_download_url' | xargs -n1 -P4 curl -LO

Download (Windows PowerShell 5.x)

(Invoke-RestMethod "https://api.github.com/repos/data-nih/nda/releases/tags/nda-2102").assets | % { Invoke-WebRequest $_.browser_download_url -OutFile (Split-Path $_.browser_download_url -Leaf) }

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2/3 – Social Processes Initiative in Neurobiology of the Schizophrenia(s) (Collection ID: 2098)

An RDoC-driven project targeting social cognitive (SCog) impairments across Schizophrenia Spectrum Disorders (SSDs), from healthy controls through full illness.

Approach

• Structural MRI to examine gray matter morphology and network topology
• DTI to map white matter circuits supporting SCog processes
• Resting and task-based fMRI to measure circuit function
• Partial Least Squares (PLS) and other multivariate tools to relate brain structure, function, and behavior

Goals

• Characterize abnormal brain–behavior relationships in SCog domains across the SZ spectrum
• Build an RDoC-aligned matrix mapping SCog constructs from normal variation to severe impairment
• Identify neural circuitry that could be targeted to improve social functioning in SSDs

Investigators: Anil K. Malhotra, Aristotle Voineskos, Robert W. Buchanan Organization: The Feinstein Institute for Medical Research Assets in this repo: 899

Download (Linux/macOS — bash)

curl -s https://api.github.com/repos/data-nih/nda/releases/tags/nda-2098 | jq -r '.assets[].browser_download_url' | xargs -n1 -P4 curl -LO

Download (Windows PowerShell 5.x)

(Invoke-RestMethod "https://api.github.com/repos/data-nih/nda/releases/tags/nda-2098").assets | % { Invoke-WebRequest $_.browser_download_url -OutFile (Split-Path $_.browser_download_url -Leaf) }

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Multimodal Developmental Neurogenetics of Females with ASD (Collection ID: 2021)

A deep, multimodal investigation of sex differences in ASD, addressing the male–female prevalence gap with a sex-balanced cohort.

Cohort

• 125 ASD participants
• 125 typically developing controls
• Unaffected siblings
• Parental genotyping for family-based analyses

Data types

• Behavioral phenotyping across multiple domains

• Brain imaging:

  • Structural MRI
  • DTI
  • Task and resting-state fMRI
  • EEG

• Genetics:

  • CNV
  • SNV

Goals

• Identify sex-specific differences in brain structure, function, connectivity, and timing
• Relate CNVs/SNVs to brain phenotypes in ASD vs. TD groups
• Use network-based approaches (e.g., iWGCNA) to integrate brain, behavior, and genetics, addressing ASD heterogeneity

Investigator: Kevin Pelphrey (University of Virginia) Assets in this repo: 243

Download (Linux/macOS — bash)

curl -s https://api.github.com/repos/data-nih/nda/releases/tags/nda-2021 | jq -r '.assets[].browser_download_url' | xargs -n1 -P4 curl -LO

Download (Windows PowerShell 5.x)

(Invoke-RestMethod "https://api.github.com/repos/data-nih/nda/releases/tags/nda-2021").assets | % { Invoke-WebRequest $_.browser_download_url -OutFile (Split-Path $_.browser_download_url -Leaf) }

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Data Access and Licensing Notes

For all collections in data-nih/nda:

• .fz/.dz files are shared under Creative Commons Attribution–NonCommercial–ShareAlike (CC BY-NC-SA).
• Access to .sz files and structural images requires a Data Use Agreement (DUA) approved by the NDA Data Use Permission Group. These must be requested directly through the NIMH Data Archive.

• When publishing work that uses these derivatives, please:

  • Cite the original NDA Collection and its primary publications
  • Acknowledge the NIMH Data Archive (NDA)

  • Optionally add:

    “Derived imaging files were curated via the Pittsburgh Fiber Data Hub (data-nih/nda).”

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© 2025 LabSolver / Pittsburgh Fiber Data Hub. Source datasets © respective investigators and the National Institute of Mental Health Data Archive (NDA). All .fz outputs in this repository follow CC BY-NC-SA, and use of underlying NDA data must follow NDA policies and DUAs.