Project Overview

The SIMON Dataset is a unique longitudinal neuroimaging dataset from a single healthy ambidextrous male, aged 29 to 46 years, who participated in 73 imaging sessions across multiple sites and scanner models. This dataset serves as a valuable resource for studying cross-site and cross-protocol variability in neuroimaging data and includes a wide variety of imaging modalities.

Data were partially acquired through the Canadian Dementia Imaging Protocol (CDIP), and new data will continue to be added as the study progresses.

Available Data

Each imaging session includes at least a T1-weighted anatomical scan. Additional modalities vary across sessions and may include:

• T1-, T2-, and PD-weighted images
• T2*-weighted images
• Diffusion-weighted imaging (DTI)
• Resting-state fMRI
• Susceptibility imaging
• Arterial spin labeling (ASL)

Phenotypic Data:

• Demographic information (age, session number, session date)
• Available in SIMON_pheno.csv

Data Access

Data are hosted on an Amazon Web Services (AWS) S3 bucket and can be accessed using HTTP-based tools:

• Access SIMON Raw Data
• Access SIMON Preprocessed Functional MRI Data

Instructions for Accessing Data via Cyberduck:

1. Open Cyberduck and select Open Connection.

2. Set the application protocol to S3 (Amazon Simple Storage Service).

3. Server: s3.amazonaws.com

4. Check Anonymous Login.

5. Expand More Options and set the Path to either:

   • fcp-indi/data/Projects/INDI/SIMON/rawdata
   • fcp-indi/data/Projects/INDI/SIMON/derivatives

6. Click Connect.

Note: Wildcards cannot be used for batch downloads. Use tools like wget or curl for direct downloads using exact file names.

Personnel

Principal Investigator:

• Simon Duchesne, Ph.D., CERVO Brain Research Centre, Quebec, Canada

Senior Personnel and Collaborators (Alphabetical):

• AmanPreet Badhwar, Ph.D., CRIUGM, Quebec, Canada
• Desiree Lussier-Levesque, Ph.D., CRIUGM, Quebec, Canada

For inquiries, please contact: info@medics.ulaval.ca

Data Sharing License

• Attribution-ShareAlike International (CC BY-SA)

Funding Acknowledgment

Please cite the following organizations and publications in any work utilizing this data:

• Duchesne S, Chouinard I, Potvin O et al. The Canadian Dementia Imaging Protocol: Harmonizing National Cohorts. J Magn Reson Imaging. 2019; 49:456-465.

The SIMON dataset has been made possible through contributions from the following organizations:

• CIMA-Q (www.cima-q.ca)
• Canadian Consortium on Neurodegeneration in Aging (CCNA) (www.ccna-ccnv.ca)
• Ontario Neurodegenerative Disease Research Initiative (ONDRI) (ondri.ca)
• Alzheimer’s Society of Canada (#13-32)
• Canadian Institutes for Health Research (#117121)
• Fonds de recherche du Québec – Santé / Pfizer-FRQS Innovation Fund (#25262, #27239)
• Ontario Brain Institute

Additional support has been provided by the Cuban Neuroscience Center and the University of Electronic Science and Technology of China under the Tri-national Axis on Normal and Pathological Aging program.

Publications Using This Dataset

1. Duchesne S, Dieumegarde L, Chouinard I, Farokhian F, Potvin O (Submitted). Multi-contrast magnetic resonance imaging series of a single human volunteer over 15+ years.
2. Duchesne S, Chouinard I, Potvin O et al. The Canadian Dementia Imaging Protocol: Harmonizing National Cohorts. J Magn Reson Imaging. 2019; 49:456-465.

This dataset was collected at the Phyllis Green and Randolph Cōwen Institute for Pediatric Neuroscience (IPN) at the New York University (NYU) School of Medicine. It represents the initial release of a larger, ongoing project aimed at characterizing normative brain connectivity across development and into adulthood. The current release includes data from 49 psychiatrically screened, neurotypical adults (ages 6–55 years in the broader IPN project) and provides matched demographic and intelligence (IQ) measures.

Each participant contributed at least one 6-minute resting-state fMRI (R-fMRI) scan, a high-resolution T1-weighted anatomical image, and two 64-direction diffusion tensor imaging (DTI) scans. Most participants have two R-fMRI runs collected within one session, separated by less than one hour — with Rest_1 always preceding Rest_2.

Future releases of this dataset will extend to include child and adolescent cohorts, clinical populations, and expanded phenotypic data to support lifespan and psychiatric connectivity research.

⚠️ Important: Some participants in this dataset also appear in the NewYork_a dataset (1000 Functional Connectomes classic collection) and NYU_Cocaine dataset (INDI retrospective release).
To prevent sample duplication, these datasets should not be combined.

Overview

• Dataset name: NYU Institute for Pediatric Neuroscience (IPN)
• Institution: NYU School of Medicine, New York, NY, USA
• Sample: 49 psychiatrically neurotypical adults
• Age range: 6–55 years (adults in this release)
• Modalities:
  • Resting-state fMRI (R-fMRI, 1–2 runs per participant)
  • High-resolution T1-weighted MPRAGE
  • Two 64-direction DTI scans
• Phenotypic data: Age, gender, and IQ (Verbal, Performance, Composite; WASI)
• License: Creative Commons Attribution–NonCommercial

Scan Description

Participants were instructed to remain still with eyes open during the resting-state scans.

Downloads

Data are hosted via the NITRC portal.
Users must register for an account and request access to the 1000 Functional Connectomes Project group.

Usage Agreement

This dataset is released under the Creative Commons Attribution–NonCommercial License.
Users are free to share and adapt the material for non-commercial research purposes, with proper attribution.

Please include the following acknowledgment in any resulting publication:

“Financial support for the data used in this project was partially provided by grants from the NIMH (R01MH083246), Autism Speaks, the Stavros Niarchos Foundation, the Leon Levy Foundation, and the endowment provided by Phyllis Green and Randolph Cōwen.”

Citation

NYU Institute for Pediatric Neuroscience (IPN) Adult Resting-State and DTI Dataset.
Phyllis Green and Randolph Cōwen Institute for Pediatric Neuroscience,
New York University School of Medicine, USA.

Source

• Dataset page:
  http://fcon_1000.projects.nitrc.org/indi/retro/nyu_ipn.html
• INDI / 1000 Functional Connectomes Project:
  https://www.nitrc.org/projects/fcon_1000/

© NYU Institute for Pediatric Neuroscience. Prepared for redistribution under data-indi/nyu-ipn by the Pittsburgh Fiber Data Hub.

The NKI/Rockland Sample is a large-scale, openly shared, and phenotypically rich neuroimaging resource designed to advance discovery science in human brain research. It includes multimodal MRI, diffusion imaging, and extensive psychiatric, cognitive, and behavioral assessments collected from individuals aged 4 to 85 years. The project’s central mission is to link brain structure and function with behavioral and clinical variation across the lifespan.

All participants undergo semi-structured psychiatric interviews and a comprehensive battery of neuropsychological and behavioral assessments to provide deep phenotyping for studying brain–behavior relationships. Data are prospectively released to the scientific community — typically with a randomized 2–8 week delay — ensuring that the dataset grows continuously while remaining accessible for collaborative research.

Each participant’s imaging protocol includes:

• 10-minute resting-state fMRI (R-fMRI)
• 6-direction diffusion tensor imaging (DTI)
• 64-direction diffusion tensor imaging (2 mm isotropic)
• High-resolution MPRAGE anatomical scan
• Short-sequence MPRAGE
• T2-weighted anatomical scan
• Comprehensive behavioral and cognitive assessments

The imaging sequences were adapted from the Brain Genomics Superstruct Project protocol (courtesy of Randy Buckner) to enable cross-site comparability in large-scale population studies.

Overview

• Dataset name: Nathan Kline Institute (NKI) / Rockland Sample
• Institution: Nathan S. Kline Institute for Psychiatric Research (NKI), Orangeburg, NY, USA
• Principal Investigators: F. Xavier Castellanos, Bennett Leventhal, Michael Milham
• Project Coordinator: Kate Nooner
• Sample: 4–85 years old, community-ascertained participants
• Modalities: R-fMRI, DTI (6- and 64-direction), T1/T2 anatomical MRI
• Phenotyping: Psychiatric, cognitive, and behavioral assessments
• Data Release Schedule: 5–10 new individuals per week (completed August 15, 2011)
• License: Creative Commons Attribution–NonCommercial

Data Characteristics

• Open longitudinal acquisition: Ongoing releases provided during active data collection.
• Comprehensive multimodal imaging: High-quality R-fMRI, DTI, and structural scans.
• Extensive phenotyping: Diagnostic interviews and standardized behavioral measures.
• Wide age range: Enables developmental and lifespan analyses.
• Community-based sampling: Recruitment designed for broad demographic representation.

Access and Download

Data are hosted via the Neuroimaging Tools and Resources Clearinghouse (NITRC) and distributed weekly in DICOM and NIfTI formats.

Total number of datasets: 207
Next release: Completed as of August 15, 2011

To access data:

1. Register for a NITRC account.
2. Request access to the 1000 Functional Connectomes Project (INDI group).
3. After approval (within 1 business day), download via the NITRC portal.

Usage Agreement

The NKI/Rockland Sample is released under the Creative Commons Attribution–NonCommercial License (CC BY-NC).
Users may share and analyze the data for non-commercial research, provided proper acknowledgment is given.

Disclaimer:
Since data are shared prospectively, acquisition issues (e.g., motion, equipment failure) may occur. All data, including lower-quality scans, are provided for transparency and completeness. Users are responsible for quality control in their analyses.

Funding and Support

Primary Support:

• New York State Office of Mental Health
• Research Foundation for Mental Hygiene
• NIH Grant P50 MH086385-S1

Additional Support:

• NKI Center for Advanced Brain Imaging (CABI)
• Brain Research Foundation (Chicago, IL)
• Stavros Niarchos Foundation

Team Members:
Melissa Benedict, Bharat Biswal, Barbara Coffey, Stan Colcombe, David Guilfoyle, David Gutman, Harold S. Koplewicz, Matthew Hoptman, Dan Javitt, Larry Maayan, Maarten Mennes, Kate Nooner, Nunzio Pomara

Citation

Castellanos F.X., Leventhal B., Milham M.P., et al.
Nathan Kline Institute (NKI) / Rockland Sample.
Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA.

Source

• Dataset page:
  http://fcon_1000.projects.nitrc.org/indi/enhanced/nki_rs.html
• INDI / 1000 Functional Connectomes Project:
  https://www.nitrc.org/projects/fcon_1000/

© Nathan Kline Institute for Psychiatric Research.
Prepared for redistribution under data-indi/nki-rockland by the Pittsburgh Fiber Data Hub.

The Enhanced NKI-Rockland Sample (NKI-RS) represents an expanded, community-based neuroimaging initiative designed to map brain development, maturation, and aging across the human lifespan (ages 6–85 years). Building upon the original NKI-RS project, this enhanced version combines state-of-the-art multiband imaging, deep phenotyping, and open-access data sharing to provide one of the most comprehensive resources for studying individual differences in brain structure and function.

The Multiband Imaging Test–Retest Pilot Dataset served as the preliminary phase for the enhanced NKI-RS project. It was specifically designed to evaluate the reliability and reproducibility of advanced multiband resting-state fMRI (R-fMRI) and diffusion tensor imaging (DTI) protocols before their implementation in the full-scale 1,000-participant study. Participants were primarily drawn from the original NKI-RS cohort, with corresponding psychiatric and phenotypic data available (individuals were not excluded for clinical history).

The pilot dataset includes repeated R-fMRI and DTI sessions, as well as task-based calibration scans for assessing image quality, vascular reactivity, and motion effects:

• Visual checkerboard stimulation (contrast-to-noise calibration)
• Breath-holding task (vascular responsiveness)
• Eye-movement calibration (motion-related artifact detection)

Overview

• Dataset name: Enhanced NKI-RS – Multiband Imaging Test–Retest Pilot Dataset
• Institution: Nathan Kline Institute for Psychiatric Research (NKI), Orangeburg, NY, USA
• Principal Investigator: Michael Milham
• DOI: 10.15387/fcp_indi.corr.nki1
• Sample: Adults from the original NKI-RS cohort
• Modalities: R-fMRI, multiband R-fMRI, DTI, task-based fMRI (checkerboard, breath-hold, eye-movement)
• Purpose: Evaluate test–retest reliability of multiband imaging protocols

Imaging Protocol

Repeated scans (test–retest):

Single-acquisition scans:

Each task includes stimulus design files and execution scripts (Vision Egg format) to reproduce acquisition conditions.

Important Notes for Multiband Data Users

• The short TR in multiband fMRI increases temporal resolution but changes temporal autocorrelation properties, which must be corrected during analysis.
• Spatial smoothness can vary non-uniformly; standard Gaussian Random Field–based cluster corrections may be unsuitable.
• Slice timing correction requires custom timing information due to simultaneous multi-slice excitation.

Researchers should consult preprocessing recommendations from Christian Beckmann and Steve Smith (HCP collaboration) when analyzing these data.

Phenotyping and Data Infrastructure

The enhanced NKI-RS includes extensive behavioral, cognitive, and clinical phenotyping, coordinated through the COllaborative Informatics and Neuroimaging Suite (COINS) platform. This system integrates all phenotypic and imaging data into a unified, queryable database.
To ensure representative sampling, the project employs community-ascertained recruitment from Rockland County, NY, using demographic stratification to mirror U.S. census distributions.

Downloads

Data are distributed via the Neuroimaging Tools and Resources Clearinghouse (NITRC).

Usage Agreement

This dataset is made available under the Creative Commons Attribution–NonCommercial License (CC BY-NC).
Users may share and adapt the material for non-commercial research with proper attribution.

Disclaimer:
All scans are provided as-is. It is the user’s responsibility to perform appropriate quality control and determine inclusion for analysis.

Funding and Acknowledgments

Primary Funding:

• NIMH BRAINS R01MH094639-01 (PI Milham)
• New York State Office of Mental Health and Research Foundation for Mental Hygiene
• Child Mind Institute (1FDN2012-1)
• Center for the Developing Brain, Child Mind Institute
• NIMH R01MH081218, R01MH083246, R21MH084126
• NKI Center for Advanced Brain Imaging (CABI)
• Brain Research Foundation, Chicago
• Stavros Niarchos Foundation

Core Team Leadership:
Michael Milham, Bennett Leventhal, F. Xavier Castellanos, Kate Nooner, Russ Tobe, Stan Colcombe

Technical & Imaging Support:
Cathy Hu, Raj Sangoi, Steve Zavitz, Cameron Craddock, Qingyang Li, Brian Cheung, Ranjit Khanuja, David Lewis, Chao-Gan Yan

Collaborations:
Special thanks to CMRR, University of Minnesota (Kamil Ugurbil, Eddie Auerbach, Junquian Gordon Xu, Steen Moeller) for providing multiband EPI sequences and reconstruction algorithms.

Citation

Milham M., Colcombe S., Castellanos F.X., et al.
Enhanced Nathan Kline Institute–Rockland Sample (NKI-RS) – Multiband Imaging Test–Retest Pilot Dataset.
Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
DOI: 10.15387/fcp_indi.corr.nki1

Source

• Dataset page:
  http://fcon_1000.projects.nitrc.org/indi/enhanced/nki_rs.html
• INDI / 1000 Functional Connectomes Project:
  https://www.nitrc.org/projects/fcon_1000/

© Nathan Kline Institute for Psychiatric Research.
Prepared for redistribution under data-indi/nki-rs by the Pittsburgh Fiber Data Hub.

The participants took part in one or two extended protocols: Leipzig Mind-Brain_BodyInteractions (LEMON) and Neuroanatomy & Connectivity Protocol (N&C). The data from LEMON protocol is included in the ‘ses-01’ subfolder; the data from N&C protocol in ‘ses-02’ subfolder.

LEMON focuses on structural imaging. 228 participants were scanned. In addition to the quantitative T1-weighted image (MP2RAGE, from 227 participants), the participants also have a structural T2-weighted image (225), a diffusion-weighted image with 60 directions (228) and a 15-minute eyes-open resting-state session (227) including scans for geometric distortion correction in DWI and rs-fMRI. Updated imaging sequences were introduced into the LEMON protocol after data acquisition for 112 participants. Before the change, a low-resolution 2D FLAIR image was acquired for for radiological screening (111). After the change, 2D FLAIR was replaced with high-resolution 3D SPACE sequence with fluid-attenuated inversion-recovery preparation (116). The second update was a change from a Siemens product Susceptibility-Weighted Imaging (SWI) sequence (109) to an in-house SWI sequence (114). The in-house sequence allows both magnitude and phase data to be stored, enabling offline processing and Quantitative Susceptibility Mapping (QSM).
The N&C protocol focuses on resting-state fMRI data. 199 participants were scanned with this protocol; 109 participants also took part in the LEMON protocol. Structural data was not acquired for the overlapping LEMON participants. For the unique N&C participants, only a T1-weighted and a low-resolution FLAIR image were acquired. Four 15-minute runs of eyes-open resting-state are the main component of N&C; they are complete for 194 participants, three participants have 3 runs, one participant has 2 runs and one participant has a single run. Due to a bug in multiband sequence used in this protocol, the echo time for N&C resting-state is longer than in LEMON — 39.4 ms vs 30 ms.

Forty-five participants have complete imaging data: quantitative T1-weighted, T2-weighted, high-resolution 3D FLAIR, DWI, SWI sequence allowing QSM, and 75 minutes of resting-state. Both gradient-echo and spin-echo field maps are available in both datasets for all EPI-based sequences (rsfMRI and DWI).

Extensive behavioral data was acquired in both protocols. They include trait and state questionnaires, as well as behavioral tasks. Here we only list the tasks and more extensive descriptions are available in the manuscripts.

LEMON QUESTIONNAIRES/TASKS

Cognitive Test Battery
California Verbal Learning Test (CVLT)
Testbatterie zur Aufmerksamkeitsprüfung (TAP: Alertness, Incompatibility, Working Memory)
Trail Making Test (TMT: A, B)
Wortschatztest (WST)
Leistungsprüfungssystem 2 (LPS-2: Subset 3)
Regensburger Wortflüssigkeitstest (RWT: S-Words, Animals,)

Emotion and Personality Test Battery
NEO Five-Factor Inventory (NEO-FFI)
Impulsive Behavior Scale (UPPS)
Behavioral Inhibition and Approach System (BISBAS)
Cognitive Emotion Regulation Questionnaire (CERQ)
Measure of Affective Style (MARS)
Fragebogen zur Sozialen Unterstützung (F-SozU K-22)
The Multidimensional Scale of Perceived Social Support (MSPSS)
Coping Orientations to Problems Experienced (COPE)
Life Orientation Test-Revised (LOT-R)
Perceived Stress Questionnaire (PSQ)
Trier Inventory of Chronic Stress (TICS)
Three-factor eating questionnaire (TFEQ)
Yale Food Addiction Scale (YFAS)
The Trait Emotional Intelligence Questionnaire (TEIQue-SF)
Trait Scale of the State-Trait Anxiety Inventory (STAI)
State-Trait Anger expression Inventory (STAXI)
Toronto-Alexithymia Scale (TAS)
Multidimensional Mood Questionnaire (MDBF)
New York Cognition Questionnaire (NYC-Q)
Future Time perspective (FTP)
Three-factor Eating Questionnaire (FEV)

Physiological measures
Resting-state EEG
Continuous Peripheral Physiological Recordings During rs-fMRI (ECG, pulse, respiration, beat-to-beat blood pressure)
Seated Resting Blood Pressure
Blood Drawing
Anthropometry
Hair Sample

Assessment of Past and Present Psychiatric Symptoms
Standardized Clinical Interview for DSM IV (SCID-I)
Screening for Clinically Relevant Symptoms (HAM-D, BSL-23)
Screening for Alcohol Abuse (AUDIT)
Screening for Substance Abuse

N&C QUESTIONNAIRES

Adult Self Report (ASR)
Goldsmiths Musical Sophistication Index (Gold-MSI)
Internet Addiction Test (IAT)
Involuntary Musical Imagery Scale (IMIS)
Multi-Gender Identity Questionnaire (MGIQ)
Brief Self-Control Scale (SCS)
Short Dark Triad (SD3)
Social Desirability Scale-17 (SDS)
Self-Esteem Scale (SE)
Tuckman Procrastination Scale (TPS)
Varieties of Inner Speech (VISQ)
UPPS-P Impulsive Behavior Scale (UPPS-P)
Attention Control Scale (ACS)
Beck's Depression Inventory-II (BDI)
Boredom Proneness Scale (BP)
Esworth Sleepiness Scale (ESS)
Hospital Anxiety and Depression Scale (HADS)
Multimedia Multitasking Index (MMI)
Mobile Phone Usage (MPU)
Personality Style and Disorder Inventory (PSSI)
Spontaneous and Deliberate Mind-Wandering (S-D-MW)
Short New York Cognition Scale (Short-NYC-Q)
New York Cognition Scale (NYC-Q)
Abbreviated Math Anxiety Scale (AMAS)
Behavioral Inhibition and Approach System (BIS/BAS)
NEO Personality Inventory Revised (NEO-PI-R)
Body Consciousness Questionnaire (BCQ)
Creative achievement questionnaire (CAQ)
Five facets of mindfulness (FFMQ)
Metacognition (MCQ-30)

N&C TASKS

Conjunctive continuous performance task (CCPT)
Emotional task switching (ETS)
Adaptive visual and auditory oddball target detection task (Oddball)
Alternative uses task (AUT)
Remote associates test (RAT)
Synesthesia color picker test (SYN)
Test of creative imagery abilities (TCIA)

This dataset was collected at the State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University (BNU), to investigate how repetition time (TR) influences resting-state fMRI signal quality and connectivity measures. The dataset provides paired resting-state scans acquired at two TRs (0.4 s and 2.0 s) from healthy, college-aged volunteers, alongside anatomical and diffusion data.

Each participant underwent both short and long TR acquisitions within the same session, enabling direct comparisons of temporal sampling effects, functional connectivity stability, and signal-to-noise tradeoffs across acquisition speeds. The dataset also includes 64-direction diffusion tensor imaging (DTI) and a high-resolution MPRAGE anatomical scan (defaced for anonymity).

Data were released incrementally in weekly batches of three to four participants, totaling 28 subjects.

Overview

• Dataset name: Beijing Normal University – Short TR Sample
• Institution: State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
• Principal Investigators: Not specified (BNU Neuroimaging Group)
• Sample: 28 healthy college-aged volunteers
• Modalities: Resting-state fMRI (short and long TR), T1-weighted MRI, 64-direction DTI
• Design: Within-subject comparison of two TR conditions
• License: Creative Commons Attribution–NonCommercial

Imaging Protocol

Participants were instructed to keep their eyes open and remain still during scanning.

Data Availability

Data are distributed through the Neuroimaging Tools and Resources Clearinghouse (NITRC) as part of the 1000 Functional Connectomes Project.
Users must register for a NITRC account and request group access before downloading.

Funding and Acknowledgment

Please include the following acknowledgment in any publication using this dataset:

“Financial support for the data used in this project was provided by grants from the National Natural Science Foundation of China (30770594) and the National High Technology Program of China (863) (2008AA02Z405).”

Usage Agreement

This dataset is distributed under the Creative Commons Attribution–NonCommercial License (CC BY-NC).
Researchers may share and adapt the material for non-commercial use, provided that proper attribution is given.

Citation

Beijing Normal University – Short TR Sample.
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.

Source

• Dataset page:
  http://fcon_1000.projects.nitrc.org/indi/retro/BeijingShortTR.html
• INDI / 1000 Functional Connectomes Project:
  https://www.nitrc.org/projects/fcon_1000/

© Beijing Normal University. Prepared for redistribution under data-indi/beijing-shorttr by the Pittsburgh Fiber Data Hub.