diff --git a/README.md b/README.md index ae50eb1..76a4810 100644 --- a/README.md +++ b/README.md @@ -1,496 +1,174 @@ # multiBrain -A list of brain imaging databases with multiple (e.g., more than 3) scans per subject. Feel free to update the list via 'pull requests'. - -### A single female subject that was scanned for 30 consecutive days. -* Functional reorganization of brain networks across the human menstrual cycle https://doi.org/10.1101/866913 -* Subjects - * N = 1 - * female - * age: 23 years old -* Data - * MRI/fMRI/Behavioral assessments/Endocrine procedures - * The participant underwent daily testing for 30 consecutive days - * Siemens 3T Prisma -* MRI data, code, and daily behavioral assessments will be publicly accessible upon publication. -* https://doi.org/10.1101/866913 - -### A densely sampled longitudinal dataset from healthy infants -* a densely sampled longitudinal dataset with 210 serial MRI scans from 43 healthy infants, with each infant being scheduled to have 7 longitudinal scans at around 1, 3, 6, 9, 12, 18, and 24 mo of age -* https://doi.org/10.1073/pnas.1821523116 -* Subjects - * N = 43 - * males & females - * age range: 1-24 month -* Data - * MRI - * 7 repetitions, at around 1, 3, 6, 9, 12, 18, and 24 mo of age - * Siemens 3T -* Data not open, https://doi.org/10.1073/pnas.1821523116 - -### A large single-participant fMRI dataset for probing brain responses to naturalistic stimuli in space and time -* A large single-participant fMRI dataset for probing brain responses to naturalistic stimuli in space and time -* https://www.biorxiv.org/content/10.1101/687681v1 -* Subjects - * N = 1 - * male - * age range: 27.5 -* Data - * MRI, fMRI - * 22 repetitions, between April 2017 and December 2017 - * Siemens 3T MAGNETOM Prisma -* https://doi.org/10.1101/687681 - -### Travelling Human Phantoms -* A longitudinal human phantom reliability study of multi-center T1-weighted, DTI, and resting state fMRI data -* https://www.sciencedirect.com/science/article/pii/S0925492717302883 -* Subjects - * N = 4 - * male - * age range: 34-59 -* Data - * MRI, dMRI, rsfMRI - * 3/6/6/9 scans on 5 scaners in 3 years - * various scanners -* Hawco, Colin, et al. "A longitudinal human phantom reliability study of multi-center T1-weighted, DTI, and resting state fMRI data." Psychiatry Research: Neuroimaging 282 (2018): 134-142. - -### Decoded Neurofeedback (DecNef) Project -* TRAVELING SUBJECTS DATA -* https://bicr-resource.atr.jp/decnefpro/ -* Subjects - * N = 9 - * male - * age range: 24–32 y; mean age: 27 ± 2.6 y -* Data - * MRI, rsfMRI - * scanned at each of 12 sites - * GE, SIEMENS, Philips -* Yamashita, Ayumu, et al. "Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias." PLOS Biology 17.4 (2019): e3000042. - -### Quantified Scientist: Tracking Myself -* Quantified Scientist: Tracking Myself -* https://www.pintofscience.nl/nijmegen-quantified-scientist-track -* Subjects - * N = 1 - * male - * a PhD student -* Data - * Brain MRI, EEG - * Rob started about 1.5 years ago and has spent about 11 hours a week measuring things -* https://www.evernote.com/l/ALvoejuj8OdPpos0YVuCKS9iIaiAUIupnn0 - -### The Single Individual volunteer for Multiple Observations across Networks (SIMON) MRI dataset -* a sample of convenience of one healthy male aged between 29 and 46 years old, scanned in 73 sessions at multiple sites and with various scanner models -* http://fcon_1000.projects.nitrc.org/indi/retro/SIMON.html -* Subjects - * N = 1 - * male - * 29-46 years old -* Data - * multiple sites and with various scanner models - * sMRI, rsfMRI, dMRI, ASL, ... - * scanned in 73 sessions at -* http://fcon_1000.projects.nitrc.org/indi/retro/SIMON.html - -### Canadian subject dataset (Csub) -* A single individual over 2.5 years, 13 sites and 3 vendors -* No link so far -* Subjects - * N = 1 - * male - * 42 years old -* Data - * 13 sites, 3T Philips, Siemens and GE - * sMRI, rsfMRI - * 25 scanning sessions -* Multivariate consistency of resting-state fMRI connectivity maps acquired on a single individual over 2.5 years, 13 sites and 3 vendors, doi: https://doi.org/10.1101/497743 - -### Maclaren test-retest brain volume dataset -* Maclaren test-retest brain volume dataset -* https://openfmri.org/dataset/ds000239/ -* Subjects - * N = 3 - * 1 female, 2 males - * 26, 30, 31 years old -* Data - * 3T GE - * sMRI - * **20 scans** -* Maclaren, Julian, et al. "Reliability of brain volume measurements: A test-retest dataset." Scientific data 1 (2014): 140037. - -### Day2day -* Day2day: investigating daily variability of magnetic resonance imaging measures over half a year -* Email to authors of https://bmcneurosci.biomedcentral.com/articles/10.1186/s12868-017-0383-y -* Subjects - * N = 8 - * 6 female, 2 males - * 24-32 years old -* Data - * 3T Siemens - * sMRI, rsfMRI, T2 Hippocampus, DTI, MRS - * **11-50 scans** -* Filevich, Elisa, et al. "Day2day: investigating daily variability of magnetic resonance imaging measures over half a year." BMC neuroscience 18.1 (2017): 65. - -### CCBD -* Center for Cognition and Brain Disorders (CCBD) at Hangzhou Normal University -* 10.6084/m9.figshare.2007483 -* Subjects - * N = 30 - * 15 females, 15 males - * 20 to 30 years old -* Data - * 3T GE - * sMRI, rsfMRI - * **10 scans** -* Chen, Bing, et al. "Individual variability and test-retest reliability revealed by ten repeated resting-state brain scans over one month." PLoS One 10.12 (2015): e0144963. - -### HBN-SSI -* Healthy Brain Network Serial Scanning Initiative (HBN-SSI) -* http://fcon_1000.projects.nitrc.org/indi/hbn_ssi/index.html -* Subjects - * N = 13 - * 8 females, 5 males - * 21 to 42 years old (18-45 years old) -* Data - * 1.5T Siemens - * sMRI, rsfMRI, task fMRI, DKI - * **-14 scans** -* O’Connor, David, et al. "The Healthy Brain Network Serial Scanning Initiative: a resource for evaluating inter-individual differences and their reliabilities across scan conditions and sessions." GigaScience 6.2 (2017): 1-14. - -### MyConnectome -* The MyConnectome project -* http://myconnectome.org/wp/ -* Subjects - * N = 1 - * Male - * 45 years old -* Data - * 3T Siemens - * sMRI, rsfMRI, task fMRI, T2 - * **104 scans** -* Poldrack, Russell A., et al. "Long-term neural and physiological phenotyping of a single human." Nature communications 6 (2015): 8885. - -### Kirby Weekly -* Single-subject Resting state fMRI Reproducibility Resource -* http://www.nitrc.org/projects/kirbyweekly -* Subjects - * N = 1 - * Male - * 40 years old -* Data - * 3T Philips - * sMRI, rsfMRI - * **158 scans** -* Choe, Ann S., et al. "Reproducibility and temporal structure in weekly resting-state fMRI over a period of 3.5 years." PloS one 10.10 (2015): e0140134. - -### MASSIVE -* Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation -* http://www.massive-data.org/ -* Subjects - * N = 1 - * Female - * 25 years old -* Data - * 3 Tesla system (Philips Achieva) - * sMRI, dMRI - * 18 different occasions -* Froeling, Martijn, et al. "“MASSIVE” brain dataset: Multiple acquisitions for standardization of structural imaging validation and evaluation." Magnetic resonance in medicine 77.5 (2017): 1797-1809. - -### National Taiwan University Hospital -* National Taiwan University Hospital -* No download link -* Subjects - * N = 34 - * 19 females, 15 males - * 34-85 years old -* Data - * 1.5T & 3T, GE & Siemens - * sMRI - * 10-24 scans -* Yang, Chung-Yi, et al. "Reproducibility of brain morphometry from short-term repeat clinical MRI examinations: a retrospective study." PloS one 11.1 (2016): e0146913. - -### A sample of 8 healthy traveling subjects -* ? -* No download link -* Subjects - * N = 8 - * 4 females, 4 males - * 26.9 ± 4.3 years -* Data - * 8 3 T MR scanners with 3 different machine models across the United States and Canada - * sMRI, rsfMRI - * 16 scans -* Cao, Hengyi, et al. "Toward Leveraging Human Connectomic Data in Large Consortia: Generalizability of fMRI-Based Brain Graphs Across Sites, Sessions, and Paradigms." Cerebral Cortex (2018). -* Sites - * Emory University - * Harvard University - * University of Calgary - * University of California Los Angeles (UCLA) - * University of California San Diego (UCSD) - * University of North Carolina Chapel Hill (UNC) - * Yale University - * Zucker Hillside Hospital (ZHH) - -### 8 healthy traveling subjects -* ? -* No download link -* Subjects - * N = 8 -* Data - * 3T scanners/ 8 healthy adults acted as traveling phantoms, and were scanned twice at each of the four sites - * 1.5 T Siemens Sonata at UA, 3 T Siemens Trio at QU and UM, and 3 T Philips Intera at UBC -* Long, Xiangyu, et al. "Sensorimotor network alterations in children and youth with prenatal alcohol exposure." Human brain mapping (2018). -* Sites - * University of Alberta (UA) - * Queen's University (QU) - * University of Manitoba (UM) - * University of British Columbia (UBC) - -### MSC -* The Midnight Scan Club (MSC) dataset -* https://openfmri.org/dataset/ds000224/ -* Subjects - * N = 10 - * 5 females, 5 males - * 24-34 years old -* Data - * 3T Siemens - * sMRI, T2, MRA, MRV, rsfMRI, task fMRI - * 4 scans for sMRI/T2/MRA, 8 scans for MRV, 10 scans for rsfMRI/task fMRI -* Gordon, Evan M., et al. "Precision Functional Mapping of Individual Human Brains." Neuron (2017). - -### Yale Test-Retest Dataset -* Yale Test-Retest Dataset -* http://fcon_1000.projects.nitrc.org/indi/retro/yale_trt.html -* Subjects - * N = 12 -* Data - * T1 and rsfMRI - * 144 min of functional data was collected for each subject (4 sessions/subject × 6 runs/session × 6 min/run) -* Noble, S., Spann, M. N., Tokoglu, F., Shen, X., Constable, R. T., & Scheinost, D. (2017). Influences on the test–retest reliability of functional connectivity MRI and its relationship with behavioral utility. Cerebral Cortex, 27(11), 5415-5429. - -### Yale High-Resolution Controls Dataset -* Yale High-Resolution Controls Dataset -* http://fcon_1000.projects.nitrc.org/indi/retro/yale_hires.html -* Subjects - * N = 120 -* Data - * T1 and rsfMRI - * 717 functional scans (120 subjects x 6 runs/subject - 3 missing runs) - * 240 anatomical scans (120 subjects x 2 scans/subject) -* Finn, E. S., Shen, X., Scheinost, D., Rosenberg, M. D., Huang, J., Chun, M. M., ... & Constable, R. T. (2015). Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity. Nature neuroscience, 18(11), 1664. - -### Yale Low-Resolution Controls Dataset -* Yale Low-Resolution Controls Dataset -* http://fcon_1000.projects.nitrc.org/indi/retro/yale_lowres.html -* Subjects - * N = 100 -* Data - * T1 and rsfMRI - * 800 functional scans (100 subjects x 8 runs/subject) - * 200 anatomical scans (100 subjects x 2 scans/subject) - -### BOLD5000 -* BOLD5000: A public fMRI dataset of 5000 images -* https://bold5000.github.io/index.html -* Subjects - * N = 4 -* Data - * 3T Siemens - * 15 fMRI sessions + 1 T1 and diffusion session - * fMRI dataset collected on 4 subjects, each observing 5,254 images -* https://arxiv.org/abs/1809.01281 - -### Reproducibility of quantitative structural and physiological MRI measurements -* Reproducibility of quantitative structural and physiological MRI measurements -* -* Subjects - * N = 25 - * 5 females, 20 males - * 18-41 years old -* Data - * 3T Siemens - * sMRI, dMRI, T2, ASL, MRS - * 3 scans -* McGuire, Stephen A., et al. "Reproducibility of quantitative structural and physiological MRI measurements." Brain and Behavior (2017). - -### The brain scans of Taylor Hanayik -* This repository contains neuroimaging data of Taylor Hanayik since 2015 (age 24). -* https://github.com/hanayik/Taylor-Hanayik-Brain-Scans -* Subjects - * N = 1 -* Data - * plan to collect at least one structural image per month -* ref? - -### Continuous scanning of the migraine cycle over 30 days -* Subject - * N = 1, female - * One patient with the diagnosis of migraine -* Data - * 3 T MRI scanner - * fMRI + T1 -* Schulte, Laura H., and Arne May. "The migraine generator revisited: continuous scanning of the migraine cycle over 30 days and three spontaneous attacks." Brain 139.7 (2016): 1987-1993. - -### The BrainTime study -* Longitudinal project, from Leiden University -* https://www.biorxiv.org/content/early/2018/08/06/278358 -* Subjects - * N = 240+, both male and female - * One patient with the diagnosis of migraine -* Data - * 3 T MRI scanner - * T1 - * three scans, with ~2 year intervals -* Klapwijk, Eduard T., et al. "Qoala-T: A supervised-learning tool for quality control of FreeSurfer segmented MRI data." - -### A dataset for the test-retest reliability assessment of EEG & ERP quantities -* This data package contains single-trial ERPs from 4 participants, each tested in 10 sessions on 10 different days. -* https://figshare.com/articles/A_dataset_for_the_test-retest_reliability_assessment_of_EEG_ERP_quantities/2068626 -* Subject - * N = 4 -* Data - * Biosemi data in BDF format were recorded from 128 electrodes at 512 Hz. - -### A dataset with T1 and multiple task fMRI -* Single subject fMRI test–retest reliability metrics and confounding factors -* https://www.sciencedirect.com/science/article/pii/S1053811912010890?via%3Dihub -* Subject - * N = 10, 50-58 years - * 2 sessions, T1 and 4 tasks in each session -* Data - * GE 1.5T - * T1 & task fMRI - * two/three days apart -* Gorgolewski, Krzysztof J., et al. "Single subject fMRI test–retest reliability metrics and confounding factors." Neuroimage 69 (2013): 231-243. - -### Multi-parametric neuroimaging reproducibility -* Multi-parametric neuroimaging reproducibility: A 3-T resource study -* Subject - * N = 21, 11M/10F - * 22-61 years old -* Data - * multiple paramatric scanning - * T1, DTI, rs-fMRI, ASL, & QT1, QT2, et al. -* Landman, Bennett A., et al. "Multi-parametric neuroimaging reproducibility: a 3-T resource study." Neuroimage 54.4 (2011): 2854-2866. - -### A high resolution 7-Tesla resting-state fMRI test-retest dataset with cognitive and physiological measures -* A high resolution 7-Tesla resting-state fMRI test-retest dataset with cognitive and physiological measures -* http://openscience.cbs.mpg.de/7t_trt/ -* Subject - * N = 22, 12M/10F - * 21-30 -* Data - * 7T scanner - * T1, rs-fMRI, and prefrontal submillimeter (0.75mm, TR=4s) rs-fMRI scan - * two sessions, multiple scans per session -* Gorgolewski, Krzysztof J., et al. "A high resolution 7-Tesla resting-state fMRI test-retest dataset with cognitive and physiological measures." Scientific data 2 (2015): 140054. - -### Duke ScanRescanData -* https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3782252/ -* Subject - * N = 23, 9 females - * mean age 23.3, sd = 3.3 -* Data - * 3T scanner - * T1 - * 4 scans, 7-9 days apart between 1-2 and 3-4 -* Morey, Rajendra A., et al. "Scan–rescan reliability of subcortical brain volumes derived from automated segmentation." Human brain mapping 31.11 (2010): 1751-1762. - -### Open Access Series of Imaging Studies (OASIS) -* Open Access Series of Imaging Studies (OASIS), cross-sectional MRI data -* https://www.oasis-brains.org/ -* Subject - * N = 416, 20 with re-scans in 90 days - * 18-96 years old -* Data - * 1.5 T - * T1 - * 3-4 scanns in each sessions, 20 subjects with two sessions -* Marcus, Daniel S., et al. "Open Access Series of Imaging Studies (OASIS): cross-sectional MRI data in young, middle aged, nondemented, and demented older adults." Journal of cognitive neuroscience 19.9 (2007): 1498-1507. - -### OASIS Longitudinal -* OASIS Longitudinal -* https://www.oasis-brains.org/ -* Subject - * N = 150 - * 60-96 years old -* Data - * 1.5 T scanner - * T1 - * two or more scans, at least one year (183-1707 day intervals) -* Marcus, Daniel S., et al. "Open access series of imaging studies: longitudinal MRI data in nondemented and demented older adults." Journal of cognitive neuroscience 22.12 (2010): 2677-2684. - -### OASIS Longitudinal OASIS-3 -* OASIS-3: Longitudinal Neuroimaging, Clinical, and Cognitive Dataset for Normal Aging and Alzheimer’s Disease -* https://www.oasis-brains.org/ -* Subject - * N = 1098 - * 42-95 years old -* Data - * > 2000 sessions - * T1, DTI, rs-fMRI, ASL, PET -* https://www.oasis-brains.org/ - -### A test–retest reliability analysis of diffusion measures -* A test–retest reliability analysis of diffusion measures -* http://www.nitrc.org/projects/dwi_test-retest/. -* Subject - * N = 34, 18 females - * 19.17-35.67 years old -* Data - * 3T scanner - * T1, DWI - * scanned twice on a single day, subsample of N = 15 had a third session in same day and a 2-week follow-up -* Boekel, W., B. U. Forstmann, and M. C. Keuken. "A test‐retest reliability analysis of diffusion measures of white matter tracts relevant for cognitive control." Psychophysiology 54.1 (2017): 24-33. - -### Human brain diffusion-weighted MRI -* Collected with high diffusion-weighting angular resolution and repeated measurements at multiple diffusion-weighting strengths -* https://purl.stanford.edu/ng782rw8378 -* Subjects - * N =2 - * 2 males, age 27 and 36 -* Data - * 3T GE - * dMRI - * 2 scans in each of b=1000, 2000, 4000 -* Rokem et al. (2015) "Evaluating the Accuracy of Diffusion MRI Models in White Matter" http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0123272 - -### 100 runs at 3T -* Three subjects were scanned on a General Electric 3T MRI scanner. All subjects underwent 100 functional runs -* https://openneuro.org/datasets/ds001553/versions/1.0.0 -* Subjects - * N =3 - * 1 males, 2 females - * age= 27(2.5) years - * right handed -* Data - * General Electric 3T MRI scanner - * task and resting-state fMRI - * 100 functional runs, which consisted of five blocks of stimulation (20 s: flickering checkerboard at 8 Hz + letter/number discrimination task) and 40 s of rest -* Gonzalez-Castillo, Javier, et al. "Whole-brain, time-locked activation with simple tasks revealed using massive averaging and model-free analysis." Proceedings of the National Academy of Sciences (2012): 201121049. - -### Individual Brain Charting -* Individual brain charting: high resolution mapping of 12 human brains -* https://project.inria.fr/IBC/ -* https://openfmri.org/dataset/ds000244/ -* Subjects - * N = 12 - * 10 males, 2 females - * age between 26 and 40 years old (median = 34.5 years) -* Data - * Siemens 3T - * T1/T2/dMRI/task fMRI - * multiple tasks for each subject, Spatial, Standard, Social, Emotional, Emotion, Gambling, Motor, Language, Relational, WM -* Pinho, Ana Luísa, et al. "Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping." Scientific data 5 (2018). - -### ISBI2015 Longitudinal Multiple Sclerosis Lesion Segmentation -* Longitudinal multiple sclerosis lesion segmentation challenge -* https://smart-stats-tools.org/lesion-challenge -* Subjects - * N = 9, 5 subjects provided ROI - * 4 males, 15 females -* Data - * a 3.0 Tesla MRI scanner - * T1/T2/FLAIR/PD - * each subject has 4 ~ 6 time-point scans -* Carass, A., Roy, S., et al. (2017). Longitudinal multiple sclerosis lesion segmentation: Resource and challenge. NeuroImage, 148, 77–102 + +A list of brain imaging databases with multiple (e.g., more than 3) scans per subject — dense single-subject sampling, traveling-subjects harmonization resources, multi-subject test-retest, longitudinal developmental/aging cohorts, longitudinal clinical cohorts, and post-treatment neuro-oncology follow-up. Feel free to update the list via pull requests. + +**Sorting:** within each table, entries are ordered chronologically (newest first) by primary publication or data release year. **Access** column flags how to obtain the data: *Open* = direct download, *BIDS/OpenNeuro* = BIDS-formatted on a public archive, *Application* = DUA/credentialed access, *Restricted* = no public link. + +--- + +## 1. Single-subject dense sampling (N = 1) + +| Year | Dataset | Subject | Sessions | Modalities | Scanner | Access | Reference | +|---|---|---|---|---|---|---|---| +| 2019 | [28andMe / Menstrual cycle](https://doi.org/10.1101/866913) | F, 23 | 30 daily | MRI, fMRI, behavioral, endocrine | Siemens 3T Prisma | Open (on publication) | Pritschet et al., bioRxiv 2019 | +| 2019 | [Naturalistic stimuli, single subject](https://doi.org/10.1101/687681) | M, 27.5 | 22 (Apr–Dec 2017) | MRI, fMRI | Siemens 3T Prisma | Open | bioRxiv 2019 | +| 2019 | [SIMON](http://fcon_1000.projects.nitrc.org/indi/retro/SIMON.html) ([CONP BIDS mirror](https://github.com/conpdatasets/SIMON-dataset)) | M, 29–46 | 73, multi-site | sMRI, rsfMRI, dMRI, ASL, etc. | Various | Open (S3) | NITRC INDI | +| 2019 | [Quantified Scientist](https://www.evernote.com/l/ALvoejuj8OdPpos0YVuCKS9iIaiAUIupnn0) | M, PhD student | ~1.5 yr, 11 h/wk | MRI, EEG | — | Personal log | Pint of Science NL | +| 2018 | Canadian subject (Csub) — [bioRxiv](https://doi.org/10.1101/497743) | M, 42 | 25 (2.5 yr, 13 sites) | sMRI, rsfMRI | 3T Philips/Siemens/GE | Restricted | bioRxiv 2018 | +| 2017 | [MASSIVE](http://www.massive-data.org/) | F, 25 | 18 | sMRI, dMRI | 3T Philips Achieva | Open | Froeling et al., MRM 2017 | +| 2016 | Migraine cycle | F, 1 patient | 30 days continuous + 3 attacks | fMRI, T1 | 3T | Restricted | Schulte & May, Brain 2016 | +| 2015 | [MyConnectome](http://myconnectome.org/wp/) | M, 45 | 104 | sMRI, rsfMRI, task fMRI, T2 | 3T Siemens | Open | Poldrack et al., Nat Commun 2015 | +| 2015 | [Kirby Weekly](http://www.nitrc.org/projects/kirbyweekly) | M, 40 | 158 (3.5 yr) | sMRI, rsfMRI | 3T Philips | Open (NITRC) | Choe et al., PLoS One 2015 | +| 2015+ | [Taylor Hanayik brain scans](https://github.com/hanayik/Taylor-Hanayik-Brain-Scans) | M, 24+ | ≥1/month | sMRI | — | Open (GitHub) | — | + +--- + +## 2. Traveling subjects / multi-site harmonization + +| Year | Dataset | N | Sites / Scanners | Modalities | Access | Reference | +|---|---|---|---|---|---|---| +| 2025 | [ON-Harmony](https://www.nature.com/articles/s41597-025-04822-2) | 20 | 6 scanners × 3 vendors (GE/Siemens/Philips) | T1w, T2w, SWI, fMRI, dMRI | BIDS [OpenNeuro ds004712](https://openneuro.org/datasets/ds004712) | Nat Sci Data 2025 | +| 2020 | Multi-shell dMRI traveling adults — [PMC7253426](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7253426/) | — | Multi-center, identical settings | dMRI | Open | Tong et al. 2020 | +| 2019 | [DecNef Travelling Subjects](https://bicr-resource.atr.jp/decnefpro/) | 9 M | 12 sites (GE/Siemens/Philips) | MRI, rsfMRI | Application | Yamashita et al., PLoS Biol 2019 | +| 2018 | [Cao 2018 (8-site)](https://doi.org/10.1093/cercor/bhy032) | 8 (M+F, ~26.9 yr) | 8× 3T, 3 models (Emory, Harvard, Calgary, UCLA, UCSD, UNC, Yale, ZHH) | sMRI, rsfMRI | Restricted | Cao et al., Cereb Cortex 2018 | +| 2018 | Hawco 2018 — Psychiatry Res Neuroimaging 282 | 4 M (34–59) | 5 scanners, 3 yr (3/6/6/9 scans) | MRI, dMRI, rsfMRI | Restricted | Hawco et al. 2018 | +| 2018 | Long 2018 (4-site Canada) — HBM | 8 | UA, QU, UM, UBC (1.5T/3T, Siemens/Philips) | sMRI, rsfMRI | Restricted | Long et al., HBM 2018 | +| — | [FTHP (Frequently Traveling Human Phantom)](https://www.nitrc.org/projects/fthp) | — | Multi-site | sMRI | Open (NITRC) | — | + +--- + +## 3. Multi-subject test-retest + +| Year | Dataset | N | Age | Sessions | Modalities | Scanner | Access | Reference | +|---|---|---|---|---|---|---|---|---| +| 2018 | [Individual Brain Charting (IBC)](https://project.inria.fr/IBC/) | 12 (10M/2F) | 26–40 | Multi-task | T1, T2, dMRI, task fMRI | 3T Siemens | [OpenfMRI ds000244](https://openfmri.org/dataset/ds000244/) | Pinho et al., Sci Data 2018 | +| 2018 | [BOLD5000](https://bold5000.github.io/) | 4 | — | 15 fMRI + 1 T1/dMRI | T1, fMRI (5,254 images) | 3T Siemens | Open | Chang et al., arXiv 2018 | +| 2018 | [100 runs at 3T](https://openneuro.org/datasets/ds001553/versions/1.0.0) | 3 (1M/2F, ~27) | — | 100 functional runs | task + rsfMRI | 3T GE | OpenNeuro | Gonzalez-Castillo et al., PNAS 2012 | +| 2017 | [Midnight Scan Club (MSC)](https://openfmri.org/dataset/ds000224/) | 10 (5F/5M) | 24–34 | 4–10 | sMRI, T2, MRA, MRV, rsfMRI, task | 3T Siemens | OpenfMRI | Gordon et al., Neuron 2017 | +| 2017 | [HBN-SSI](http://fcon_1000.projects.nitrc.org/indi/hbn_ssi/index.html) | 13 (8F/5M) | 21–42 | ~14 | sMRI, rsfMRI, task fMRI, DKI | 1.5T Siemens | Open | O'Connor et al., GigaScience 2017 | +| 2017 | Reproducibility (McGuire) — Brain Behav | 25 (5F/20M) | 18–41 | 3 | sMRI, dMRI, T2, ASL, MRS | 3T Siemens | Restricted | McGuire et al. 2017 | +| 2017 | Day2day — BMC Neurosci | 8 (6F/2M) | 24–32 | 11–50 | sMRI, rsfMRI, T2 hippo, DTI, MRS | 3T Siemens | Email authors | Filevich et al. 2017 | +| 2017 | [Yale Test-Retest](http://fcon_1000.projects.nitrc.org/indi/retro/yale_trt.html) | 12 | — | 4 sess × 6 runs | T1, rsfMRI | — | Open | Noble et al., Cereb Cortex 2017 | +| 2017 | [DWI test-retest (Boekel)](http://www.nitrc.org/projects/dwi_test-retest/) | 34 (18F) | 19–36 | 2 (+ subsample 4) | T1, DWI | 3T | Open | Boekel et al., Psychophysiology 2017 | +| 2016 | NTUH — PLoS One | 34 (19F/15M) | 34–85 | 10–24 | sMRI | 1.5T/3T GE & Siemens | Restricted | Yang et al. 2016 | +| 2015 | [CCBD](https://doi.org/10.6084/m9.figshare.2007483) | 30 (15F/15M) | 20–30 | 10 | sMRI, rsfMRI | 3T GE | Open (figshare) | Chen et al., PLoS One 2015 | +| 2015 | [Yale Hi-Res Controls](http://fcon_1000.projects.nitrc.org/indi/retro/yale_hires.html) | 120 | — | 2 anat + 6 runs | T1, rsfMRI | — | Open | Finn et al., Nat Neurosci 2015 | +| 2015 | [7T test-retest (MPI)](http://openscience.cbs.mpg.de/7t_trt/) | 22 (12M/10F) | 21–30 | 2 sess, multi | T1, rsfMRI, submm rsfMRI | 7T | Open | Gorgolewski et al., Sci Data 2015 | +| 2015 | [High-angular dMRI (Rokem)](https://purl.stanford.edu/ng782rw8378) | 2 M (27, 36) | — | 2 × b=1000/2000/4000 | dMRI | 3T GE | Open | Rokem et al., PLoS One 2015 | +| 2014 | [Maclaren test-retest](https://openfmri.org/dataset/ds000239/) | 3 (1F/2M) | 26–31 | 20 | sMRI | 3T GE | OpenfMRI | Maclaren et al., Sci Data 2014 | +| 2013 | Gorgolewski 2013 — NeuroImage | 10 | 50–58 | 2 sess (T1 + 4 tasks) | T1, task fMRI | 1.5T GE | Restricted | Gorgolewski et al. 2013 | +| 2011 | Multi-parametric (Landman) — NeuroImage | 21 (11M/10F) | 22–61 | Multi | T1, DTI, rsfMRI, ASL, qT1/qT2 | 3T | Restricted | Landman et al. 2011 | +| 2010 | Duke ScanRescan — HBM | 23 (9F) | ~23 | 4 (7–9 d apart) | T1 | 3T | Restricted | Morey et al. 2010 | +| — | [Yale Low-Res Controls](http://fcon_1000.projects.nitrc.org/indi/retro/yale_lowres.html) | 100 | — | 2 anat + 8 runs | T1, rsfMRI | Open | — | +| — | [EEG/ERP test-retest](https://figshare.com/articles/_/2068626) | 4 | — | 10 sessions / 10 days | EEG (128ch, 512 Hz) | Open (figshare) | — | + +### Related: meta-resources for reliability + +| Dataset | N | Note | +|---|---|---| +| [CoRR](http://fcon_1000.projects.nitrc.org/indi/CoRR/html/) | 1629 across 32 sites | Aggregates many retest cohorts (HBN-SSI, NYU, BNU, IPCAS, etc.) | +| [Open BHB](https://baobablab.github.io/bhb/) | 5330 + 661 retest | Brain-age benchmark, multi-site healthy | +| HCP Test-Retest | 45 from HCP-YA | Gold-standard reliability ([humanconnectome.org](https://www.humanconnectome.org/)) | +| HCP 7T Retest | 33 | 7T rsfMRI/dMRI repeat | + +--- + +## 4. Longitudinal developmental / aging cohorts + +| Year | Dataset | N | Age | Schedule | Modalities | Access | +|---|---|---|---|---|---|---| +| 2019 | [OASIS-3](https://www.oasis-brains.org/) | 1098 | 42–95 | ~2000 sessions | T1, DTI, rsfMRI, ASL, PET | Application | +| 2019 | Infants longitudinal — [PNAS](https://doi.org/10.1073/pnas.1821523116) | 43 | 1–24 mo | 7 (1/3/6/9/12/18/24 mo) | MRI | Restricted | +| 2018+ | [ABCD](https://nda.nih.gov/abcd) | 11800+ | 9–10 baseline | 2-yearly, 10 yr planned | sMRI, fMRI, dMRI | Application (NDA) | +| 2018+ | [HCP-Aging](https://www.humanconnectome.org/study/hcp-lifespan-aging) | 1200 | 36–100 | + 200 retest | Full HCP protocol | Application | +| 2018+ | [HCP-Development](https://www.humanconnectome.org/study/hcp-lifespan-development) | 1300 | 5–21 | + retest subset | Full HCP protocol | Application | +| 2018 | BrainTime (Leiden) — [bioRxiv](https://www.biorxiv.org/content/early/2018/08/06/278358) | 240+ | — | 3 (~2 yr intervals) | T1 | Restricted | Klapwijk et al. | +| 2017+ | [UK Biobank Imaging](https://www.ukbiobank.ac.uk/) | 100000 target | 40–80 | Baseline + repeat visit (~10000) | T1, T2 FLAIR, SWI, dMRI, rsfMRI, tfMRI | Application | +| 2015 | [NCANDA](https://www.niaaa.nih.gov/research/major-initiatives/national-consortium-alcohol-and-neurodevelopment-adolescence) | 800+ | 12–21 baseline | Annual ≥5 yr, 5 sites | sMRI, dMRI, fMRI | Application | +| 2014 | [PNC](https://www.med.upenn.edu/bbl/philadelphianeurodevelopmentalcohort.html) | 1445 + 340 retest | 8–21 | Mostly cross-sec + retest subset | sMRI, dMRI, fMRI, ASL | dbGaP | +| 2014+ | [Cam-CAN](https://www.cam-can.mrc-cbu.cam.ac.uk/) | 700 (~280 with 2nd visit) | 18–88 | + follow-up subset | Multi-modal | Application | +| 2010 | OASIS Longitudinal — [oasis-brains.org](https://www.oasis-brains.org/) | 150 | 60–96 | ≥2 (183–1707 d) | T1 | Open | Marcus et al., JoCN 2010 | +| 2010 | [IMAGEN](https://imagen-project.org/) | 2000+ | 14 baseline | 14/16/19/22 yr | sMRI, fMRI | Application | +| 2007 | OASIS cross-sectional — [oasis-brains.org](https://www.oasis-brains.org/) | 416 (20 rescans ≤90 d) | 18–96 | 3–4 per session | T1 | Open | Marcus et al., JoCN 2007 | +| — | [BLSA imaging](https://www.blsa.nih.gov/) | 1500+ | Adult | Multi-year | T1, fMRI, PET | Application | +| — | [Generation R](https://generationr.nl/) | 9000+ | Pediatric | Multi-wave | MRI | Restricted | +| — | [Dallas Lifespan Brain Study](https://labs.utdallas.edu/dallaslifespanbrainstudy/) | 500+ | 20–89 | ~4 yr intervals | sMRI, fMRI, PET | Restricted | +| — | [NSPN (Cambridge)](https://www.nspn.org.uk/) | 300+ | 14–24 | 2 timepoints | sMRI, fMRI | Application | +| — | [MACS](https://for2107.de/) | 2000+ | Adult | 2 timepoints, 2 sites | Multi-modal | Restricted | +| — | [MPI-Leipzig Mind-Brain-Body](https://openneuro.org/datasets/ds000221) | 318 | 20–75 | 2 sessions | Multi-modal | OpenNeuro | +| — | NKI-RS / eNKI longitudinal — [INDI](http://fcon_1000.projects.nitrc.org/indi/enhanced/) | — | Lifespan | Multi-visit subset | Multi-modal | Application | +| — | SLIM (Southwest Longitudinal) | ~600 students | College | 3 timepoints | Multi-modal | Restricted | + +--- + +## 5. Longitudinal clinical cohorts + +### Alzheimer's disease / dementia + +| Year | Dataset | N | Schedule | Modalities | Access | +|---|---|---|---|---|---| +| 2019+ | [OASIS-4](https://www.oasis-brains.org/) | 663 | Clinical referrals | Multi | Application | +| 2017+ | [PREVENT-AD](https://openpreventad.loris.ca/) | 400+ | Annual ≥3 yr | T1, FLAIR, ASL, DTI, rsfMRI | Open subset | +| 2014+ | [A4 / LEARN](https://a4study.org/) | 1000+ | Multi-year | T1, amyloid PET | Application | +| 2012+ | [DIAN](https://dian.wustl.edu/) | 500+ | Multi-year | T1, DTI, fMRI, PET, CSF | Application | +| 2010 | [MIRIAD](https://www.ucl.ac.uk/drc/research/methods/minimal-interval-resonance-imaging-alzheimers-disease-miriad) | 69 (46 AD, 23 ctrl) | Up to 9 scans over 2 yr | T1 | Open (registration) | +| 2009+ | [AIBL](https://aibl.csiro.au/) | 1100+ | 18 mo intervals | T1, FLAIR, PET | Application | +| 2004+ | [ADNI](https://adni.loni.usc.edu/) (1/GO/2/3/4) | 2400+ | 6–12 mo, up to 10+ timepoints | T1, T2, FLAIR, DTI, fMRI, ASL, PET | Application | +| — | [WRAP](https://wrap.wisc.edu/) | 1500+ | 2–4 yr cycle | T1, DTI, PET | Application | +| — | [NACC](https://naccdata.org/) | 40000+ | Annual | T1 + clinical | Application | + +### Parkinson's & Huntington's + +| Year | Dataset | N | Schedule | Modalities | Access | +|---|---|---|---|---|---| +| 2010+ | [PPMI](https://www.ppmi-info.org/) | 1400+ | Annual, multi-site | T1, DTI, rsfMRI, DAT-SPECT | Application | +| 2009+ | [Enroll-HD / PREDICT-HD / TRACK-HD](https://enroll-hd.org/) | 360 + 240 + 1000 | Annual ≥3 yr | T1, DTI, fMRI | Application | +| — | TRACK-PD | 350+ | Annual | T1, DTI, fMRI | Restricted | + +### Multiple sclerosis + +| Year | Dataset | N | Note | Access | +|---|---|---|---|---| +| 2021 | [MSSEG-2](https://portal.fli-iam.irisa.fr/msseg-2/) | 100 | 2 timepoints, lesion seg | Open (challenge) | +| 2017 | [ISBI2015 MS Lesion](https://smart-stats-tools.org/lesion-challenge) | 9 (5 with ROI) | 4–6 timepoints; T1/T2/FLAIR/PD | Open | Carass et al., NeuroImage 2017 | +| 2016 | [MSSEG-1](https://portal.fli-iam.irisa.fr/msseg-challenge/overview) | 53 | Multi-scanner | Open (challenge) | +| — | [OFSEP](https://www.ofsep.org/en/) | 70000+ | Multi-year French MS cohort | Restricted | + +### Psychosis / schizophrenia + +| Dataset | N | Note | Access | +|---|---|---|---| +| [FBIRN Phase II/III](https://coins.trendscenter.org/) | 5 traveling + patients | Multi-site (3T, 4 vendors); classic harmonization | Application | +| [B-SNIP](https://www.b-snip.org/) | 2400+ | Multi-site psychosis | NDA | +| [COBRE longitudinal](https://coins.trendscenter.org/) | 200+ | 2–3 timepoints | Application | + +### Epilepsy + +| Dataset | Note | Access | +|---|---|---| +| [MELD Project](https://meldproject.github.io/) | Multi-site FCD detection | Open | + +--- + +## 6. Neuro-oncology — pre/post-treatment & longitudinal follow-up + +All on [The Cancer Imaging Archive (TCIA)](https://www.cancerimagingarchive.net/) unless noted. + +| Year | Dataset | N | Timepoints | Tumor type | Modalities | +|---|---|---|---|---|---| +| 2024 | [BraTS 2024 post-treatment](https://www.synapse.org/brats2024) | 2200+ | Pre + post-treatment | GBM | Multi-parametric MRI | +| 2024 | [ReMIND (Brigham)](https://www.cancerimagingarchive.net/collection/remind/) | 114 | Pre + intra-op + post-op (incl. iUS) | Brain tumors (mixed) | MRI + intraoperative US | +| 2023 | [Burdenko-GBM-Progression](https://www.cancerimagingarchive.net/collection/burdenko-gbm-progression/) | 180 | Multi-timepoint progression | GBM | Multi-parametric MRI | +| 2023 | [RHUH-GBM](https://www.cancerimagingarchive.net/collection/rhuh-gbm/) | 40 | Pre + 3 post-op | GBM | Multi-parametric MRI | +| 2022 | [LUMIERE](https://www.cancerimagingarchive.net/collection/lumiere/) | 91 | Pre-op + ~4 follow-ups | GBM | Multi-parametric MRI | +| 2022 | [UCSF-PDGM](https://www.cancerimagingarchive.net/collection/ucsf-pdgm/) | 501 | Pre-op + follow-up subset | Glioma | Multi-parametric MRI | +| 2022 | [Brain-TR-GammaKnife](https://www.cancerimagingarchive.net/collection/brain-tr-gammaknife/) | 47 | Pre + multi follow-up post-SRS | Metastases | T1c MRI | +| 2021 | [UPENN-GBM](https://www.cancerimagingarchive.net/collection/upenn-gbm/) | 630 | Pre + post-op | GBM | Multi-parametric MRI | +| 2020 | [GLIS-RT](https://www.cancerimagingarchive.net/collection/glis-rt/) | 230 | Pre + radiotherapy planning | Glioma | MRI + RT structures | +| 2016 | [Ivy GAP](https://www.cancerimagingarchive.net/collection/ivygap/) | 39 | Multi-modal + follow-up | GBM | Multi-parametric MRI | + +--- + +## Contributing + +PRs adding new datasets, fixing broken links, or updating access status are welcome. Please keep entries within the existing table format and sort chronologically (newest first) within the appropriate section. For datasets that don't fit existing categories, add a new section rather than forcing them into an unrelated one.