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https://github.com/Conxz/multiBrain

A list of brain imaging datasets with multiple scans per subject. Feel free to update the list via 'pull requests'!
https://github.com/Conxz/multiBrain

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A list of brain imaging datasets with multiple scans per subject. Feel free to update the list via 'pull requests'!

Host: GitHub
URL: https://github.com/Conxz/multiBrain
Owner: Conxz
Created: 2017-08-10T12:58:09.000Z (over 7 years ago)
Default Branch: master
Last Pushed: 2022-03-26T20:40:47.000Z (over 2 years ago)
Last Synced: 2024-08-03T15:11:33.920Z (3 months ago)
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Forks: 16
Open Issues: 1
Metadata Files:
- Readme: README.md

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README

# 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).