IDsecondary_IDnamedescriptionpi_firstnamepi_lastnameURI
IGT1IGT1SPL Image Guided TherapyPublic access data from the Image Guided Therapy program in the Surgical Planning Laboratory at Brigham and Womens Hospital/data/projects/IGT1
CENTRAL_hiphiphippocampus lddmma description/data/projects/CENTRAL_hip
CENTRAL_MRTBrain10MRTBrain10MRT Brain Non-rigid registration/data/projects/CENTRAL_MRTBrain10
PBNCPBNCPediatric Bipolar Neuroimaging ConsortiumA central location for sharing images for the PBNC/data/projects/PBNC
BPC2019BPCBrasilia Parkinson CohortCohort study of ParkinsonĀ“s disease and cognitive symptomsPedro Renato de PaulaBrandao/data/projects/BPC2019
PALSPALSPALS: Population-Average, Landmark- and Surface-based atlasCases composing the PALS atlas as borrowed from the OASIS cross-sectional data set. Includes raw T1 images, FSL's FAST tissue-segmented images, and Freesurfer-generated surfaces and subcortical parcellations./data/projects/PALS
CVRG0001CVRG0001CVRG LDDMM Cardiac DataTesting upload of cardiac data./data/projects/CVRG0001
BC_CT_TORBC_CT_TORBoston Children's CT TorsosCT torso image volumes collected and manually segmented by the Pediatric Cardiology Department of Boston Children's Hospital and uploaded as a pilot project for the CardioVascular Research Grid (CVRG)./data/projects/BC_CT_TOR
NHRDNAMIC High Res DTINAMIC High Resolution DTI/data/projects/NHRD
KKtest_XNDKKtest_XNDKKtest_XND/data/projects/KKtest_XND
RAT_Bottom-upRat Bottom-up fMRIBottom-up sensory processing can decrease activity and functional connectivity in the default mode like network in ratsData described in paper: Bottom-up sensory processing can decrease activity and functional connectivity in the default mode like network in rats - Hinz R et al., 2019. Data includes: Anatomical T2 TurboRARE, Resting state baseline (RSB), Continuous random visual stimulation (CVS) and block design visual stimulation (BVS) scans.RukunHinz/data/projects/RAT_Bottom-up
SelfcareDISDepression Impacted by SelfcareA non-official linear study collecting data of high school students reporting mild depression. After giving instructions for simple, short treatments they can complete on their own, they will be continuously collecting data for us. Olivia Harris/data/projects/Selfcare
mBIRN_demomBIRN_demomBIRN_demo/data/projects/mBIRN_demo
GroupwiseNAMIC Groupwise RegNAMIC Groupwise RegistrationThe NAMIC Groupwise Registration Tutorial represents the convergence of groupwise registration algorithms from Polina Golland's lab at MIT, data from Martha Shenton's group at the Harvard Medical School, and the XNAT project. The goal is to showcase the use of these NAMIC tools and promote the use of the groupwise registration methods throughout the NAMIC community./data/projects/Groupwise
defaultdefaultdefaulttest xnd upload project/data/projects/default
DicomRTDicomRT SamplesDicomRT SamplesThese are data samples for the DicomRT extension to DICOM.GregSharp/data/projects/DicomRT
GWEGWE Test DataGWE Integration Test DataMarcoRuiz/data/projects/GWE
SPL_IGTNCIGT SPLNCIGTNCIGT MRT Tumor Resectiontinakapur/data/projects/SPL_IGT
CalibmBIRN CalibrationmBIRN_calibThis data set consists of spoiled gradient-recalled echo magnetic resonance imaging data from five healthy volunteers (four males and one female) scanned twice at four sites having 1.5T systems from different vendors(Siemens, GE, Marconi Medical Systems). Some subjects were also scanned a single time at another site. One subject was only scanned twice at three sites (subject 73213384) and once at another site. For each subject, four Fast Low-Angle Shot (FLASH) scans with flip angles of 3, 5, 20, and 30 degrees were obtained in a single scan session, from which tissue proton density and T1 maps can be derived. These data were acquired to investigate various metrics of within-site and across-site reproducibility. This study was sponsored by the Brain Morphometry testbed (MBIRN) of the Biomedical Informatics Research Network (BIRN). The images have been defaced so that no facial features can be reconstructed from these data. KarlHelmer/data/projects/Calib
IGT_FMRI_NEURONCIGT_Functional_NeuroFunctional Data for Neurosurgical PlanningThis is a collection of 44 publicly available functional mri scans for neurosurgery. The series description is the task performed for that particular series.FerencJolesz/data/projects/IGT_FMRI_NEURO
LONI_PL_ICBMLONI Pipeline ICBM DataLONI_PL_ICBMZhizhongLiu/data/projects/LONI_PL_ICBM
IGT_GLIOMANCIGT_Intraop_GliomaNCIGT Intra-operative MRT Glioma ResectionThis is a collection of 33 publicly available MR data sets containing brain tumors (gliomas). Each data set contains multiple MR acquisitions (T1, T2, or SPGR) within a single series, as well as a description of the tumor, its size, grade, and location. FerencJolesz/data/projects/IGT_GLIOMA
tttttttttttteeesstttt/data/projects/ttt
Neuro_MRT_gNeuro-MRT genesis dataNCIGT-Harvard-BWH Neurosurgical Intraoperative Image Database GENESIS format dataPublic access neurosurgical cases made available by the Image Guided Therapy Program at Harvard-Brigham and Women's Hospital. This data was originally in GENESIS formatFerencJolesz/data/projects/Neuro_MRT_g
XTE_3XTE_3XTE_3XTE_3_Description/data/projects/XTE_3
NPTESTNipypeTestNipypeTestTest project to store nipype output./data/projects/NPTEST
BPBrain plasticity Combination training increases cognitive performance and modifies the brain resting state activity in healthy aging individualsfMRIStefano L.Sensi/data/projects/BP
NeuroMRTNeuro-MRT Image DatabaseNCIGT-Harvard-Brigham Neurosurgical Intraoperative Image DatabasePublic access neurosurgical cases made available by the Image Guided Therapy Program at Harvard-Brigham and Women's Hospital./data/projects/NeuroMRT
Sample_DICOMSample_DICOMSample DICOM dataset/data/projects/Sample_DICOM
NCIGT_PROSTATEBWH MRI ProstateProstate MRI DatabaseBWH MRI Prostate data. 10 datasets, including a derived segmentation series with labelmaps. FerencJolesz/data/projects/NCIGT_PROSTATE
NTNTNITRC Testthis is a test/data/projects/NT
VolatileVolatileVolatileitsnotme/data/projects/Volatile
AVZ_Slicer3MinAVZ_Slicer3MinAVZ_Slicer3MinuteTutorialGray scale image from Slicer 3 Minute Tutorial - with generated DICOM and nrrd files in reconstruction folderAlexanderZaitsev/data/projects/AVZ_Slicer3Min
TP_AbbrTest Project TitleTest ProjectMy_Description/data/projects/TP_Abbr
XTE_1XNAT_Test_Emory_1XNAT_Test_Emory_1/data/projects/XTE_1
XTE_2XNAT_Test_Emory_2XNAT_Test_Emory_2/data/projects/XTE_2
STSLObject identity mappingSpatiotemporal object identity mappingA collection of functional mri datasets used to map areas involved in individual-level object categorization/data/projects/STSL
MCICMCICThe Mind Clinical Imaging Consortium (MCIC): A Multisite MRI Study of Schizophrenia/data/projects/MCIC
PAPAPA/data/projects/PA
PBPBPB/data/projects/PB
TESTSGTESTSGTESTSG/data/projects/TESTSG
unknownunknownunknown/data/projects/unknown
DOT_fMRIDOT_fMRI_matched_datasetSubject matched Diffuse Optical Tomography and fMRI: language tasks and resting stateThis data set is composed of subject-matched data recorded non concurrently with Diffuse Optical Tomography (DOT) and fMRI. Task-based responses to four language tasks were recorded in five subjects. Resting state data was also collected in a set of eight subjects.JosephCulver/data/projects/DOT_fMRI
ADHD200ADHD200ADHD200FreeSurfer reconstructions of the ADHD200 data/data/projects/ADHD200
zip_testzip_testzip_testzip test/data/projects/zip_test
PROBEfMRI PROBEfMRI data for model PROBE experimentEtienneKoechlin/data/projects/PROBE
100RunsPerSubjWhole-brain activityWhole-brain, time-locked activation with simple tasks revealed using massive averaging and model-free analysisThis dataset contains anatomical, average of 100 functional runs and clustering results associated with the PNAS article of the same name as the project.JavierGonzalez-Castillo/data/projects/100RunsPerSubj
UploadUpload SampleUpload Sample/data/projects/Upload
surfmask_smplsurfmask_smplSurface masking samplesThe collection of structural T1 MRI scans from "Functional Data for Neurosurgical Planning" (IGT_FMRI_NEURO) project processed with surface obscuring algorithm./data/projects/surfmask_smpl
DCMPHANTOMDicomphantomsPhantom DICOM data/data/projects/DCMPHANTOM
HACKEDPROJECTHACKEDPROJECTHACKEDPROJECTAdded with CSRF attack from google.com/data/projects/HACKEDPROJECT
DTIChallenge12MICCAI2012 DTI ChallengeMICCAI 2012 DTI Tractography ChallengeMICCAI 2012 DTI Challenge 2nd EditionSoniaPujol/data/projects/DTIChallenge12
AgingAging_TAUBrain correlates of age related cognitive decline00/data/projects/Aging
XnatSlicerTest2XnatSlicerTest2XnatSlicerTest2/data/projects/XnatSlicerTest2
_DRC_test1_DRC_test1_DRC_test1_DRC_test1/data/projects/_DRC_test1
PlasticityBrain plasticityNeural mechanisms of brain plasticity with complex cognitive training in healthy seniors/data/projects/Plasticity
NIFTINIFTINIFTI/data/projects/NIFTI
HHumorHumor/data/projects/H
slicedropSlice:DropSlice:DropYo, drop tha slize!!!/data/projects/slicedrop
OrientationOrientationNeural Networks and OrientationfMRI data set on spatial orientation/data/projects/Orientation
OJNFCOJ, NFCOrange Juice, Not From ConcentrateTest 123/data/projects/OJNFC
testandaPAtestandaRTtestandaTAndaPacurar/data/projects/testandaPA
FOS_MMCFOS TaskFOS Task - Block DesignEllaGabitov/data/projects/FOS_MMC
PFSnovMRIfMRI episodic simulationFunctional MRI dataset of episodic simulation studyThis dataset contains functional MRI data investigating repetition in episodic simulation, and was made accessible to go along with a paper. Donna RoseAddis/data/projects/PFSnovMRI
MVPA_trueDecoding true answersDecoding subjectively true “Yes/No” thoughts in the human brain using fMRIHuman fMRI data for the paper "Decoding subjectively true “Yes/No” thoughts in the human brain using fMRI"ZhiYang/data/projects/MVPA_true
bistableBistable Perception fMRIBrain mechanisms for simple perception and bistable perception For details of this project, see Wang, Artega & He, PNAS 2013BiyuHe/data/projects/bistable
IXIIXIIXI/data/projects/IXI
XNATSlicerTestXNATSlicerTestXNATSlicerTest/data/projects/XNATSlicerTest
fMRI_DKfMRI decision-makingfMRI data for integration of rules and preferences in human decision-makingfMRI data for integration of rules and preferences in human decision-making Data acquired in Hospital Pitie SalpetriereEtienneKoechlin/data/projects/fMRI_DK
switchigdmnsnstate switchingAnticipatory processes in brain state switching Anticipatory processes in brain state switching (rest-to-task and task-to-rest) implicating the DMN and SN (rAI). JustinaSidlauskaite/data/projects/switchigdmnsn
MEG_fMRIMEG-fMRI IntegrationMEG-fMRI IntegrationRyanD'Arcy/data/projects/MEG_fMRI
fMRI_AD_mouseRS fMRI ArcAbeta mouseResting state fMRI and diffusion tensor imaging in a mouse model of cerebral amyloidosisArcAbeta mouse model of AD was studies in a cross-sectional design at 1, 2, 5, 8, 11, 19 and 21 months. Resting state fMRI and DTI was performed in isoflurane anesthetized mice using a 9.4T Biospec magnet, and a cryogenic surface reciever coil. For details, please refer to Grandjean et al. J.Neuro 2014JoanesGrandjean/data/projects/fMRI_AD_mouse
T1rhoFunctional T1rhoFunctional T1rho ImagingFunctional T1rho Imaging DataVincentMagnotta/data/projects/T1rho
testProject_00testProject_002testProject_002/data/projects/testProject_00
FramesocdiscFrame social discountingFraming effect on social discounting40 participants. FOR EACH PARTICIPANT THERE ARE TEN FOLDERS. SIX FOLDERS CONTAIN THE FIELDMAPS COLLECTED RIGHT BEFORE THE FUNCTIONAL RUNS (TWO 'GFM_SD_FRAME_1' BEFORE THE FIRST FUNCTIONAL RUNS; TWO 'GFM_SD_FRAME_2' BEFORE THE SECOND FUNCTIONAL RUNS; TWO 'GFM_SD_FRAME_3' BEFORE THE THIRD FUNCTIONAL RUNS). THREE FOLDERS CONTAIN THE FUNCTIONAL IMAGES (RUN 1='SD_FRAME_1'; RUN 2='SD_FRAME_2'; RUN 3='SD_FRAME_3'). ONE FOLDER CONTAINS STRUCTURAL IMAGES ('T1_MPR_32CH_ISO').ManuelaSellitto/data/projects/Framesocdisc
PRO123PRO123PRO123/data/projects/PRO123
PROJ234PROJ234PROJ234/data/projects/PROJ234
ISMRMRDISMRMRDISMRMRD PaperRaw data for the ISMRMRD manuscript.SouheilInati/data/projects/ISMRMRD
OlgaKotelkoOlga Kotelko's brainStructural MRI data of Olga Kotelko (1919-2014): a world-famous nonagenarian track and field athleteThis is the MRI data (DTI, anatomical, and T2-WI) of an exceptional nonagenarian Olga Kotelko (1919-2014), acquired in 2012 when she was 93. Olga began engaging in regular exercise after retiring at 65, trained for competitions since age of 77, and as of June 2014 held over 30 world records in her age category in track-and-field. https://en.wikipedia.org/wiki/Olga_Kotelko The data is published in Neurocase http://dx.doi.org/10.1080/13554794.2015.1074709AgnieszkaBurzynska/data/projects/OlgaKotelko
OutcomesAutism outcomes rs-fMRIResting-state functional connectivity predicts longitudinal change in autistic traits and adaptive functioning in autism31 resting-state fMRI and structural scans from individuals with Autism Spectrum Disorder. Outcome measures (ABAS and SRS scores) are included as well. AlexMartin/data/projects/Outcomes
CSD_MRI_MOUSECSD MouseChronic social defeat in mouseChronic social defeat (CSD) was performed over 15 days in mice. Animals were measured at baseline, and 1 day following the end of the paradigm. rs-fMRI, 3d anatomical, diffusion tensor imaging and spectroscopy were acquired. Spectroscopy was either performed in the right amygdala or in the prefrontal cortexJoanesGrandjean/data/projects/CSD_MRI_MOUSE
IPMSA_CSPIPMSA_CSPLongitudinal multicenter cervical spinal tract diffusion MRI for progressive MS/data/projects/IPMSA_CSP
nosetestsnosetestsnosetestsRandom_project_description_36/data/projects/nosetests
JRH_TestJRH TestJRH Test/data/projects/JRH_Test
PrjTestUploadPrjTestUploadPrjTestUpload_nameThis is a description for PrjTestUpload uploaded via RESTRaphaelEspanha /data/projects/PrjTestUpload
ins_d_qa_mriins_d_qa_mriins_d_qa_mriDaily MRI QA: INS. MRI Quality assurance data. /data/projects/ins_d_qa_mri
SHCFSSHCFSShangHai ChangFeng Study/data/projects/SHCFS
FCPFCPFCP/data/projects/FCP
SAFMDSA in FMDSelf agency in functional movement disordersIntramural NIH-funded study exploring the self-agency neural network in patients/controls with functional movement disorders.FattaNahab/data/projects/SAFMD
DemoProjectDemoProjectDemoProjectRaphaelEspanha/data/projects/DemoProject
DemoToXNATDemoToXNATDemoToXNAT/data/projects/DemoToXNAT
XnatProjectXnatProjectXnatProject/data/projects/XnatProject
MVPA_FEAT_CONJConjunctive CodingConjunctive coding of complex object features in human anterior temporal cortexJonathanErez/data/projects/MVPA_FEAT_CONJ
FCStateClassifFCvsCognitiveStateTracking ongoing cognition in individuals using brief, whole-brain functional connectivity patternsJavierGonzalez-Castillo/data/projects/FCStateClassif
RestFaceTMSRestFaceNetworkTMSThetaburst TMS to the posterior superior temporal sulcus disrupts resting-state fMRI connectivity across the face processing networkHumans recognize faces using a network of face-selective regions distributed across the brain. Neuropsychological patient studies demonstrate that focal damage to nodes in this network can impair face recognition, but such patients are rare. In the present study we simulated the effects of damage to the face network in neurologically normal human participants using thetaburst transcranial magnetic stimulation (TBS). Multi-echo functional magnetic resonance imaging (fMRI) was performed prior to and following TBS delivered over the face-selective right superior temporal sulcus (rpSTS), or a control site in the right motor cortex. TBS delivered over the rpSTS reduced resting-state connectivity across the extended face-processing network. This connectivity reduction was observed not only between the rpSTS and other face-selective areas, but also between non-stimulated face-selective areas across the ventral, medial and lateral brain surfaces (e.g. between the right amygdala and bilateral fusiform face areas and occipital face areas). TBS delivered over the motor cortex did not produce significant changes in resting-state connectivity across the face-processing network. These results demonstrate disrupting a single node in a brain network can impair the functional connectivity between the distributed nodes of that network that have not been directly stimulated. DanielHandwerker/data/projects/RestFaceTMS
nosetests3nosetests3nosetests3/data/projects/nosetests3
19081998hyab33: Phase 2 SSIPUndergraduate project: A Longitudinal Comparative Assessment of the Neurological Imaging Changes seen In Alzheimer’s Disease and AgingMedical student Phase 2 undergraduate research project at the Hull York Medical School/data/projects/19081998
fMRI_ane_mousefMRI anesthesia in miceResting-state anesthetic protocol comparison in miceBOLD Resting-state fMRI in mice were acquired on a 9.4T Bruker magnet using a 2x2 phased-array cryogenic coil. Anesthesia protocols are compared: Isoflurane 1%, Medetomidine 0.1mg/kg+0.2mg/kg/h, Medetomidine 0.05mg/kg+0.1mg/kg/h, Propofol 30 mg/kg, Urethane 1.5g/kg and Isoflurane 0.5% + Medetomidine 0.05mg/kg+0.1mg/kg/h combined. For details, see Grandjean, Schroeter et al. Neuroimage 2014JoanesGrandjean/data/projects/fMRI_ane_mouse
fMRI_AD_mouse2fMRI/MRI of APP tg linesfMRI/MRI phenotyping of 3 differnet APP transgenic mouse models of Alzheimer's disease3 different APP transgenic strains were investigated using resting-state fMRI, volumetric MRI, and diffusion weighted imaging. Each strain present different type of amyloid pathologies: E22{delta}A{beta} with Swedish mutation (K670N+M671L) and Osaka mutation (E693{delta}) presents only intracellular amyloid deposits. ArcA{beta} with Swedish mutation (K670N+M671L) and the Arctic mutation (E693G) presents intracellular amyloid deposits, parenchymal and vascular amyloid plaques. PSAPP with Swedish mutation (K670N+M671L) and PS1 {delta}E9 mutation presents parenchymal plaques. For details, see: Grandjean et al. Complex interplay between brain function and structure during cerebral amyloidosis in APP transgenic mouse strains revealed by multi-parametric MRI comparison , Neuroimage 2016JoanesGrandjean/data/projects/fMRI_AD_mouse2
Day3DataDay3DataDay3Data/data/projects/Day3Data
eTRIKSeTRIKS-ImagingOptimiseData repository for linking XNAT into eTRIKS repositoryMayYong/data/projects/eTRIKS
DIAGTREAThow doctors diagnoseHow doctors diagnose diseases and prescribe treatments: an fMRI investigation with primary care physiciansMarcioMelo/data/projects/DIAGTREAT
msimagingMS ImagingMultiple Sclerosis ImagingMayYong/data/projects/msimaging
zxj_projectzxj_projectzxj_project/data/projects/zxj_project
dcmsampledcmsampledcmsample/data/projects/dcmsample
6-OHDArsfMRI 6-OHDArsfMRI 6-OHDA/data/projects/6-OHDA
zxj1117zxj1117zxj1117/data/projects/zxj1117
L2strucBilingualism and brainEffects of bilingualism on brain structure and functionChristosPliatsikas/data/projects/L2struc
Project1234Raphael_TestRaphael_TestThis is some description for this beautiful projectRaphaelEspanha/data/projects/Project1234
GSP_testGSP_testGSP_test/data/projects/GSP_test
NDA_TESTNDA_TESTNDA_TEST/data/projects/NDA_TEST
GRAPPANoisek-space Noise AnalysisExact Calculation of Noise Maps and g-Factor in GRAPPA using a k–space AnalysisNoise characterization in MRI has multiple applications, including quality assurance and protocol optimization. It is particularly important in the presence of parallel imaging acceleration, where the noise distribution can contain severe spatial heterogeneities. If the parallel imaging reconstruction is a linear process, an exact noise analysis is possible by taking into account the correlations between all the samples involved. However, for k-space based techniques like GRAPPA, the exact analysis has been considered computationally prohibitive due to the very large size of the noise covariance matrices required to characterize the noise propagation from k-space to image-space. Previous methods avoid this computational burden by approximating the GRAPPA reconstruction as a pixel-wise linear operation performed in the image-space. However, these methods are not exact in the presence of non-uniform k-space undersampling (e.g.: containing a calibration region). For this reason, in this work we develop an exact characterization of the noise distribution for self-calibrated parallel imaging in the presence of arbitrary Cartesian undersampling patterns. By exploiting the symmetries and separability in the noise propagation process, the proposed method is computationally efficient and does not require large matrices. In this manuscript, we present the proposed noise characterization method and compare it to previous techniques using Monte-Carlo simulations as well as phantom acquisitions./data/projects/GRAPPANoise
nosetests4nosetests4nosetests4/data/projects/nosetests4
jh_sandboxsandboxsandbox/data/projects/jh_sandbox
NUDataSharingNUSDASTNU Schizophrenia Data and Software Tool Federation using BIRN Infrastructure (NUSDAST)-- To access data, please read and sign the Data Use Agreement: http://niacal.northwestern.edu/nusdast_accessors/new. -- All MR data are in AnalyzeTM format. The dataset includes high-resolution T1- (FLASH and MPRAGE) and T2- (TSE) weighted MR scans, in AnalyzeTM format. -- The clinical datasets include diagnosis, age, gender, parental socioeconomic status, as well as measures of the severity of psychopathology. -- Z-scored neurological test can be accessed here. Tasks are grouped into the following four domains: Working Memory, Episodic Memory, Executive Function, Crystallized Intelligence. From the NUDataSharing project page, click on “add tab” next to the “Subjects” tab at the bottom, and select “Neurocogs”. The spreadsheet can be downloaded by clicking “Options”>”Spreadsheet” on the right. -- Item-wide Neuropsychological test data are now accessible at http://schizconnect.org/, along with all imaging and clinical data. The battery of neuropsychological tests includes tasks relevant to prior studies of cognition in schizophrenia. Tasks are grouped into the following four domains: Working Memory, Episodic Memory, Executive Function, Crystallized Intelligence. -- The genotyping data will include BDNF (rs6265), EGFR (rs10228436), FGF-2 (rs1048201), and IL-3 (rs40401). -- Also, GWAS data is available for a subset of subjects: https://central.xnat.org/data/projects/NUDataSharing/resources/Genetics/files/130130_­NWProject_­Genotypes_­N=143_­NoFiltering-QC.­map https://central.xnat.org/data/projects/NUDataSharing/resources/Genetics/files/130130_­NWProject_­Genotypes_­N=143_­NoFiltering-QC.­ped -- This project was funded by the NIMH: 1R01 MH084803 -- This project makes available MR images, demographic, clinical, neurocognitive and genotype data from 139 subjects with schizophrenia and 136 control subjects. The dataset also includes manual segmentation for: Hippocampus, Amygdala, Thalamus, Basal Ganglia (caudate nucleus, nucleus accumbens, putamen, globus pallidus), Cingulate gyrus, include the anterior, posterior segments, Prefrontal cortex (including superior, middle and inferior gyri), and Parahippocampal gyrus (including entorhinal, perirhinal and parahippocampal cortices). LeiWang/data/projects/NUDataSharing
ME_epi_mouseME-EPI MouseMulti-echo gradient-echo EPI resting-state fMRI in miceA dataset of 14 multi-echo-epi scans of the mouse brain at rest, acquired at 9.4T with a 2x2 phased-array cryogenic reciever coil Study design and results are described in: Grandjean et al. Dynamic reorganization of intrinsic functional networks in the mouse brain, 2017, NeuroImageJoanesGrandjean/data/projects/ME_epi_mouse
CSD_ME_MOUSECPS ME mouseChronic psychosocial stress multi-echo EPI in mouseMulti-echo EPI fMRI acquired in mice at baseline and following Chronic Psychosocial Stress. Baseline consists of two scans acquired 30 minutes apart. Acquired at 9.4T with a 2x2 phased-array cryogenic reciever coil Study design and results are described in: Grandjean et al. Dynamic reorganization of intrinsic functional networks in the mouse brain, 2017, NeuroImageJoanesGrandjean/data/projects/CSD_ME_MOUSE
MIXPFC decision-makingPrefrontal mechanisms combining reward probabilities and values in human adaptive decision-makingEtienneKoechlin/data/projects/MIX
ASD_NFASD neurofeedbackDirect modulation of aberrant brain network connectivity through real-time neurofeedback17 patients with Autism Spectrum Disorder and 10 typically developing controls underwent 4 days of neurofeedback trainingAlexMartin/data/projects/ASD_NF
Raw_dual_echoeRaw_dual_echoesRaw_dual_echoesRaw_dual_echoesPei-YanLi/data/projects/Raw_dual_echoe
xnatpydemoxnatpydemoxnatpydemoRandom project description 76/data/projects/xnatpydemo
xnatPro2xnatPro2xnatPro2/data/projects/xnatPro2
CENTRAL_OASIS_CSOASIS_CSOasis Cross-Sectional StudiesSee www.oasis-brains.org for details.DanMarcus/data/projects/CENTRAL_OASIS_CS
OASIS3OASIS3OASIS3Data Use Agreement at ** www.oasis-brains.org ** ###### Details and Download scripts available at ** www.oasis-brains.org ** /data/projects/OASIS3
dMRI_Phant_MGHConnectome phantom dMRIA comprehensive diffusion MRI dataset acquired on the MGH Connectome scanner using a biomimetic brain phantomDiffusion microstructural imaging techniques have attracted great interest in the last decade due to their ability to quantify axon diameter and volume fraction in healthy and diseased human white matter. The estimates of compartment size and volume fraction continue to be debated, in part due to the lack of a gold standard for validation and quality control. In this work, we validate diffusion MRI estimates of compartment size and volume fraction using a novel textile axon (“taxon”) phantom constructed from hollow polypropylene yarns with distinct intra- and extra-taxonal compartments to mimic white matter in the brain. We acquired a comprehensive set of diffusion MRI measurements in the phantom using multiple gradient directions, diffusion times and gradient strengths on a human MRI scanner equipped with gradient strengths up to 300 mT/m. We recovered estimates of compartment size and restricted volume fraction through a straightforward extension of the AxCaliber/ActiveAx frameworks that enables estimation of mean compartment size in fiber bundles of arbitrary orientation. The voxel-wise taxon diameter estimates of 12.2 ± 0.9 um were close to the manufactured inner diameter of 11.8 ± 1.2 um. The estimated restricted volume fraction demonstrated an expected decrease in accordance with the known construction of decreasing packing density in the phantom. In conclusion, the compartment size and volume fraction estimates resulting from diffusion measurements on a human scanner were validated against ground truth in a phantom mimicking human white matter, providing confidence that this method can provide accurate estimates of parameters in simplified but realistic microstructural environments. Our work also demonstrates the importance of a biologically analogous phantom that can be applied to validate a variety of diffusion microstructural imaging methods in human scanners and be used for standardization of diffusion MRI protocols for neuroimaging research.QiuyunFan/data/projects/dMRI_Phant_MGH
CENTRAL_OASIS_LONGOASIS_LONGOASIS Longitudinal StudiesThe Open Access Series of Imaging Studies (OASIS) is a series of MRI data sets that is publicly available for study and analysis. The present data set consists of a longitudinal collection of 151 subjects aged 60 to 98. Each subject was scanned on two or more visits, separated by at least one year. All subjects were characterized using the Clinical Dementia Rating (CDR) are either nondemented or with very mild to mild dementia of the Alzheimer’s type (DAT). 77 of the subjects were characterized as nondemented at the time of each of their visits. 64 of the included subjects were characterized as demented at the time of their initial visits and remained so for subsequent scans. Another 10 subjects were characterized as nondemented at the time of their initial visit and were subsequently characterized as demented at the time of one or more later visits. The subjects were all right-handed and include both men (n=62) and women (n=89). For each scanning session, 3 or 4 individual T1-weighted MRI scans were obtained. Multiple within-session acquisitions provide extremely high contrast-to-noise making the data amenable to a wide range of analytic approaches including automated computational analysis. Automated calculation of whole brain volume and estimated total intracranial volume are presented to demonstrate use of the data for measuring differences associated with normal aging and Alzheimer’s disease. /data/projects/CENTRAL_OASIS_LONG
xnatDownloadxnatDownloadxnatDownloadAutomated testing of software./data/projects/xnatDownload
TractoArcuate and SLF TractsConnections between temporo-parietal and frontal brain areasReconstruction and better defining the Arcuate and Superior Longitudinal fasciculiMichaelPetrides/data/projects/Tracto
SoyassaAcute Mild ExerciseAcute Mild ExerciseHideakiSoya/data/projects/Soyassa