Database of human brain images derived from a realistic phantom and generated using a sophisticated MRI simulator. Custom simulations may be generated to match a user's selected parameters. The goal is to aid validation of computer-aided quantitative analysis of medical image data. The SBD contains a set of realistic MRI data volumes produced by an MRI simulator. These data can be used by the neuroimaging community to evaluate the performance of various image analysis methods in a setting where the truth is known. The SBD contains simulated brain MRI data based on two anatomical models: normal and multiple sclerosis (MS). For both of these, full 3-dimensional data volumes have been simulated using three sequences (T1-, T2-, and proton-density- (PD-) weighted) and a variety of slice thicknesses, noise levels, and levels of intensity non-uniformity. These data are available for viewing in three orthogonal views (transversal, sagittal, and coronal), and for downloading.

Preliminary database of neuroanatomical connectivity reports specifically for the human brain, which have been manually curated. It includes details (based on manual literature curation) of tract tracing or related connectivity studies conducted in human brain tissue. This database and user interface will be expanded and improved in the near future.

The Brain Imaging and Neurophysiology Database (BIND) represents one of the largest multi-institutional, multimodal neuroimaging repositories, comprising 1.8 million brain scans from 38,945 subjects linked to neurophysiological recordings. This comprehensive dataset addresses critical limitations in neuroimaging research by providing unprecedented scale and diversity across pathologies and healthy controls. BIND integrates de-identified data from three major academic medical centers -- Massachusetts General Hospital, Brigham and Women's Hospital, and Stanford University Medical Center -- including 1,724,300 MRI scans (1.5T, 3T, and 7T), 54,154 CT scans, 5,720 PET scans, and 655 SPECT scans, converted to standardized NIfTI format following BIDS organization. The database spans the full age spectrum and encompasses diverse neurological conditions alongside healthy subjects. We deployed Bio-Medical Large Language Models to extract structured clinical metadata from 84,960 associated radiology reports, categorizing findings into standardized pathology classifications. All imaging data are linked to previously published EEG and polysomnography recordings from the Harvard Electroencephalography Database and Human Sleep Project, enabling unprecedented multimodal analyses. BIND is freely accessible for academic research through the Brain Data Science Platform (https://bdsp.io/). This resource facilitates large-scale neuroimaging studies, machine learning applications, and multimodal brain research to accelerate discoveries in clinical neuroscience.

Brain methods

This resource provides comprehensive spatial profiling of the Brain, including overview of protein expression in the mammalian brain based on integration of data from human, pig and mouse. Transcriptomics data combined with affinity-based protein in situ localization down to single cell detail is available in this brain-centric sub atlas of the Human Protein Atlas. The data presented are for human genes and their one-to-one orthologues in pig and mouse. Gene summary pages provide the hierarchical expression landscape form 13 main regions of the brain to individual nuclei and subfields for every protein coding gene. For selected proteins, high content images are available to explore the cellular and subcellular protein distribution. In addition, the Brain resource contains lists of genes with elevated expression in one or a group of regions to help the user identify unique protein expression profiles linked to physiology and function. 

More information about the specific content and the generation and analysis of the data in this resource can be found on the Methods Summary. Learn about:

Expression levels for all human proteins in regions and subregions of the human brain Expression levels for all proteins with human orthologs in regions and subregions of the pig and mouse brain Brain enriched genes with higher expression in any of the regions of the brain compared to peripheral organs Regional enriched genes with higher expression in a single or few regions of the brain Cell-type and cell-compartment distribution of selected proteins in the human and mouse brain Differences in gene expression between mammalian species

Additional information: In addition to the data provided in the brain resource there is also data on human retina and single cell data containing information on protein expression in human neuronal and non-neuronal cell-types in the central nervous system.

A database to support research on drugs for the treatment of different neurological disorders. It contains agents that act on neuronal receptors and signal transduction pathways in the normal brain and in nervous disorders. It enables searches for drug actions at the level of key molecular constituents, cell compartments and individual cells, with links to models of these actions.

Dataset provides 22 axial thin slice CTA images along with their brain mask in NIFTI format. These image pairs will be grouped in folders named after their 'Case ID.' The CTA images will be named 'CaseID.nii.gz,' and their respective brain masks will be 'CaseID_ROI.nii.gz. The brain masks will have either “0” or “1” as the intensity with “1” representing brain region. Example: Let us consider “Anon1” as the case id. The CTA image and its mask for case id “Anon1” will be named as “Anon1.nii.gz” and “Anon1_ROI.nii.gz” respectively and they will be present inside a folder called “Anon1”.

Dataset

This dataset was created by MD. Nahid Hasan

Released under CC0: Public Domain

Contents

Comprehensive three-dimensional digital atlas database of the C57BL/6J mouse brain based on magnetic resonance microscopy images acquired on a 17.6-T superconducting magnet. This database consists of: Individual MRI images of mouse brains; three types of atlases: individual atlases, minimum deformation atlases and probabilistic atlases; the associated quantitative structural information, such as structural volumes and surface areas. Quantitative group information, such as variations in structural volume, surface area, magnetic resonance microscopy image intensity and local geometry, have been computed and stored as an integral part of the database. The database augments ongoing efforts with other high priority strains as defined by the Mouse Phenome Database focused on providing a quantitative framework for accurate mapping of functional, genetic and protein expression patterns acquired by a myriad of technologies and imaging modalities. You must register First (Mandatory) and then you may Download Images and Data.

IntroductionBrain-wide mRNA mappings offer a great potential for neuroscience research as they can provide information about system proteomics. In a previous work we have correlated mRNA maps with the binding patterns of radioligands targeting specific molecular systems and imaged with positron emission tomography (PET) in unrelated control groups. This approach is potentially applicable to any imaging modality as long as an efficient procedure of imaging-genomic matching is provided. In the original work we considered mRNA brain maps of the whole human genome derived from the Allen human brain database (ABA) and we performed the analysis with a specific region-based segmentation with a resolution that was limited by the PET data parcellation. There we identified the need for a platform for imaging-genomic integration that should be usable with any imaging modalities and fully exploit the high resolution mapping of ABA dataset.AimIn this work we present MENGA (Multimodal Environment for Neuroimaging and Genomic Analysis), a software platform that allows the investigation of the correlation patterns between neuroimaging data of any sort (both functional and structural) with mRNA gene expression profiles derived from the ABA database at high resolution.ResultsWe applied MENGA to six different imaging datasets from three modalities (PET, single photon emission tomography and magnetic resonance imaging) targeting the dopamine and serotonin receptor systems and the myelin molecular structure. We further investigated imaging-genomic correlations in the case of mismatch between selected proteins and imaging targets.

Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) is currently one of the powerful tools for the clinical diagnosis of dementia such as Alzheimer's Disease (AD). Meanwhile, MR imaging, being non-radioactive and having high contrast resolution, is highly accessible in clinical settings. Therefore, this dataset intends to use FDG-PET images as the Ground Truth for evaluating AD, for the development of predicting AD patients using MR images. This dataset includes an AD group and a control group (Healthy Group). The determination of the image diagnosis group is made by neurology specialists based on comprehensive judgment using clinically relevant information. Each set of data contains one set of MRI T1 images and one set of FDG-PET images. The image format is DICOM, and all images have been anonymized. To obtain the clinical information and related documentation, please contact the administrator.

Group average map of FLAIR images in standard MNI space across 1,832 MRiShare subjects.

Collection description

This collection contains group average maps presented in the associated publication "The MRi-Share database: brain imaging in a cross-sectional cohort of 1,870 university students".

Subject species

homo sapiens

Modality

Structural MRI

Analysis level

group

Cognitive paradigm (task)

None / Other

Map type

A

Group average map of cortical thickness in fsaverage space across 1,832 MRiShare subjects.

Collection description

This collection contains group average maps presented in the associated publication "The MRi-Share database: brain imaging in a cross-sectional cohort of 1,870 university students".

Subject species

homo sapiens

Modality

Structural MRI

Analysis level

group

Cognitive paradigm (task)

None / Other

Map type

A

We report on MRi-Share, a multi-modal brain MRI database acquired in a unique sample of 1,870 young healthy adults, aged 18 to 35 years, while undergoing university-level education. MRi-Share contains structural (T1 and FLAIR), diffusion (multispectral), susceptibility weighted (SWI), and resting-state functional imaging modalities. Here, we described the contents of these different neuroimaging datasets and the processing pipelines used to derive brain phenotypes, as well as how quality control was assessed. In addition, we present preliminary results on associations of some of these brain image-derived phenotypes at the whole brain level with both age and sex, in the subsample of 1,722 individuals aged less than 26 years. We demonstrate that the post-adolescence period is characterized by changes in both structural and microstructural brain phenotypes. Grey matter cortical thickness, surface area and volume were found to decrease with age, while white matter volume shows increase. Diffusivity, either radial or axial, was found to robustly decrease with age whereas fractional anisotropy only slightly increased. As for the neurite orientation dispersion and densities, both were found to increase with age. The isotropic volume fraction also showed a slight increase with age. These preliminary findings emphasize the complexity of changes in brain structure and function occurring in this critical period at the interface of late maturation and early aging.

Atlas of magnetic resonance images and histological sections of a Japanese monkey brain, Rhesus monkey and human. The Brain Explorer allows for display, magnification, and comparison these images. Other formats include a collection of .jpg images, Quicktime VR (allow user to zoom in), and EmonV, a voxel viewer for MacOS X.

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 08, 2011. This database contains gene expression data for various physiological and pathological processes in mouse brain. All the data have been obtained by adaptor-tagged competitive PCR, an advanced version of quantitative PCR. Brain Gene Expression Database (BGED) contains gene expression data for various physiological and pathological processes in mouse brain. All the data have been obtained by adaptor-tagged competitive PCR, an advanced version of quantitative PCR. Manual Download 1. Data retrieval Gene expression data can be retrieved either by ID numbers or by keywords representing functional annotations from this page. The ID numbers include GenBank, RefSeq, SwissProt, Gene Ontology, and BED (our own ID). The keyword search is based either on definition in GenBank, SwissProt and RefSeq, functional annotation of SwissProt database, or Gene Ontology terms. 2. Gene expression pattern display * Display of multiple gene expression patterns. Expression patterns of multiple genes selected by the keyword search can be displayed from the result page of the keyword search. * Gene expression pattern similarity search This function is available on the information page of each gene accessed through BED ID (in-house ID).

The HIV Brain Sequence Database (HIVBrainSeqDB) is a public database of HIV envelope sequences, directly sequenced from brain and other tissues from the same patients. For inclusion in the database, sequences must: (i) be deposited in Genbank; (ii) include some portion of the HIV env region; (iii) be clonal, amplified directly from tissue; and (iv) be sampled from the brain, or sampled from a patient for which the database already contains brain sequence. Sequences are annotated with clinical data including viral load, CD4 count, antiretroviral status, neurocognitive impairment, and neuropathological diagnosis, all curated from the original publication. Tissue source is coded using an anatomical ontology, the Foundational Model of Anatomy, to capture the maximum level of detail available, while maintaining ontological relationships between tissues and their subparts. 44 tissue types are represented within the database, grouped into 4 categories: (i) brain, brainstem, and spinal cord; (ii) meninges, choroid plexus, and CSF; (iii) blood and lymphoid; and (iv) other (bone marrow, colon, lung, liver, etc). Currently, the database contains 2517 envelope sequences from 90 patients, obtained from 22 published studies. 1272 sequences are from brain; the remaining 1245 are from blood, lymph node, spleen, bone marrow, colon, lung and other non-brain tissues. The database interface utilizes a faceted interface, allowing real-time combination of multiple search parameters to assemble a meta-dataset, which can be downloaded for further analysis. This online resource will greatly facilitate analysis of the genetic aspects of HIV macrophage tropism, HIV compartmentalization and evolution within the brain and other tissue reservoirs, and the relationship of these findings to HIV-associated neurological disorders and other clinical consequences of HIV infection.

Collection of neuroanatomically labeled MRI brain scans, created by neuroanatomical experts. Regions of interest include the sub-cortical structures (thalamus, caudate, putamen, hippocampus, etc), along with ventricles, brain stem, cerebellum, and gray and white matter and sub-divided cortex into parcellation units that are defined by gyral and sulcal landmarks.

Overview

Functional Magnetic Resonance Imaging (fMRI) has opened the door to brain mapping of perceptual, motor, or cognitive functions. As such, it provides an instrumental basis for the whole field of cognitive neuroimag- ing. However, there exists to date no data collection that systematically maps representations for a wide-variety of mental functions at a fine spa- tial scale. The Individual Brain Charting (IBC) project is collecting a high-resolution multi-task-fMRI dataset, to provide an objective basis for a comprehensive atlas of brain responses. The data refer to a cohort of twelve participants performing many different tasks. Acquiring a large amount of tasks on the same subjects yields a precise mapping of the underlying functions, free from both inter-subject and inter-site variabil- ity. Additionally, the dataset comes with high-resolution anatomical and diffusion images, to achieve a fine anatomical characterization of these brains.

Dataset content overview

This is an overview of the dataset content.

More information and updates are available at http://project.inria.fr/IBC/

The data in release 1 are organized as follows:

./task*.json: Descritpion of the tasks used in this release ./participants.tsv Description of the participants ./sub-XX subject directories ./sub-XX/ses-YY session directories

Note that there are many sessions per subject and that the session are numbered according to acquisition date, which yields different actual acquisitions depending on the subjects. The data are thus much better by the MRI file names, than by session id.

Session directories comprise the following subdirectories: * anat/ for T1w-, T2w- and flair image * dwi/ for diffusion-weighted data * fmap/ for field maps * func/ for functional data

Note that diffusion-weighted, T2-weighted and FLAIR images are not meant to be used for advanced neuroimaging investigations. They were acquired to check the absence of conspicuos abnormalities at screening stage. High-resolution anatomical and diffusion-weighted images will be procided in the future.

Regarding functional data, the file naming conventions is sub-XX_ses-YY_task-ZZZ_acq-AA_bold.nii.gz, where * XX is the subject id * YY is the session id * ZZZ is one of the twelve tasks used * 'AA' is either ap pa, corresponding to the phase encoding direction

These fMRI files are provided together with sub-XX_ses-YY_task-ZZZ_acq-AA_events.tsv files, that describe the corresponding events.

In the same folder, the 'ap' and 'pa' variant of a given acquisition are always found. the corresponding fiel maps are available in the fmap folder to correct distortions. test-retest or fixed effectsmodels can be computed across the corresponding data after suitable preprocessing.

More information and material

The functional protocols used can be dowloaded at: https://github.com/hbp-brain-charting/public_protocols

Analysis scripts can be found at: https://github.com/hbp-brain-charting/public_analysis_code

Contact

Bertrand Thirion, bertrand.thirion@inria.fr

Comments added by Openfmri Curators

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General Comments

Defacing

The submitter defaced all the T1w anatomical images. We used pydeface to deface the rest of the anatomical images, excluding acq-tse_T2w.nii.gz which did not need to be defaced. The code can be found at https://github.com/poldracklab/pydeface

Quality Control

MRIQC output could not be included at this time. It will be added to the next revision.

Where to discuss the dataset

1) www.openfmri.org/dataset/ds000244/ See the comments section at the bottom of the dataset page. 2) www.neurostars.org Please tag any discussion topics with the tags openfmri and ds000244. 3) Send an email to submissions@openfmri.org. Please include the accession number in your email.

Known Issues

pixdim7 for all bold images is very large (ranging from 32406.267578 to 67769.250000)

Brain structures measured in the BRAIN database.

The Harvard EEG Database will encompass data gathered from four hospitals affiliated with Harvard University:Massachusetts General Hospital (MGH), Brigham and Women's Hospital (BWH), Beth Israel Deaconess Medical Center (BIDMC), and Boston Children's Hospital (BCH).