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http://www.nia.nih.gov/research/intramural-research-program/dynamics-health-aging-and-body-composition-health-abc

A study that characterizes the extent of change in body composition in older men and women, identifies clinical conditions accelerating these changes, and examines the health impact of these changes on strength, endurance, disability, and weight-related diseases of old age. The study population consists of 3,075 persons age 70-79 at baseline with about equal numbers of men and women. Thirty-three percent of the men are African-Americans as are 46% of the women. All persons in the study were selected to be free of disability in activities of daily living and free of functional limitation (defined as any difficulty walking a quarter of a mile or any difficulty walking up 10 steps without resting) at baseline. The core yearly examination for HEALTH ABC includes measurement of body composition by dual energy x-ray absorptio��������metry (DXA), walking ability, strength, an interview that includes self-report of limitations, a medication survey, and weight (Measurements in the Health ABC Study). Provision has been made for banking of blood specimens and extracted DNA (HealthABC repository). Study investigators are open to collaboration especially for measures focused on obesity and associated weight-related health conditions including osteoporosis, osteoarthritis, pulmonary function, cardiovascular disease, vascular disease, diabetes and glucose intolerance, and depression. The principal goals of the HEALTH ABC are: # To assess the association of baseline body weight, lean body mass, body fat, and bone mineral content, in relation to weight history, with: incident functional limitation; incidence and change in severity of weight-related health conditions; recovery of physical function after an acute event; baseline measures of strength, fitness and physical performance; gender, ethnicity and socioeconomic status # To access the contribution of episodes of severe acute illness in healthier older persons to changes in body weight, bone mineral content, lean body mass and body fat, and the relationship of these episodes to risk of functional limitation and recovery. # To assess the impact of weight-related co-morbid illness on the risk of functional limitation and recovery. # To assess the ways in which physiologic mediators of change in body composition influence and are influenced by changes in health in older adults and contribute to change in body composition; to understand how changes in body composition affect weight-related cardiovascular disease risk factors such as lipids, blood pressure and glucose tolerance. # To assess the interdependency of behavioral factors, such as nutrition and physical activity, co-morbid health conditions, and their association with change in body composition in old age. # To provide a firm scientific basis for understanding issues related to weight recommendations in old age through increased knowledge of the potential trade-offs between weight and risk of functional limitation, disability, morbidity and death; to provide information critical for developing effective strategies for the maintenance of health in older persons.

Proper citation: Dynamics of Health Aging and Body Composition (Health ABC) (RRID:SCR_008813) Copy   

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http://fcon_1000.projects.nitrc.org/indi/pro/BeijingShortTR.html

Dataset of resting state fMRI scans obtained using two different TR's in healthy college-aged volunteers. Specifically, for each participant, data is being obtained with a short TR (0.4 seconds) and a long TR (2.0 seconds). In addition this dataset contains a 64-direction DTI scan for every participant. The following data are released for every participant: * 8-minute resting-state fMRI scan (TR = 2 seconds, # repetitions = 240) * 8-minute resting-state fMRI scans (TR = 0.4 seconds, # repetitions = 1200) * MPRAGE anatomical scan, defaced to protect patient confidentiality * 64-direction diffusion tensor imaging scan (2mm isotropic) * Demographic information

Proper citation: Beijing: Short TR Study (RRID:SCR_003502) Copy   

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http://www.physionet.org/physiobank/database/sleep-edf/

Sleep EEG dataset from 8 subjects in European Data Format (EDF) including original recordings and their hypnograms as described in B Kemp, AH Zwinderman, B Tuk, HAC Kamphuisen, JJL Obery��. Analysis of a sleep-dependent neuronal feedback loop: the slow-wave microcontinuity of the EEG. IEEE-BME 47(9):1185-1194 (2000). The recordings were obtained from Caucasian males and females (21 - 35 years old) without any medication; they contain horizontal EOG, FpzCz and PzOz EEG, each sampled at 100 Hz. The sc* recordings also contain the submental-EMG envelope, oro-nasal airflow, rectal body temperature and an event marker, all sampled at 1 Hz. The st* recordings contain submental EMG sampled at 100 Hz and an event marker sampled at 1 Hz. The 4 sc* recordings were obtained in 1989 from ambulatory healthy volunteers during 24 hours in their normal daily life, using a modified cassette tape recorder. The 4 st* recordings were obtained in 1994 from subjects who had mild difficulty falling asleep but were otherwise healthy, during a night in the hospital, using a miniature telemetry system with very good signal quality.

Proper citation: Sleep-EDF Database (RRID:SCR_006976) Copy   

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http://snyderome.stanford.edu/

Data set generated by personal omics profiling of Dr. Michael Snyder at Stanford University. It combines genomic, transcriptomic, proteomic, metabolomic, and autoantibody profiles from a single individual over a 14 month period. The analysis revealed various medical risks, including type II diabetes. It also uncovered extensive, dynamic changes in diverse molecular components and biological pathways across healthy and diseased conditions.

Proper citation: iPOP (RRID:SCR_008991) Copy   

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http://irc.cchmc.org/software/pedbrain.php

Brain imaging data collected from a large population of normal, healthy children that have been used to construct pediatric brain templates, which can be used within statistical parametric mapping for spatial normalization, tissue segmentation and visualization of imaging study results. The data has been processed and compiled in various ways to accommodate a wide range of possible research approaches. The templates are made available free of charge to all interested parties for research purposes only. When processing imaging data from children, it is important to take into account the fact that the pediatric brain differs significantly from the adult brain. Therefore, optimized processing requires appropriate reference data be used because adult reference data will introduce a systematic bias into the results. We have shown that, in the in the case of spatial normalization, the amount of non-linear deformation is dramatically less when a pediatric template is used (left, see also HBM 2002; 17:48-60). We could also show that tissue composition is substantially different between adults and children, and more so the younger the children are (right, see also MRM 2003; 50:749-757). We thus believe that the use of pediatric reference data might be more appropriate.

Proper citation: CCHMC Pediatric Brain Templates (RRID:SCR_003276) Copy   

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http://www.pediatricmri.nih.gov/

Data sets of clinical / behavioral and image data are available for download by qualified researchers from a seven year, multi-site, longitudinal study using magnetic resonance technologies to study brain maturation in healthy, typically-developing infants, children, and adolescents and to correlate brain development with cognitive and behavioral development. The information obtained in this study is expected to provide essential data for understanding the course of normal brain development as a basis for understanding atypical brain development associated with a variety of developmental, neurological, and neuropsychiatric disorders affecting children and adults. This study enrolled over 500 children, ranging from infancy to young adulthood. The goal was to study each participant at least three times over the course of the project at one of six Pediatric Centers across the United States. Brain MR and clinical/behavioral data have been compiled and analyzed at a Data Coordinating Center and Clinical Coordinating Center. Additionally, MR spectroscopy and DTI data are being analyzed. The study was organized around two objectives corresponding to two age ranges at the time of enrollment, each with its own protocols. * Objective 1 enrolled children ages 4 years, 6 months through 18 years (total N = 433). This sample was recruited across the six Pediatric Study Centers using community based sampling to reflect the demographics of the United States in terms of income, race, and ethnicity. The subjects were studied with both imaging and clinical/behavioral measures at two year intervals for three time points. * Objective 2 enrolled newborns, infants, toddlers, and preschoolers from birth through 4 years, 5 months, who were studied three or more times at two Pediatric Study Centers at intervals ranging from three months for the youngest subjects to one year as the children approach the Objective 1 age range. Both imaging and clinical/behavioral measures were collected at each time point. Participant recruitment used community based sampling that included hospital venues (e.g., maternity wards and nurseries, satellite physician offices, and well-child clinics), community organizations (e.g., day-care centers, schools, and churches), and siblings of children participating in other research at the Pediatric Study Centers. At timepoint 1, of those enrolled, 114 children had T1 scans that passed quality control checks. Staged data release plan: The first data release included structural MR images and clinical/behavioral data from the first assessments, Visit 1, for Objective 1. A second data release included structural MRI and clinical/behavioral data from the second visit for Objective 1. A third data release included structural MRI data for both Objective 1 and 2 and all time points, as well as preliminary spectroscopy data. A fourth data release added cortical thickness, gyrification and cortical surface data. Yet to be released are longitudinally registered anatomic MRI data and diffusion tensor data. A collaborative effort among the participating centers and NIH resulted in age-appropriate MR protocols and clinical/behavioral batteries of instruments. A summary of this protocol is available as a Protocol release document. Details of the project, such as study design, rationale, recruitment, instrument battery, MRI acquisition details, and quality controls can be found in the study protocol. Also available are the MRI procedure manual and Clinical/Behavioral procedure manuals for Objective 1 and Objective 2.

Proper citation: NIH MRI Study of Normal Brain Development (RRID:SCR_003394) Copy   

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http://www.theearlab.org

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 13, 2026. Computationally oriented experimental laboratory interested in the encoding of auditory information in the cerebral cortex and brainstem, and in the mechanisms of tinnitus and the effect of various drugs (Lidocaine, steroids, anti-oxidants) in relieving noise trauma induced tinnitus. The ferret (Mustela putorius) and the rat serve as their system model. Through chronic implants, they obtain electrophysiological data from awake behaving animals in order to investigate the response properties and functional organization of the auditory system, both in health and after noise trauma that induces tinnitus in rats. Projects: * Response Modulation to Ongoing Broadband Sounds in Primary Auditory Cortex * Neuronal Response Characteristics in the Inferior Colliculus of the Awake Ferret and Rat * Spectro-Temporal Representation of Feature Onsets in Primary Auditory Cortex * Targeting the changes in inferior colliculus induced by tinnitus

Proper citation: Ear Lab (RRID:SCR_002531) Copy   

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https://simtk.org/home/cv-gmodels

Repository of geometric models collected from on-going and past research projects in the Cardiovascular Biomechanics Research Laboratory at Stanford University. The geometric models are mostly built from imaging data of healthy and diseased individuals. For each of the models, a short description is given with a reference. The geometric models are in VTK PolyData XML .vtp format. * Audience: Biomechanical and computational researchers interested in complex models of cardiovascular applications * Long Term Goals and Related Uses: Allow users to download geometric models for cardiovascular applications. These geometric models can be used for research purposes, such as meshing and scientific visualization. Users are welcome to contact the project administrator, join the project and contribute additional models.

Proper citation: Cardiovascular Model Repository (RRID:SCR_002679) Copy   

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http://brain-development.org/ixi-dataset/

Data set of nearly 600 MR images from normal, healthy subjects, along with demographic characteristics, collected as part of the Information eXtraction from Images (IXI) project available for download. Tar files containing T1, T2, PD, MRA and DTI (15 directions) scans from these subjects are available. The data has been collected at three different hospitals in London: * Hammersmith Hospital using a Philips 3T system * Guy''s Hospital using a Philips 1.5T system * Institute of Psychiatry using a GE 1.5T system

Proper citation: IXI dataset (RRID:SCR_005839) Copy   

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https://www.researchmatch.org/

Free and secure registry to bring together two groups of people who are looking for one another: (1) people who are trying to find research studies, and (2) researchers who are looking for people to participate in their studies. It has been developed by major academic institutions across the country who want to involve you in the mission of helping today''''s studies make a real difference for everyone''''s health in the future. Anyone can join ResearchMatch. Many studies are looking for healthy people of all ages, while some are looking for people with specific health conditions. ResearchMatch can help ''''match'''' you with any type of research study, ranging from surveys to clinical trials, always giving you the choice to decide what studies may interest you.

Proper citation: ResearchMatch (RRID:SCR_006387) Copy   

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http://www.rls.org/Page.aspx?pid=540

The Restless Legs Syndrome Foundation established the RLS Foundation Brain Bank at the Harvard Brain Tissue Resource Center in 2000. A part of the Harvard University medical system, the Center (housed at McLean Hospital and commonly referred to as The Brain Bank) began in 1978 as a centralized resource for the collection and distribution of human brain specimens for research and diagnostic studies. Over the years, hundreds of scientists from the nation''s top research and medical centers have requested tissue from The Brain Bank for their investigations. Because most of these studies can be carried out on a very small amount of tissue, each donated brain provides a large number of samples for many researchers. For comparative purposes, brain tissue is needed from healthy individuals, as well as from those who had RLS. When possible, a small portion of frozen tissue taken from each brain donated to the RLS Foundation Collection will be kept available to serve as a resource for future genetic testing. The process of donating your brain to RLS research is broken down into 5 steps. To view these steps, please read our Process Steps in RLS Brain Tissue Collection. To read about the process of donating brain tissue for research, visit our Brain Bank Tissue Donation page.

Proper citation: RLS Foundation Brain Bank (RRID:SCR_005089) Copy   

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http://humanconnectome.org/

Consortium to comprehensively map long-distance brain connections and their variability. It is acquiring data and developing analysis pipelines for several modalities of neuroimaging data plus behavioral and genetic data from healthy adults.

Proper citation: Human Connectome Coordination Facility (RRID:SCR_008749) Copy   

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http://www.mssm.edu/research/centers/alzheimers-disease-research-center/

A research facility and clinical program that is dedicated to the study and the treatment of both normal aging and Alzheimer's disease. This facility will accommodate requests for its resources (for example, data or tissue) from investigators that are not funded by the ADRC. Their team is composed of experts in geriatrics, geriatric psychiatry and psychology, neurology, pathology, and radiology. All team members work to provide services to those with memory disorders. This center sponsors educational programs for healthcare professionals and community groups. Data from the ADRC cores are available to all ADRC investigators after approval from the PI who collected the data. Data generated by the ADRC cores are communicated to the National Alzheimer's Coordinating Center (NACC) and can be available through them. Tissue can be distributed after approval of the Tissue Allocation Committee, and can be used for further research.

Proper citation: Mount Sinai Alzheimer's Disease Research Center (RRID:SCR_008780) Copy   

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http://physionet.org/physiobank/

Archive of well-characterized digital recordings of physiologic signals and related data for use by the biomedical research community. PhysioBank currently includes databases of multi-parameter cardiopulmonary, neural, and other biomedical signals from healthy subjects and patients with a variety of conditions with major public health implications, including sudden cardiac death, congestive heart failure, epilepsy, gait disorders, sleep apnea, and aging. The PhysioBank Archives now contain over 700 gigabytes of data that may be freely downloaded. PhysioNet is seeking contributions of data sets that can be made freely available in PhysioBank. Contributions of digitized and anonymized (deidentified) physiologic signals and time series of all types are welcome. If you have a data set that may be suitable, please review PhysioNet''s guidelines for contributors and contact them.

Proper citation: Physiobank (RRID:SCR_006949) Copy   

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http://www.hbpp.org/

An open international project under the patronage of the Human Proteome Organisation (HUPO) that aims: To analyze the brain proteome of human as well as mouse models in healthy, neurodiseased and aged status with focus on Alzheimer's and Parkinson's Disease; To perform quantitative proteomics as well as complementary gene expression profiling on disease-related brain areas and bodily fluids; To advance knowledge of neurodiseases and aging in order to push new diagnostic approaches and medications; To exchange knowledge and data with other HUPO projects and national / international initiatives in the neuroproteomic field; To make neuroproteomic research and its results available in the scientific community and society. Recent work has shown that standards in proteomics and especially in bioinformatics are mandatory to allow comparable analyses, but still missing. To address this challenge, the HUPO BPP is closely working together with the HUPO Proteome Standards Initiative (HUPO PSI).

Proper citation: HUPO Brain Proteome Project (RRID:SCR_007302) Copy   

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http://dgv.tcag.ca/

Collection of curated structural variation in the human genome. Catalogue of human genomic structural variation identified in healthy control samples for studies aiming to correlate genomic variation with phenotypic data. It is continuously updated with new data from peer reviewed research studies. The Database is no longer accepting direct submission of data as they are currently part of a collaboration with two new archival CNV databases at EBI and NCBI, called DGVa and dbVAR, respectively. One of the changes to DGV as part of this collaborative effort is that they will no longer be accepting direct submissions, but rather obtain the datasets from DGVa (short for DGV archive). This will ensure that the three databases are synchronized, and will allow for an official accessioning of variants.

Proper citation: Database of Genomic Variants (RRID:SCR_007000) Copy   

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http://www.nimh.nih.gov/labs-at-nimh/research-areas/research-support-services/hbcc/index.shtml

A collection of brain tissue from individuals suffering from schizophrenia, bipolar disorder, depression, anxiety disorders, and substance abuse, as well as healthy individuals. The research mission of the NIMH Brain Bank is to better understand the underlying biological mechanisms and pathways that contribute to schizophrenia and other neuropsychiatric disorders, as well as to study normal human brain development.

Proper citation: NIMH Brain Tissue Collection (RRID:SCR_008726) Copy   

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http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Atlases

Probabilistic atlases covering 48 cortical and 21 subcortical structural areas, derived from structural data and segmentations kindly provided by the Harvard Center for Morphometric Analysis. T1-weighted images of 21 healthy male and 16 healthy female subjects (ages 18-50) were individually segmented by the CMA using semi-automated tools developed in-house. The T1-weighted images were affine-registered to MNI152 space using FLIRT (FSL), and the transforms then applied to the individual labels. Finally, these were combined across subjects to form population probability maps for each label. Segmentations used to create these atlases were provided by: David Kennedy and Christian Haselgrove, Centre for Morphometric Analysis, Harvard; Bruce Fischl, the Martinos Center for Biomedical Imaging, MGH; Janis Breeze and Jean Frazier from the Child and Adolescent Neuropsychiatric Research Program, Cambridge Health Alliance; Larry Seidman and Jill Goldstein from the Department of Psychiatry of Harvard Medical School.

Proper citation: Harvard - Oxford Cortical Structural Atlas (RRID:SCR_001476) Copy   

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http://www.icn.ucl.ac.uk/motorcontrol/imaging/suit.htm

High-resolution atlas template of the human cerebellum and brainstem, based on the anatomy of 20 young healthy individuals. The atlas is spatially unbiased, i.e. the location of each structure is equal to the expected location of that structure across individuals in MNI space. At the same time, the new template preserves the anatomical detail of cerebellar structures through a nonlinear atlas-generation algorithm. By using automated nonlinear normalization methods, a more accurate intersubject-alignment than current whole-brain methods can be achieved. The toolbox allows you to: * Automatically isolate cerebellar structures from the cerebral cortex based on an anatomical image * Achieve accurate anatomical normalization of cerebellar structures * Normalize functional imaging data for fMRI group analysis * Normalize focal cerebellar lesions for lesion-symptom mapping * Use Voxel-based morphometry (VBM) to determine patterns of cerebellar degeneration or growth * Use a probabilisitc atlas in SUIT space to assign locations to different cerebellar lobuli in an unbiased and informed way * Automatically define ROIs for specific cerebellar lobuli and summarize function and anatomical data * Improve normalization of the deep cerebellar nuclei using an ROI-driven normalization. The suit-toolbox requires Matlab (Version 6.5 and higher) and SPM. The newest version only supports SPM8, although it likely runs under SPM2 or 5 as well. A standalone version for the suit-toolbox is not planned. Usage of the isolation or normalization functions, however, does not require that the analysis is conducted under SPM.

Proper citation: Spatially unbiased atlas template of the cerebellum and brainstem (RRID:SCR_004969) Copy   

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http://centerforaging.duke.edu/index.php?option=com_content&view=article&id=115&Itemid=152

The project has been collecting detailed panel data about the health, disability, demographic, family, socioeconomic, and behavioral risk-factors for mortality and healthy longevity of the oldest old, with a comparative sub-sample of younger elders, to examine the factors in healthy longevity. The baseline survey was conducted in 1998 and the follow-up surveys with replacement to compensate for deceased elders were conducted in 2000, 2002, 2005, and 2008, For each centenarian, one near-by octogenarian (aged 80-89) and one near-by nonagenarian (aged 90-99) of pre-designated age and sex were interviewed. Near-by is loosely defined it could be in the same village or street if available, or in the same town or in the same county or city. The idea was to have comparable numbers of male and female octogenarians and nonagenarians at each age from 80 to 99. In 2002, the study added a refresher sub-sample of 4,845 interviewees aged 65-79, and a sub-sample of 4,478 adult children (aged 35-65) of the elderly interviewees aged 65-110 in eight provinces Comparative study of intergenerational relationships in the context of rapid aging and healthy longevity between Mainland China and Taiwan is possible. At each wave, the longitudinal survivors were re-interviewed, and the deceased interviewees were replaced by additional participants. Data on mortality and health status before dying for the 12,136 elders aged 65-112 who died between the waves were collected in interviews with a close family member of the deceased. The study also included interviews and follow-ups with 4,478 elderly interviewees'''' children aged 35-65. * Dates of Study: 1998-2005 * Study Features: Longitudinal, International * Sample Size: ** 1998: 8,993 ** 2000: 11,199 ** 2002: 16,064 ** 2005: 14,923 Links * Data Archive, http://www.geri.duke.edu/china_study/CLHLS6.htm * ICPSR, http://www.icpsr.umich.edu/icpsrweb/NACDA/studies/03891

Proper citation: Chinese Longitudinal Healthy Longevity Survey (CLHLS) (RRID:SCR_008904) Copy   

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