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Found 9 result(s)
The PAIN Repository is a recently funded NIH initiative, which has two components: an archive for already collected imaging data (Archived Repository), and a repository for structural and functional brain images and metadata acquired prospectively using standardized acquisition parameters (Standardized Repository) in healthy control subjects and patients with different types of chronic pain. The PAIN Repository provides the infrastructure for storage of standardized resting state functional, diffusion tensor imaging and structural brain imaging data and associated biological, physiological and behavioral metadata from multiple scanning sites, and provides tools to facilitate analysis of the resulting comprehensive data sets.
The FREEBIRD website aims to facilitate data sharing in the area of injury and emergency research in a timely and responsible manner. It has been launched by providing open access to anonymised data on over 30,000 injured patients (the CRASH-1 and CRASH-2 trials).
The CARMEN pilot project seeks to create a virtual laboratory for experimental neurophysiology, enabling the sharing and collaborative exploitation of data, analysis code and expertise. This study by the DCC contributes to an understanding of the data curation requirements of the eScience community, through its extended observation of the CARMEN neurophysiology community’s specification and selection of solutions for the organisation, access and curation of digital research output.
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One of the world’s largest banks of biological, psychosocial and clinical data on people suffering from mental health problems. The Signature center systematically collects biological, psychosocial and clinical indicators from patients admitted to the psychiatric emergency and at four points throughout their journey in the hospital: upon arrival to the emergency room (state of crisis), at the end of their hospital stay, as well as at the beginning and the end of outpatient treatment. For all hospital clients who agree to participate, blood specimens are collected for the purpose of measuring metabolic, genetic, toxic and infectious biomarkers, while saliva samples are collected to measure sex hormones and hair samples are collected to measure stress hormones. Questionnaire has been selected to cover important dimensional aspects of mental illness such as Behaviour and Cognition (Psychosis, Depression, Anxiety, Impulsiveness, Aggression, Suicide, Addiction, Sleep),Socio-demographic Profile (Spiritual beliefs, Social functioning, Childhood experiences, Demographic, Family background) and Medical Data (Medication, Diagnosis, Long-term health, RAMQ data). On 2016, May there are more than 1150 participants and 400 for the longitudinal Follow-Up
Older persons are often referred to physicians because of complaints of progressive difficulties in walking. The diagnostic and therapeutic approach to these patients is complex. Multiple physiologic subsystems may influence the ability to walk and no standard criteria are currently available to establish whether these subsystems are functioning within the “normal” range. To address lack of knowledge Dr. Luigi Ferrucci and Dr. Stefania Bandinelli conducted InCHIANTI, a representative population-based study of older persons living in the Chianti geographic area (Tuscany, Italy). The data collection started in September 1998 and was completed in March 2000. 3 and 6-year follow-up assessment of the InCHIANTI study population were performed in the years 2001-2003 and 2004-2006. A nine-year follow-up is already planned and funded through an NIA grant. The InCHIANTI Biobank is a collection of biological samples of the study population.
INDI was formed as a next generation FCP effort. INDI aims to provide a model for the broader imaging community while simultaneously creating a public dataset capable of dwarfing those that most groups could obtain individually.
We are developing an open, online platform to provide a seamless access to cloud computing infrastructure and brain data and data derivatives. This platform is meant to reach out beyond neuroscience, allowing also computer scientists, statisticians and engineers interested in brain data to use the data to develop and publish their methods. Brain Life is a project under active development. We currently offer several cloud computing services – also called Brain Life Applications. Sixty-six collaborators from global scientific communities contribute to the project by providing data, applications, technology and products to advance understanding the human brain.