Abstract
Investigations of mental illness have been enriched by the advent and maturation of neuroimaging technologies and the rapid pace and increased affordability of molecular sequencing techniques, however, the increased volume, variety and velocity of research data, presents a considerable technical and analytic challenge to curate, federate and interpret. Aggregation of high-dimensional datasets across brain disorders can increase sample sizes and may help identify underlying causes of brain dysfunction, however, additional barriers exist for effective data harmonization and integration for their combined use in research. To help realize the potential of multi-modal data integration for the study of mental illness, the Centre for Addiction and Mental Health (CAMH) constructed a centralized data capture, visualization and analytics environment—the CAMH Neuroinformatics Platform—based on the Ontario Brain Institute (OBI) Brain-CODE architecture, towards the curation of a standardized, consolidated psychiatric hospital-wide research dataset, directly coupled to high performance computing resources.
Highlights
The Neuroinformatics platform has provided a key component of technological infrastructure that affords researchers with a standardized framework for data organization and analytics, accessible through a centralized portal
Sophisticated systems are required to handle the increasing variety and scale of neuropsychiatric research data. These challenges are well-known to the neuroscience community, which have driven the development of several concurrent approaches to manage complex datasets including, FBIRN Federated Informatics Research Environment (FIRE), COINS, Longitudinal Online Research and Imaging System (LORIS), NeuroLOG, i2b2 and the Human Brain Project Medical Informatics Platform (Amorim et al, 2016)
The Center for Addiction and Mental Health (CAMH) Neuroinformatics Platform represents a unique application of the Brain-CODE model in a hospital setting, enabling data management and federation between research and clinical domains, in support of treatment units and study centers
Summary
Mental illness affects one in three individuals in their lifetimes (Smetanin et al, 2011), and is the leading cause of disability in Canada (Lim et al, 2008; Mental Health Commission of Canada, 2014; Whiteford et al, 2015) exerting an economic burden estimated at $51 billion per year, including health care costs, lost productivity and reductions in health-related quality of life (Lim et al, 2008; Smetanin et al, 2011). Investigations of mental illness have been enriched by the advent and maturation of neuroimaging technologies and the rapid pace and increased affordability of molecular sequencing techniques (Lynch, 2003; Linden, 2012; Factors Study, 2013; Fu and Costafreda, 2013; Schreiber et al, 2013; Mayberg, 2014; Etkin, 2014; Power et al, 2016; Altman et al, 2016) While these tools can independently provide powerful insights into the brain’s structure and function, directed integration of complementary information holds considerable promise to accelerate discovery and identify cross-modal biomarkers for stratification, diagnosis and treatment of mental illness (Potkin et al, 2014; Mufford et al, 2017). To help realize the potential of multi-modal data towards the study of mental illness, the Center for Addiction and Mental Health (CAMH) constructed a centralized data capture, visualization and analytics environment—the CAMH Neuroinformatics Platform—based on the Ontario Brain Institute’s (OBI) Brain-CODE platform, enabling the curation of a standardized, consolidated psychiatric hospital-wide research dataset, directly connected to high performance computing resources
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