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Related Concept Videos

Brain Imaging01:14

Brain Imaging

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Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
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The brain is an integral component of the nervous system and serves as the center for processing sensory inputs, making decisions, and directing bodily actions. This complex organ is organized into three primary sections: the hindbrain, midbrain, and forebrain, each responsible for a range of vital functions.
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FAIR in action: Brain-CODE - A neuroscience data sharing platform to accelerate brain research.

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The Brain-CODE platform operationalizes the FAIR data principles to enhance neuroscience research. This facilitates effective health data sharing, improving disease understanding and patient outcomes within learning health systems.

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Area of Science:

  • Neuroscience
  • Health Informatics
  • Data Science

Background:

  • Effective health research data sharing is crucial for advancing disease understanding, prevention, treatment, and monitoring.
  • A learning health system requires data to be Findable, Accessible, Interoperable, and Reusable (FAIR).
  • The Ontario Brain Institute (OBI) has pioneered FAIR data sharing in neuroscience since 2012 through its Brain-CODE platform.

Purpose of the Study:

  • To describe how the Brain-CODE platform operationalizes the FAIR data principles for neuroscience research.
  • To highlight the successes and challenges of a FAIR-focused neuroinformatics platform.

Main Methods:

  • Findable: Brain-CODE provides interactive tools for generating specific data subsets aligned with research questions.
  • Accessible: Multiple data access mechanisms are offered, including metadata access, secure computing environment access, and data export.
  • Interoperable: Standardization is implemented at data capture and release stages for seamless integration of data elements.
  • Reusable: Quality assurance measures and controls are in place to maximize the value and reusability of the data.

Main Results:

  • Brain-CODE successfully operationalizes FAIR principles, enhancing data sharing in neuroscience.
  • The platform offers diverse mechanisms for data access and promotes data standardization.
  • Quality control measures ensure data value and reusability for advanced research.

Conclusions:

  • The Brain-CODE platform serves as a model for implementing FAIR data principles in neuroinformatics.
  • This approach supports the development of learning health systems by facilitating widespread collection and sharing of neuroscience research data.
  • Addressing challenges in FAIR data operationalization is key to maximizing the impact of health research data.