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CAN-BIND, Canada's Largest Depression Research Network

Canada's Largest Depression Research Network

CAN-BIND, Canada's Largest Depression Research Network

Canada's Largest Depression Research Network

  • About CAN-BIND
    • Vision & Mission
    • Why and How We Study Depression
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    • Recruiting: OPTIMUM-D Study
    • Recruiting: PERFORM-D Study
    • Recruiting: ENABLE Platform
    • Recruiting: LIMIT-D Study
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  • About CAN-BIND
    • Vision & Mission
    • Why and How We Study Depression
    • Our Research Platforms
    • Our Team
    • Our Research Network
    • Our Partners
    • Funding & Support
  • Research Studies
    • Recruiting: OPTIMUM-D Study
    • Recruiting: PERFORM-D Study
    • Recruiting: ENABLE Platform
    • Recruiting: LIMIT-D Study
    • Previous CAN-BIND Research Studies
  • Research at a Glance
    • Latest Research Summaries
    • Research Summary Archive
  • Research Publications
    • List of Publications
  • Resources
    • CHOICE-D Guide to Depression Treatment
    • Public Resources
    • Healthcare Provider Resources
  • New & Events
    • Events
  • Videos & Podcasts
    • Podcasts
    • Video Library
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Neuroimaging

Platform Leadership

Katharine Dunlop, PhD
Nathan Churchill, PhD

Platform Management

Stefanie Hassel, PhD

Active Sites

The Neuroimaging Platform operates at the following research sites:

  • St. Joseph’s Healthcare Hamilton (Hamilton, Ontario)
  • St. Michael’s Hospital (Toronto, Ontario)
  • University of Calgary (Calgary, Alberta)

Platform Overview

The Neuroimaging Platform is responsible for the standardization of neuroimaging protocols across study sites, as well as the quality assurance, quality control, and preliminary analysis of brain imaging data collected through CAN-BIND studies. This platform focuses on evaluating brain structure and function to better understand the neural mechanisms underlying depression and treatment response.

CAN-BIND studies acquire neuroimaging data from hundreds of participants using harmonized imaging protocols, with the goal of enabling large-scale, longitudinal comparisons across cohorts. This will support analyses of nearly a thousand participants, many of whom are scanned at multiple time points. Imaging data include task-based functional magnetic resonance imaging (fMRI), resting-state fMRI, structural MRI for assessing brain volume, and diffusion tensor imaging (DTI) for examining white matter connectivity.

The Neuroimaging Platform provides a critical foundation for computational approaches that integrate multiple neuroimaging modalities with clinical and biological data to improve the classification, prediction, and understanding of depression. By combining these diverse data sources, the platform supports the identification of brain-based markers of illness and treatment response. This work also contributes to establishing the clinical utility of imaging-based measures and supports the long-term goal of translating neuroimaging tools into clinical psychiatry, where they may eventually aid in diagnosis, treatment selection, and monitoring of depression.

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