Recognizing that HBHL research efforts are dependent on key platform technologies, the HBHL Research Management Committee (RMC) has established 5 subcommittees to support and develop platform technologies relevant to HBHL’s research priorities. Researchers planning to use or further develop such platforms should contact each sub-committee leader. The mandates of each sub-committee are as follows:
Leader: Dr. Laurence Kirmayer
Mandate: Provide input into HBHL theme projects and other activities, oversee training in social science for neuroscientists, and foster new approaches to interdisciplinary collaboration through organizing focused workshops and training programs. Establish interdisciplinary working groups on: 1) Social Indicators of Brain Health to systematize and refine existing indicators in available open science data-sets at McGill and beyond; 2) Social Contexts of Brain Health with a view to refine existing research frameworks and diagnostic tools in psychiatry.
NeuroHub and Machine Learning
Mandate: Oversee the development of the platform for integrating data across studies and state-of-the-art modelling methodologies by: 1) identifying and addressing the research challenges in extending the current HBHL infrastructure to ensure that it will be able to support the wide range of applications that will be developed in the HBHL context; 2) identifying the community, data, important infrastructure (hardware and software) and needs for enhanced research infrastructure (e.g. storage/capacity, computational/HPC, growing needs etc.); 3) assisting the Neuroinformatics theme with the routine operations of managing a complex HBHL-related data repository, employing the LORIS/CBRAIN data-sharing ecosystem; 4) interacting with and advising the other research themes and facilitating the use of NeuroHub in their research activities; 5) participating in all HBHL activities, when relevant (e.g. workshops, seminars, development of the Request for Proposals, etc.); and 6) building relationships with external academics, resources, and companies.
Mandate: Ensure that the clinical goals of HBHL are met by: 1) supporting the translation of scientific advances from HBHL to the clinic; 2) ensuring that HBHL priorities consider clinical perspectives; 3) facilitating communication amongst clinical neuroscientists (broadly inclusive of those who study neurological disorders, medical conditions affecting the brain, and clinical and psychosocial mental health researchers) at McGill and at partner organizations; 4) communicating between this clinical research community and the HBHL RMC; and 5) identifying bottlenecks or gaps between fundamental research and potential applications to the clinic, and propose solutions.
Mandate: Promote animal models to achieve HBHL goals by: 1) accelerating large-scale data acquisition from animal models at behavioral, circuit and cellular levels through HBHL funding mechanisms; 2) fostering the development of novel methodologies for the analysis of large datasets from animal experimentation through HBHL funding mechanisms; 3) developing innovative bioinformatics technologies to allow effective and bidirectional knowledge translation from animal to human research through HBHL funding mechanisms; 4) establishing formal relationships with the four themes in order to foster research on normal and pathological brain function across all brain research areas; 5) identifying external partners (academia and industry) with expertise currently unavailable in HBHL to enhance the research potential; and 6) contributing to HBHL activities in general across themes and subthemes to optimize synergy between this subcommittee and other HBHL committees and subcommittees.
Cellular and Tissue Models
Leader: Dr. Edward Fon
Mandate: Support the following types of technologies and platforms across the four HBHL themes: 1) development of novel biomaterials, scaffolds and methods for growing, characterizing (RNASeq, single cell sequencing) and genetically engineering (CRISPR) iPSCderived neurons, glia and organoids in both 2 and 3 dimensions to better reflect how they behave in the brain; 2) integration of multidimensional clinical, genetic, and imaging patient data from the C-BIGR with the comprehensive profiling of patient samples, neurons and organoids generated from iPSCs in close collaboration with the four other HBHL platforms; 3) development of tools for the analysis of large structured and unstructured datasets obtained from assays with iPSC-derived neurons and glia; 4) generation of cell- and tissue-based assays that will be disease-relevant and robust enough to use in open drug screening campaigns in collaboration with Pharma partners.