Read the latest centre updates in our spring bulletin.
No images? Click here
Dr. Tristan Glatard
Scientific Director
Krembil Centre for Neuroinformatics (KCNI)
BMO Chair in Artificial Intelligence and Mental Health
Email Us:
Krembil.Centre@camh.ca for questions, feedback and to learn more about the KCNI!
A message from Director:
We have a lot to Celebrate
As I reflect on the past year at the Krembil Centre for Neuroinformatics, one message comes to mind: we have a lot to celebrate.
We’re building momentum across every part of our work—driving forward research, data infrastructure, and innovation that are transforming the landscape of mental health care. From new projects like BAARD that bring precision medicine closer to people with treatment-resistant late-life depression, to the continued growth of the BrainHealth Databank, our teams are doing exceptional science with real-world impact.
This year, I was deeply honoured to be appointed as the inaugural BMO Chair in Artificial Intelligence and Mental Health. This role represents not just an exciting opportunity for collaboration across CAMH and the University of Toronto, but also a shared commitment to embedding ethical, scalable AI solutions that improve outcomes and reduce barriers to care. It's one piece of a much broader vision we’re building together—using data and technology to get upstream, advance care, and lift societal health.
We’re also celebrating the people who power this work. Our researchers, staff, and trainees continue to inspire, earning recognition through major awards and leading ambitious, collaborative projects that span disciplines and geographies. Your dedication and curiosity are what make KCNI a truly special place to be.
Thank you for everything you do. I’m excited about what lies ahead—and grateful to be on this journey with all of you.
Featured Highlights
Announcing the BMO AI Chair
CAMH is pleased to announce that Dr. Tristan Glatard has been appointed as the inaugural BMO Chair in Artificial Intelligence and Mental Health, a joint role with the University of Toronto. This Chair, made possible through the generous support of the Krembil Foundation and BMO, is housed within the Krembil Centre for Neuroinformatics (KCNI).
As Chair, Dr. Glatard will lead the development and implementation of AI tools that support real-time clinical decision-making, predictive modeling of patient outcomes, and the integration of diverse data sources— such as turning different types of health information, like doctors’ notes, brain scans, or data from fitness trackers, into useful insights.
The BMO Chair in Artificial Intelligence and Mental Health is designed to accelerate the responsible use of AI in mental health by building teamwork across research, patient care, and hospital systems. A key goal of the Chair is to create scalable, ethical, and transparent AI systems that improve care quality while addressing issues of equity and access. This directly supports CAMH’s strategic plan Connected CAMH to advance care by embedding innovative tools that enhance precision, efficiency, and responsiveness in the delivery of mental health services.
The Chair will also contribute to upstream efforts by using data to catch mental health issues sooner and support early action. This aligns with the strategic pillar to get upstream—identifying risk factors earlier and supporting prevention-focused strategies powered by data and technology. The role will further support initiatives to reduce disparities in access to care, and foster partnerships that extend beyond the hospital. In doing so, it helps CAMH lift societal health by promoting equity and enhancing mental health outcomes at the population level.
This appointment underscores CAMH’s commitment to embedding cutting-edge technologies into care, research, and operations—ensuring mental health services become increasingly personalized, data-driven, and impactful for people in Canada and around the world.
Introducing BAARD
In September 2024, CAMH, Washington University (StL), and the University of Pittsburgh were awarded an NIH UG3/UH3 Grant (USA) to study predictive precision medicine in people with treatment-resistant late-life depression.
Depression in older adults is a major public health concern, and many individuals do not respond to their first antidepressant. In fact, fewer than 20% of older adults achieve full remission. Previous large-scale clinical trials have shown that adding medications like aripiprazole or bupropion can improve outcomes (29%), but results still vary widely between individuals.
This project introduces a new clinical decision support tool called BAARD (Biotype-assigned Augmentation Approach in Resistant Late-Life Depression). The goal is to improve how treatment decisions are made for seniors who have not responded to initial antidepressants, using personalized biomedical data to guide choices.
In the UG3 phase (Years 1-2), led by Dr. Daniel Felsky (KCNI), researchers will develop and refine the BAARD tool using clinical, cognitive, genetic, and neuroimaging data from previous studies (total N700). Progression to the UH3 phase (Years 3-5) depends on the BAARD tool achieving a combined predicted remission rate of ≥46% in cross-validation using data from the CAN-BIND (N200) and UK Biobank (N~2,400) studies.
In the UH3 phase), the BAARD tool will be tested in a new randomized controlled trial with 300 participants across all 3 sites. The hypothesis is that BAARD-guided treatment will lead to significantly higher remission rates (≥46%) than random treatment assignment (29%). Researchers will also assess how acceptable the tool is to patients and clinicians, paving the way for broader implementation in clinical practice
The Brain Health Databank
The BrainHealth Databank (BHDB) is a comprehensive data platform that integrates clinical, imaging, genetic and behavioural data, allowing for robust analyses of mental health conditions. The BHDB will act both as a repository for data generated by CAMH studies, and as a portal for internal and external scientists to request access to de-identified datasets with established participant consent for re-use -- enabling internal and external researchers to process, analyze and integrate vast amounts of diverse data. This supports the identification of previously unrecognized patterns and relationships that contribute to mental illnesses.
This year the BHDB expanded, hiring Nicole Schoer as manager of the Brain Health Databank. With Nicole’s guidance and support the BHDB has gone from Ideation to Implementation.
To date 23 projects have deposited their research data into the repository, and the team is well underway in development of the researcher facing portal. Keep an eye out for an announcement later this year about the launch of the Portal
BHDB By the Numbers
- 23 studies deposited, with 3,500+ participants' data including assessments/questionnaires/surveys, imaging (EEG, MRI, PET), molecular/genetics and qualitative data types
- 54 studies in progress
- 82 more studies expected to start depositing in in 2025
KCNI Awards & Accomplishments
Congratulations to our KCNI Scientists on their recent recognitions and awards!
Dr. Dan Felsky- 2025
IMS Emerging Leader Alumni award
Promotion to Associate Professor in the Department of Psychiatry at the University of Toronto
-
Dr. Gillian Strudwick
Canadian Life Sciences Top 20 Under 40
-
Dr. Laura Sikstrom
2024 Rising Star Early Career Award in Health Services and Policy Research - CIHR
-
Dr. Andreea Diaconescu
2024 NARSAD Young Investigator award
Promotion to Associate Professor in the Department of Psychiatry at the University of Toronto
Dr. Andreea Diaconescu Scientist at the KCNI, Cognitive Network Modelling
Dr. Daniel Felsky , Scientist at the KCNI, Whole person and Population Modeling Lab
Dr. Gillian Strudwick Senior Scientist at the KCNI, Digital Mental Health Lab
Dr. Laura Sikstom, Staff Scientist at the KCNI, Predictive Care Lab
KCNI Scientist Highlight
DR. ETAY HAY and the BRAIN CIRCUIT MODELING LAB
The Brain Circuit Modelling team has made tremendous progress over the past year. The team completed several major projects, and filed a patent to facilitate translating the method to clinical use. The method will enable a more accurate patient stratification and identifying patients that would benefit from the new drugs that target this mechanism. Frank Mazza and Kant Yao both completed their PhDs; Sana Rosanally completed her master’s thesis; and Faraz Moghbel transferred to his PhD.
The lab received funding from several sources, including a team grant from Brain Canada that will support a collaborative project with Weizmann Institute of Science in Israel. In this collaboration, researchers will study brain activity on a large scale by using advanced electrode probes to record electrical signals from many neurons at once and use detailed computer models to analyze these recordings. The goal is to understand how a decrease in activity from a specific type of brain cell, called somatostatin interneurons, might affect overall brain function, especially in cases of chronic stress. The researchers hope to gain insights into how chronic stress impacts the brain.
Dr. Etay Hay
Scientist, at the KCNI Brain Circuit Modeling Lab
Dr. Hay’s lab completed several key projects and published papers:
- Invention disclosure submitted (for patent submission). Title: Machine learning estimated SST interneuron inhibition from EEG for stratifying depression patients (role: principal inventor; collaborator: Tarek Rajji
- Linking EEG biomarkers of schizophrenia with reduced parvalbumin-expressing (PV) interneuron inhibition. (Pre-print)
- Characterizing EEG biomarkers of new drugs for depression (developed by Drs. Etienne Sibille and Thomas Prevot) that target somatostatin-expressing (SST) interneuron inhibition, as measured in animal models. (published)
- Simulating the effect of spine loss in depression on signal processing, a study that also pioneers modelling dendritic properties as measured in human neurons. (Published)
- Improving methods for deriving neuronal connectivity from spiking activity in large-scale neuronal networks, with possible immediate applications in deriving network connectivity changes in aging. (Pre-Print)
Team photo of the Brain Circuit Modeling Lab in the Distillery District.
In The Media
Episode description: Numerous neuron models have been made, but most of them are “single-purpose” in that they are made to address a single scientific question. In contrast, multipurpose neuron models are made to be used to address many scientific questions.
In 2011, the guest published a multipurpose rodent pyramidal-cell model which has been actively used by the community ever since.
We talk about how such models are made, and how his group later built human neuron models to explore network dynamics in brains of depressed patients.
Connecting Minds -Dr. Etay Hay - IMPROVING PRECISION Feature in Mind over Matter Magazine (full magazine text and Feature available here)
TRAINEE HIGHLIGHT
Dr. Hwayeon Danielle Shin
Dr. Hwayeon Danielle Shin is a Registered Nurse and recently defended her PhD as part of the Digital Mental Health Lab. Fun fact: she has two (adorable) Maltipoos.
Through her PhD work Danielle has been awarded a CIHR postdoctoral fellowship to work with Dr. Patricia Dykes and Dr. Ania Syrowatka. Dr. Dykes is a Professor at Harvard Medical School and Research Program Director at the Center for Patient Safety, Research and Practice at Brigham and Women’s Hospital (BWH) in Boston. Dr. Syrowatka is a Lead Investigator in the Division of General Internal Medicine and Primary Care at BWH and an Assistant Professor at Harvard Medical School.
Dr. Shin’s research focuses on the implementation of AI in healthcare. While AI has gained significant attention, relatively few studies explore how to effectively implement it, with much of the existing research centred on tool development. Moreover, many studies do not reference existing implementation science theories to guide AI adoption, nor do they emphasize collaboration. In addition, limited research includes the perspectives of the diverse people who will be affected by or using AI in healthcare settings. As such, there is a clear need for research that builds knowledge around effective AI implementation and prioritizes collaboration with knowledge users and partners. The overarching goal of this work is to develop a theory-informed, responsible guide for the implementation and evaluation of AI in healthcare across North America, with a focus on Canada and the United States.
Dr. Hwayeon Danielle Shin RN, MScN, PhD
Digital mental health Lab-G. Strudwick
Celebrating the accomplishments of our Trainees
Jiya Shah- NSERC Canadian Graduate Scholarship -Master's
Lucas Makhlouf T-CAIREM summer studentship
Alex Guet-McCreight & Mohamed Abdelhack Canadian Neuroanalytics Scholars Program
Marry Anne Panoyan. Novo Nordisk Network for Healthy Populations Graduate Award,
KCNI Staff and trainees celebrating the 2024 holiday season
Congratulations to our recent Graduates from 2024 and 2025!
We'd like to take a moment to acknowledge the significant work and contributions of Trainees who have Graduated or Defended their PhDs in the last year!
Whole Brain Modelling - Dr. John Griffiths.
- Taha Morshedzadeh (MSc, 04/24)
- Andrew Clappison, (MSc, 05/24)
- Dr. Shreyas Harita (PhD, 09/24)
- Mohammad Parsa Oveisi, (MSc, 12/24)
Cognitive Network Modeling - Dr. Andree Daconescu
- Jason Yang (MSc 05/24)
Brain Circuit Modeling - Dr. Etay Hay
- Dr. Frank Mazza (PhD, 06/24)
- Dr. Kant Yao, (PhD, 12/24)
Whole Person Modeling - Dr. Dan Felsky
- Denise Sabac (MSc, 06/24)
- Dr. Tara Henechowicz– (PhD, 04/25)
Digital Mental Health Lab - Dr. Gillian Strudwick
- Dr. Keri Durocher (PhD, 12/24)
- Dr. Danielle Shin (PhD, 04/25)
Featured Publications
- Therapeutic dose prediction of α5-GABA receptor modulation from simulated EEG of depression severity- Guet-McCreight A, Mazza F., Prevot T., Sibille E. Hay https://doi.org/10.1371/journal.pcbi.1012693
- The Emergent Role of Digital Navigators: Case Examples - Pape C, Kassam I, Shin HD, et al. https://pubmed.ncbi.nlm.nih.gov/39968541/
- Diminished pain sensitivity mediates the relationship between psychopathic traits and reduced learning from pain --Atanassova, D.V., Mathys, C., Diaconescu, A.O. et al. https://doi.org/10.1038/s44271-024-00133-1
- Target engagement of the subgenual anterior cingulate cortex with transcranial temporal interference stimulation in major depressive disorder: a protocol for a randomized sham-controlled trial -- Demchenko I, Rampersad S, Datta A, Horn A, Churchill NW, Kennedy SH, Krishnan S, Rueda A, Schweizer TA, Griffiths JD, Boyden ES, Santarnecchi E, Bhat V https://doi.org/10.3389/fnins.2024.1390250
About Us
The Krembil Centre for Neuroinformatics collaborates globally to collect and integrate large-scale brain research data, apply machine learning and artificial intelligence, and develop multiscale computational models that can transform our understanding of brain disorders. Our open, team science approach focuses on bridging the levels of the brain, from genes to circuits and from whole brains to the whole person, in order to better define, prevent and treat mental illnesses.
Learn more at
www.krembilneuroinformatics.ca
Want to Join Our Team? KCNI is always looking for scientists, post-doctoral fellows, grad students, coordinators, and more!
#KrembilNeuroinformatics is putting today’s most advanced technology to work on this universal task that will unlock the power of personalized medicine to change the world.
