$640K INVESTMENT IN NEUROANALYTICS BY THE ONTARIO BRAIN INSTITUTE

New AI-driven projects represent the next frontier in brain health research

TORONTO, April 10, 2025 /CNW/ - The Ontario Brain Institute (OBI) has invested $640,000 into eight new projects through the Centre for Analytics (CfA), continuing to foster the development of innovative technologies that better detect, predict, and treat brain disorders.

"We are committed to bridging scientific discovery and innovation, and these groundbreaking AI-driven projects represent the next frontier in brain health research. By integrating advanced computing with neuroscience, we can accelerate early diagnosis, improve treatment precision, and develop more effective tools for managing neurological conditions, said Dr. Tom Mikkelsen, OBI's President and Scientific Director. "This investment not only strengthens Ontario's leadership in brain health but also positions Canada at the forefront of global innovation, ensuring that our homegrown research continues to drive better outcomes for patients and greater economic opportunity for our communities."

From mental health and concussion to ocular care, OBI is proud to introduce the latest group of Analytics Initiatives, all which are leveraging the CfA's advanced computing, artificial intelligence, and machine learning to improve diagnosis, treatment, or research efficiency in mental health, neurology, and more.

"Ontario researchers are making groundbreaking discoveries to improve brain health so that residents of our province live longer, healthier lives," stated the Honourable Nolan Quinn, Minister of Colleges, Universities, Research Excellence and Security. "Our government is proud to invest in the Ontario Brain Institute and commend their brilliant new cohort of researchers as they drive innovation in our health care sector and grow our economic advantage on the global research stage."

The new Analytics Initiatives are:

• Voices for Mental Health: AI-Driven Diagnosis through Speech, Language, and other Data: A project led by Dr. Frank Rudzicz of Dalhousie University will use advanced machine learning models to analyze speech and language for signs of mental health conditions like depression, bipolar disorder, and anxiety. Down the road, the Voice for Mental Health tool could help with early detection, diagnosis, and monitoring of mental conditions through an integrated analysis of sentiment, tone, word choice, and speech patterns.
  
  
• Accelerating Mental Health Precision Trials: Dr. Clement Ma of the Centre for Addiction of Mental Health is building a digital platform to improve the success rate of precision psychiatry trials. Dr. Ma's platform will help researchers determine the number of participants needed to have a high chance to detect a real treatment effect in precision psychiatry trials. Further, using existing patient data securely stored on Brain-CODE, OBI's neuroinformatics platform, Dr. Ma will examine treatment effectiveness for diagnostic sub-types or predictive biomarkers in order predict future results, which will help researchers design smarter studies that focus on each individual's nuanced mental health journey.
  
  
• Measurement of Psychomotor Speed from Multimodal Data: Dr. Rudolf Uher of Dalhousie University is developing a new technology that uses speech and movement data to measure how quickly a person processes and responds to information, known as the psychomotor speed, which is an important feature of brain functioning that is affected by multiple brain conditions. With the support of the CfA team to refine this tool, Dr. Uher aims to accelerate the diagnosis and monitoring brain disorders like dementia, depression, psychosis, and traumatic brain injuries.
  
  
• An Integrated Multimodal Biotyping Toolbox for Yielding Personalized Health: With the Centre for Analytics' machine learning resources to analyze different types of medical data together, Dr. Faranak Farzan of Simon Fraser University is looking to create new software tool for researchers that will facilitate the identification of subgroups in people living with depression, as well as to personalize treatments based on brain scans, and clinical tests.
  
  
• ADVISING – Autonomic Dysfunction using Vital-sign Indicators to Subtype via Integrated Neuroanalytics for Guidance: Dr. Roger Zemek of the University of Ottawa and the CHEO Research Institute is using AI to better characterize and predict autonomic dysfunction – issues with involuntary body functions like heart rate – in concussion patients. His work with the CfA could lead to improved treatment and recovery plans in concussion management and care.
  
  
• Development of AI Algorithms for Enhancing Resolution in Portable Brain Imaging: The AiimSense team, led by Dr. Atefeh Zarabadi and located in Kitchener, Ontario, is developing AI-powered algorithms at the Centre for Analytics to enhance the resolution of brain images from portable, cost-effective imaging devices. This work aims to improve accessibility to brain scans and support more accurate diagnosis and treatment of neurological conditions.
  
  
• Multimodal Foundation Model for Optic Nerve Damage Detection: Dr. Ehsan Amjadian, CEO of Ophthalmo Corp. and a faculty member in the Cheriton School of Computer Science at the University of Waterloo, will test a powerful new technology designed to lower the physician's burden by applying AI in eye care. Involving the use of advanced language and vision models, this novel approach will be one of the first attempts to utilize multimodality to improve and speed up early diagnosis of eye diseases caused by damage to the nerves. The approach incorporates different types of input data including medical texts and images.
  
  
• Major depression multivariate patient response characterization: Dr. Joseph Geraci and the team at Netr"aMark in Toronto are using a unique mathematically augmented AI to analyze depression treatment outcomes from an existing comprehensive dataset that is securely stored on OBI's Brain-CODE platform. The goal of their project is to uncover different subtypes of major depression and how these characterize drug response from brain scans and genetic data. These models will help NetraMark improve major depression clinical trial success rates for their clients.

Learn more about the Centre for Analytics and working with Brain-CODE, OBI's neuroinformatics platform at braininstitute.ca/cfa.

About the Ontario Brain Institute

The Ontario Brain Institute (OBI) is a provincially funded, not-for-profit organization that accelerates discovery and innovation, benefiting both patients and the economy. OBI's collaborative team science approach promotes brain research, commercialization, and care by connecting researchers, clinicians, industry, patients, and their advocates to improve the lives of those living with brain disorders. For more information, visit braininstitute.ca.

SOURCE Ontario Brain Institute

Renée Dunk, Senior Communications Lead (Ontario Brain Institute): [email protected], 416-562-2695