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Faranak Farzan (standing) and grad student Raaj Chatterjee demonstrate non-invasive brain mapping technologies in the eBrain Lab at Simon Fraser University. These include transcranial magnetic stimulation (the blue machine in the background and the black coil Farzan is holding to Chatterjee’s head) and a neuro-navigational device (camera in the top right and trackers on Chatterjee’s head).SIMON FRASER UNIVERSITY

Faranak Farzan is a mechatronic systems engineering professor and Chair in Technology Innovations for Youth Addiction Recovery and Mental Health at Simon Fraser University and founder and head of SFU’s CFI-funded eBrain Lab.

CFI: The eBrain Lab at SFU’s Surrey campus takes a unique approach to studying mental illness and addiction. How is it different?

Farzan: The eBrain Lab is about bringing disciplines together to develop new ways of understanding and treating mental health illnesses.

The lab has two essential features. One is the transdisciplinary approach that I believe is the future of mental health care. We integrate engineering, neuroscience, psychiatry, psychology and computer science to co-create new technologies. We need to combine them due to the complexity of the challenge to develop meaningful solutions that are translatable to real-life settings.

The other aspect that is unique with eBrain Lab is our local and global collaborations. The City of Surrey has one of the highest youth populations in British Columbia, and there is a real need for the community to address youth addiction and mental health. We start with what the community needs are and involve people with lived experience in technology creation. We also collaborate across Canada and internationally to validate the new solutions.

CFI: You’re combining engineering with health disciplines to better understand how brain function and mental illness interact. What kinds of equipment are you using to do this?

Farzan: Since mental illnesses impact the nervous system, we need tools to look at how the nervous system functions or to modify it for treatment. To do this, we develop and integrate technologies like wearable sensors for collecting data, computational methods, machine learning, and neuromodulation technologies for diagnosis and treatments. For example, neuromodulation technologies allow us to objectively assess brain circuitries. You could stimulate the brain and study its reaction to assess how certain circuitries work and then target them for treatment. We have used these in youth depression to develop new treatments.

CFI: What sorts of questions are you trying to answer?

Farzan: One problem we have with depression, for youth and adults, is that it takes years before clinicians can identify which treatment could work better for a given patient. The process of offering the treatment to patients is trial and error and it’s not objective.

We published a paper in January 2020 through our work with the Canadian Biomarker Integration Network in Depression, showing that using technologies, we can predict which patient with depression is going to respond to an antidepressant. The technologies can tell us, with clinically meaningful accuracy, if a person is a good candidate for the treatment.

Moreover, in addiction recovery programs we can look at the brain activity before interventions and over time to see how the brain is changing. We want to know if we can predict who is going to respond to a treatment and to predict who is going to have a relapse or when they are safe to go back to their normal life. Can we predict that from brain waves?

These kinds of questions aren’t new – we’ve been asking them for decades or centuries. We haven’t found the answers because we haven’t had the right methodology. eBrain Lab uses new methodologies to answer these questions. How does depression impact the brain? What is addiction? Can we predict which treatments will work? How can we develop more efficacious treatments?

Originally published by the Canada Foundation for Innovation (CFI).

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