The brain is our most complex organ – in fact, it’s one of the most complex systems in the entire universe – and no two brains are exactly the same.
Brains with mental illness are similarly diverse, and can exhibit an array of abnormalities in basic mental operations including sensory, perceptual, attentional and emotional processes. Despite the uniqueness of brains with mental illness, however, our current approaches to diagnosis and treatment are still largely one-size fits all.
That is why better understanding of brain function is an important clinical and research priority.
In order to effectively personalize treatment and reduce some of the trial-and-error that currently exists in mental health care, researchers are hard at work seeking to better understand basic sensory, cognitive and emotional processes, and the effects of pharmacological and non-pharmacological interventions on the brain in the context of psychiatry.
In doing so, the hope is to more accurately diagnose mental illness, and develop more individualized and precision-based treatment strategies – ones that are based on our unique brain profiles.
The more we understand about the brain, the more we increase the possibility of developing personalized interventions. We hope to one day be at a point where we can look at brain imaging markers and clinical markers together for each patient, and be able to objectively tell someone, for instance, which anti-depressant or type of exercise intervention program they will best respond to. Research that seeks to explore and understand different brain profiles can help us to effectively eliminate a lot of the trial- and- error that comes with current diagnostics and treatment.
Using various neuroimaging and brain electrical activity techniques including clinical electroencephalography (EEG), magnetic resonance imaging (MRI) and positron emission tomography (PET), the Clinical EEG & Neuroimaging Research Unit seeks to better understand the depressed brain, in particular, and what effects various kinds of treatment interventions have on the neural, clinical and cognitive features of mental illness.
Ongoing research in this unit also explores the effects of various non-pharmacological treatment approaches (i.e. aerobic exercise and stimulation therapies) in psychiatric illness on neural profiles, to characterize what brain profiles may “respond” best to which types of treatment. Increasingly, researchers are applying machine learning/big-data approaches to attain this goal.
Because depression often emerges in youth (16-24 year olds) – and because various health agencies have published warnings regarding the use of some drug therapies in this age bracket – the research team has a strong focus on youth mental health as well.
Though much of laboratory’s work centers on better understanding the brain profiles of individuals with depression, studies have examined brain features in populations with schizophrenia, ADHD, dysfunctional anger, as well as non-psychiatric populations.