Cognitive Control Network in Elderly Depressed Patients At-Risk for Suicide: a Functional MRI Study
Stéphane Richard-Devantoy, M.D., Ph.D., Douglas Mental Health University Institute
Mentor: Gustavo Turecki, M.D., Ph.D., McGill University, Douglas Mental Health University Institute
2014 Young Investigator Grant
Inside the Research
Bio: Dr. Richard-Devantoy received his medical degree from the University of Angers (France) in 2007, and the same institution awarded him his Ph.D in neuroscience in 2011. He is currently Adjunct Professor in the Department of Psychiatry at McGill University, and also serves as an attending psychiatrist at both Saint-Jerome Hospital and at Douglas Mental Health University Institute.
Research Category: Neurobiological – brain functioning
Abstract: Suicide is three times more frequent in elderly adults compared to younger people. Unfortunately, predicting and preventing suicidal behaviors in elderly people remains difficult. Clinical, biological, and genetic data suggests that suicidal behaviors may be best understood within a stress-vulnerability model where more vulnerable individuals are at increased risk of engaging in suicidal behaviors when experiencing stress. Vulnerability to suicidal behavior has also been associated with specific changes in brain and the ways people think and problem solve, i.e., cognition. One of the relevant cognitive functions is cognitive inhibition, a function dedicated to controlling and selecting the most advantageous thoughts and behaviors. Dr. Richard-Devantoy will use functional Magnetic Resonance Imaging (fMRI) and Diffusion Tensor Imaging (DTI) to examine the neural basis of the vulnerability to suicidal behavior in elderly, with a particular focus on cognitive inhibition and how it is change by emotions. Based on the neurocognitive model underlying the study, the primary focus will be to assess the imbalance between emotions and regulatory processes.
Three groups will be compared: 25 elderly people who are depressed and have a personal history of suicidal behaviors; 25 elderly people who are depressed with no personal or first-degree family history of suicidal behavior; and 25 elderly people without a psychiatric history and no personal or first-degree family history of suicidal behavior or depressive disorder. Participants will be between 65 and 85 years old. Participants will complete a thorough mental health and suicide risk assessment and a go-no go reaction time task during the scan. Findings from this study will improve the understanding of the brain basis of suicidal behaviors in elderly, and will help to define potential predictive risk factors.
Impact: Improved understanding of the brain basis of suicidal behavior in elderly.