Researchers using brain imaging to identify people with suicidal thoughts just landed a $3.8 million grant from the National Institute for Mental Health.
Marcel Just of Carnegie Mellon University and David Brent of the University of Pittsburgh will use the money to advance their research analyzing the alterations in how brains represent certain concepts, such as death, cruelty and trouble. Their initial study was published in Nature Human Behaviour in 2017.
Suicidal risk is notoriously difficult to assess and predict. The researchers will attempt to establish reliable neurocognitive markers of suicidal ideation and attempt, examining the differences in brain activation patterns between suicidal and non-suicidal young adults as they think about words related to suicide, and use machine learning techniques to identify neural signatures of suicidal ideation and behavior.
“The cornerstone of this project is our recent ability to identify what concept a person is thinking about based on its accompanying brain activation pattern or neural signature,” said Just, the Carnegie Mellon professor, in a prepared statement. “We were previously able to obtain consistent neural signatures to determine whether someone was thinking about objects like a banana or a hammer by examining their fMRI brain activation patterns. But now we are able to tell whether someone is thinking about ‘trouble’ or ‘death’ in an unusual way. The alterations in the signatures of these concepts are the ‘neurocognitive thought markers’ that our machine learning program looks for.”
The new funding will enable Just and Brent to test the technology in a much larger sample of patients than in the 2017 study, and to include a variety of comparison patients with other psychiatric illnesses.
If the project is as successful as their preliminary work, it will advance clinical practice by improving physicians’ ability to:
- Detect and monitor suicidal risk
- Understand alterations in thinking and feelings related to suicide in their patients, and
- Develop personalized treatment strategies for their suicidal patients based on their altered patterns of thinking and feeling that can more precisely and effectively reduce suicide risk.
“Suicide is the second leading cause of death among young adults in the U.S., and current assessment methods rely entirely on patients’ self-reporting and doctors’ observations,” said Brent, of the University of Pittsburgh School of Medicine. “Any new inroads to better diagnosis and treatment have the potential to save lives.”