Scientists claim brain imaging could be a vital tool in suicide prevention, thanks to new research that suggests machine learning can identify those at risk of taking their own lives.
Almost 800,000 people die by suicide every year, and unless they forewarn friends, family, or their therapist, those deaths are very difficult to predict – but researchers say biological signs do exist, buried in the hidden patterns of brain activity.
“Our latest work is unique insofar as it identifies concept alterations that are associated with suicidal ideation and behaviour,” explains psychologist Marcel Just from Carnegie Mellon University.
“This gives us a window into the brain and mind, shedding light on how suicidal individuals think about suicide and emotion related concepts.”
In previous research, Just and his team used computational models to map how the brain processes complex thoughts, whether that’s things like scientific concepts or the tangled combinations of ideas that represent human action.
Now, the researchers have used the same techniques to try and isolate what suicidal tendencies might look like in terms of our brain’s electrical activity, by searching for neural signatures that give away emotional responses such as sadness, shame, anger, and pride.