The World Health Organisation estimates that one million people die from suicide each year, which is about one death every 40 seconds. In the last 45 years global suicide rates have increased by 60% and suicide is now among the the three leading causes of death among those aged 15-44 (male and female)

Scientists have now identified that suicidal thoughts can be identified by the activity of neurons. Through the use of AI and machine learning this discovery could be used to develop tools to identify those at risk.

Researchers at Carnegie Mellon University and the University of Pittsburgh performed studies and discovered that brain activity is different in a suicidal person when reacting to concepts such as death. the Using this brain imaging technology, the researchers were able to predict who was suicidal with an accuracy of 94%.

The researches found 34 young adults of which 17 have had suicidal thoughts before, and about half of them have attempted suicide before. The researches also found 17 neurotypical controls. Then they used a fMRI machine to perform brain scans of all the patients.

Patients were presented with 10 suicide related words (e.g ‘hopeless’ and ‘lifeless’) and then with 10 positive words (such as ‘carefree’) and 10 slightly negative words (such as ‘trouble’).

From the brain activity recorded and the emotional responses they indicated, the researchers isolated six terms – ‘death’, ‘cruelty’, ‘trouble’, ‘carefree’, ‘good’, and ‘praise’ – and five brain areas that most clearly distinguished the suicidal ideators from the control group.

223 algorithm suicide 1
(CMU)

Using this subset of the data, a machine-learning algorithm trained on the brain responses was able to correctly identify suicidal patients and controls 91 percent of the time: recognising 15 of 17 patients as belonging to the suicide group, and 16 of 17 healthy individuals as belonging to the control group.

“There is undoubtedly a biological basis for whether someone is going to commit suicide,” neuroscientist Blake Richards from the University of Toronto in Canada told The Verge.

To address those kinds of problems, the team is now looking into whether participants wearing electroencephalography (EEG) sensors give off similar kinds of identifiable brain activity – using smaller and much more portable monitoring equipment that’s significantly cheaper than expensive fMRI machines.

Until that future research is conducted, we won’t know how effective such a proxy would be, but one thing’s for sure – this is important research, and when it comes to saving lives lost to suicide, we need every bit of help we can get.