Researchers Use AI to Detect Correlation between Suicidal Tendencies and Brain Waves

Published By : 01 Nov 2017 | Published By : QYRESEARCH

A new study, carried out at Carnegie Mellon University, has identified patterns in MRI related to suicidal thoughts. The study was carried out on 34 test subjects, half having suicidal thoughts and the other half not. Researchers showed the participants words related to death as well as positive and negative emotions to examine their neural response to the words with fMRI technology. Differences in the MRI patterns of the participants were then matched with the known information about whether they were having suicidal thoughts or not to isolate a pattern of brain waves that corresponded to the presence of suicidal thoughts.

Five regions of the brain were involved in the determination of the pattern, with the neural activity related to suicidal thoughts showing up in the forebrain as well as the hindbrain. Six words, such as ‘death’ and ‘distress’ were isolated by the researchers as being clear markers of the presence of suicidal thoughts. An algorithm based on this data accurately identified 15 of 17 participants having suicidal thoughts and 16 of 17 of the control group as not having any. The algorithm was then put to test in another experiment. The second experiment consisted of a group that had attempted suicide and one that hadn’t. The algorithm succeeded in identifying 16 of 17 patients.

The research represents a new step in studying mental disorders such as depression, as the wide range of symptoms of such mental diseases makes it harder to detect individuals suffering from them. Knowing which parts of the brain are responsible for mental diseases will help medical researchers come up with better targeted treatment.

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