Scientists have identified a feature of brain structure that may be linked to a predisposition for premeditated murder. Researchers analyzed MRI scans of 37 individuals accused of homicide and found differences in the amygdala, a brain region involved in emotion processing and fear recognition. The material from Daily Mail was translated by aif.ru.
Among study participants who were later convicted, the amygdala volume was nearly 6% smaller compared to individuals in the control group.
An even more pronounced difference was observed in those who had planned the murder in advance. In this group, the amygdala volume was 14.3% smaller.
The lead author of the study, Professor Adrian Raine from the University of Pennsylvania, explained that such individuals may have less pronounced emotional responses related to concern for others.
Researchers separately examined the circumstances of the crimes based on case materials and information from relatives to assess the degree of premeditation.
Magnetic resonance imaging was used to analyze brain structure. Scientists precisely determined the boundaries of the amygdala and calculated its volume.
According to the study, differences also affected areas involved in fear-based learning and avoidance of painful consequences.
Additionally, among participants who committed homicides, scientists found a smaller volume of the lateral orbitofrontal cortex. As Raine explained, this brain region is associated with experiencing feelings of guilt.
Psychiatrists also assessed the personality traits of the study participants. Individuals with a smaller amygdala volume more frequently exhibited psychopathic characteristics, particularly emotional superficiality and a lack of remorse.
The study was published in the journal Aggression and Violent Behavior.
However, the scientists themselves emphasized that brain features are only one possible risk factor and cannot reliably predict criminal behavior.
“Some murderers have completely normal brain scan results, and some ordinary individuals have abnormal ones,” Professor Raine explained.
According to him, future prediction accuracy could improve through joint analysis of biological, social, psychological factors, and health data, incorporating artificial intelligence and machine learning.
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