Criminal Intent May Be Measurable on Imaging
April 12, 2017 by Deborah Brauser
New research suggests the possibility of measuring whether an individual was just reckless while committing a crime or was acting knowingly, which can have more severe legal implications.
In the study, 40 participants were told they would need to go through a security checkpoint with a suitcase that may or may not have contraband in it. Although some were told the suitcase definitely held contraband, putting them in a “knowing state,” others were only told there was a risk. But all heard there would be a reward if they got the suitcase through and punishment if they were caught.
The participants then underwent neuroimaging while making their decisions. These data, combined with machine learning techniques, gave high probability in predicting whether an individual was in a knowing or reckless state, especially when the participants were given a lot of information about the hypothetical scenario.
Coinvestigator Gideon Yaffe, PhD, professor of law at Yale University, New Haven, Connecticut, told Medscape Medical News that the study is not implying that juries of today should be replaced by these processes.
However, “it does suggest that neuroimaging can be useful for helping us to make distinctions in mental state when it comes to culpability,” said Dr Yaffe. “These decisions are made every day in the courtroom, and we should be using every tool we have to do it better and more accurately.”
The findings are published in the March 21 issue of the Proceedings of the National Academy of Sciences.
“Criminal convictions require proof that a prohibited act was performed in a statutorily specified mental state,” write the investigators, adding that greater punishments are supposed to be given for those who act knowingly.
However, past research “suggests people have trouble classifying defendants as knowing, rather than reckless, even when instructed on the relevant legal criteria,” they write.
“It’s important to the legal system to make distinctions in defendants on the basis of their mental states, as this can often make the difference in years in prison,” added Dr Yaffe. One example he cited was whether a person was aware that they were carrying drugs across the border.
“People are misclassified all the time, and this raised the worry that perhaps there isn’t a meaningful distinction and the law is acting on a fiction,” he said. “So we were interested in exploring whether we really could distinguish between these two mental states.”
In the current study, all the participants were shown between 1 and 5 suitcases, told only 1 held contraband, and told 1 of those would be randomly selected for them to take through a checkpoint.
When only one suitcase was shown, this represented a knowing situation, as obviously the contraband was there. If more than one suitcase was shown, this represented a reckless situation because the participants knew there was “a risk of varying magnitude.”
In addition, half of the participants were in the Search-First condition (50% women; mean age, 32.9 years), and the other half in the Contraband-First condition (50% women; mean age, 26.9 years).
The Search-First group was shown risk probability statistics of being searched/caught before the probability that their suitcase held contraband, whereas the other group received this information in the reverse order.
All the participants underwent functional magnetic resonance imaging while deciding whether they would go through with the hypothetical suitcase scenario.
Changing Brain Patterns
Not surprisingly, the number of participants in either condition group willing to carry a suitcase decreased as the likelihood that it held contraband or that they would be searched increased.
In the Search-First group, there was an out-of-sample average area under the curve value of 0.789 for predicting whether a person was in a knowing or reckless situation, based on elastic-net regression.
Although a number close to 0.5 suggests a random value, a “1” indicates perfect classification. There was also an average correct classification rate of 71%.
Brain activation in the dorsomedial prefrontal cortex, medial orbitofrontal cortex, middle and anterior cingulate cortex, bilateral superior temporal gyrus/temporoparietal junction, and bilateral anterior insula helped predict a knowing situation.
“Areas more predictive of being in a reckless situation were mainly in the occipital cortex,” report the investigators.
In the Contraband-First group, the area under the curve value dropped to 0.287, with an average correct classification rate of just 32.1%. The right temporoparietal junction was implicated in the knowing situation, whereas occipital areas were again implicated in the reckless situation.
In other words, “when subjects weren’t told their probability of being caught at the time they were told the probability of having contraband, we weren’t really able to distinguish between those who knew they had contraband and those who merely thought there was a chance they had it,” said Dr Yaffe.
“We thought the order that they were told the probabilities wouldn’t matter, so we were very surprised to see that it did matter,” he added.
When examining different levels of contraband risk (1 vs 2 to 5 suitcases), the elastic-net model’s ability to distinguish between reckless or knowing situations depended both on degree of probability risk and how much information was given to the participants at scenario presentation.
Overall, the findings “provide neural evidence of a detectable difference in the mental state of knowledge in contrast to recklessness and suggest, as a proof of principle, the possibility of inferring from brain data in which legally relevant category a person belongs,” write the investigators.
“What this study is suggesting is that a neuroscientific tool might really be helpful. And that is surprising and, I think, very interesting,” said Dr Yaffe.
“It’s also suggesting that over time we could perhaps build even more accurate tools.”
The study was funded by a grant from the John D and Catherine T MacArthur Foundation. The study authors have disclosed no relevant financial relationships.
PNAS. 2017;114:3222-3227. Full text