Brain Scans Can Predict Which Criminals Are Likely to Get Re-Arrested

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While criminal activity can’t be reduced to a brain image, understanding changes in brain function could improve the way criminals are rehabilitated.

In research published in the Proceedings of the National Academy of Sciences, scientists found that brain scans can predict with startling accuracy the likelihood that criminals will run afoul of the law again. But they caution that the results of such “neuroprediction” requires serious legal and ethical debate before being introduced into the criminal justice system.

The study included 96 male felons, including burglars, robbers, drug dealers and men convicted of assault. All had been sentenced to at least a year in prison. Many had alcohol or other drug addictions and 20% met criteria for a diagnosis of psychopathy or extreme antisocial behavior but none had been convicted of homicide. All agreed to perform a specific task that measured impulse control while their brains were scanned in an fMRI machine. Participants pressed a key on the computer when they saw the letter X, which appeared about 84% of the time. But they had to avoid hitting the key when a K appeared. That required curbing their automatic response to press the key, since the X’s appeared so frequently.

The scans found that those with low levels of activity in a brain region called the anterior cingulate cortex (ACC) while they executed the exercise were more than twice as likely to be re-arrested within four years of their release, compared to those with higher activation in the region. The test normally activates the ACC, which is involved in regulating planned behavior, since not pressing the key when the K appeared required a conscious and organized response. The elevated risk remained even after the scientists controlled for other known criminality risk factors such as age, psychopathy and addictions.

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For nonviolent crimes, the risk of re-arrest was even higher — about five times — for those with low ACC activity. However, because only a few offenders committed violent crimes after release, the researchers could not assess the risk for violence properly. About 53% of the sample was re-arrested during the four year study period, but minor parole and probation violations were not counted.

The results suggest that such brain activity can be a reliable predictor of recidivism, which can have profound implications for rehabilitation strategies. “It’s exciting because it is so incrementally useful above and beyond other measures,” says lead author Kent Kiehl, associate professor of psychology at the University of New Mexico.  For example, ACC activity predicted recidivism better than simply scoring the participants on their impulse control task performance.

“It’s proof of concept research,” says Stephen Morse, professor of law and psychiatry at the University of Pennsylvania, who was not associated with the study but has worked with the authors on other projects.

Kiehl and his colleagues found that once they combined the results from brain scans along with information about psychopathy and other risk factors, their ability to determine which convicts were at highest risk of re-arrest improved even more. And that has implications for treatment. “We know there are certain types of treatment that could increase activity here,” he says.

During the study, for example, the inmates had to learn to suppress the learned response to press the key, an action that normally boosts activity in the ACC. So it’s possible that training on such tasks might increase activity in the ACC and therefore could be useful in treating deviant behavior. While such simple self control training might seem trivial, some research suggests that helping inmates to master even this basic type of performance might help them to better inhibit other ingrained impulsive behaviors— like those that lead to relapse in addictions or re-committing crimes.

As exciting as that potential is, don’t expect “Minority Report”- style crime prediction any time soon.“It’s not ready to be rolled out,” says Kiehl. “Other researchers need to replicate the results and the scanning strategy needs to be tested on a larger sample and with different populations.”

And as with any predictive screen, it’s not foolproof. Some of the inmates with low ACC activity did not get re-arrested. In order to be used in court, any scanning data would have to have a known error rate, which requires more intensive research. “We are skeptical that emerging neurobiological markers could ever independently outperform these existing tools,” like prior history and psychological tests, the authors write.

Yet both Morse and Kiehl anticipate brain scans could become one of the tools that the justice system relies upon to predict re-arrest. They see using brain scans as no different than behavioral measures like psychological tests or prior offense history to predict recidivism, although Kiehl concedes that “Brain scans seem more scary because it seems like reading minds.”

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One issue that additional research will have to address is whether the reduction in ACC activity is indeed linked with a greater tendency to re-offend— or simply with higher odds of being caught. This problem has hampered prior research on predicting violence.

Still, the possibility that brain activity could predict, and possibly explain criminal behavior should create rich new opportunities for understanding such deviance and ultimately lead to more effective rehabilitation efforts.