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[liberationtech] [tt] Neuroimaging 'biomarker' linked to rearrest after incarceration.

Eugen Leitl eugen at leitl.org
Wed Mar 27 06:36:11 PDT 2013


http://www.nature.com/news/brain-scans-predict-which-criminals-are-more-likely-to-reoffend-1.12672

Brain scans predict which criminals are more likely to reoffend

Neuroimaging 'biomarker' linked to rearrest after incarceration.

Regina Nuzzo

25 March 2013

Activity in a particular region of the cortex could tell whether a convict is
likely to get in trouble again.  DOUG MENUEZ/GETTY

In a twist that evokes the dystopian science fiction of writer Philip K.
Dick, neuroscientists have found a way to predict whether convicted felons
are likely to commit crimes again from looking at their brain scans. Convicts
showing low activity in a brain region associated with decision-making and
action are more likely to be arrested again, and sooner.

Kent Kiehl, a neuroscientist at the non-profit Mind Research Network in
Albuquerque, New Mexico, and his collaborators studied a group of 96 male
prisoners just before their release. The researchers used functional magnetic
resonance imaging (fMRI) to scan the prisoners’ brains during computer tasks
in which subjects had to make quick decisions and inhibit impulsive
reactions.

The scans focused on activity in a section of the anterior cingulate cortex
(ACC), a small region in the front of the brain involved in motor control and
executive functioning. The researchers then followed the ex-convicts for four
years to see how they fared.

Among the subjects of the study, men who had lower ACC activity during the
quick-decision tasks were more likely to be arrested again after getting out
of prison, even after the researchers accounted for other risk factors such
as age, drug and alcohol abuse and psychopathic traits. Men who were in the
lower half of the ACC activity ranking had a 2.6-fold higher rate of rearrest
for all crimes and a 4.3-fold higher rate for nonviolent crimes. The results
are published today in the Proceedings of the National Academy of Sciences1.

There is growing interest in using neuroimaging to predict specific
behaviour, says Tor Wager, a neuroscientist at the University of Colorado in
Boulder. He says that studies such as this one, which tie brain imaging to
concrete clinical outcomes, “provide a new and so far very promising way” to
find patterns of brain activity that have broader implications for society.

But the authors themselves stress that much more work is needed to prove that
the technique is reliable and consistent, and that it is likely to flag only
the truly high-risk felons and leave the low-risk ones alone. “This isn't
ready for prime time,” says Kiehl.

Wager adds that the part of the ACC examined in this study “is one of the
most frequently activated areas in the human brain across all kinds of tasks
and psychological states”. Low ACC activity could have a variety of causes —
impulsivity, caffeine use, vascular health, low motivation or better neural
efficiency — and not all of these are necessarily related to criminal
behaviour.

Crime prediction was the subject of Dick's 1956 short story “The Minority
Report” (adapted for the silver screen by Steven Spielberg in 2002), which
highlighted the thorny ethics of arresting people for crimes they had yet to
commit.

Brain scans are of course a far cry from the clairvoyants featured in that
science-fiction story. But even if the science turns out to be reliable, the
legal and social implications remain to be explored, the authors warn.
Perhaps the most appropriate use for neurobiological markers would be for
helping to make low-stakes decisions, such as which rehabilitation treatment
to assign a prisoner, rather than high-stakes ones such as sentencing or
releasing on parole.

“A treatment of [these clinical neuroimaging studies] that is either too
glibly enthusiastic or over-critical,” Wager says, “will be damaging for this
emerging science in the long run.”

Nature doi:10.1038/nature.2013.12672

References

Aharoni, E. et al. Proc. Natl Acad. Sci. USA
http://dx.doi.org/10.1073/pnas.1219302110 (2013).

Yarkoni, T., Poldrack, R. A., Nichols, T. E., Van Essen, D. C. & Wager, T. D.
Nature Methods 8, 665–670 (2011).
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