Can Neuroscience Help Predict Future Antisocial Behavior?

29 Pages Posted: 1 Nov 2016

See all articles by Lyn M. Gaudet

Lyn M. Gaudet


Jason Kerkmans


Nathaniel Anderson

The Mind Research Network

Kent Kiehl

University of New Mexico

Date Written: September 29, 2016


Our society is founded on a collection of rules regarding acceptable and unacceptable behavior. These rules are shaped by beliefs and values and are subject to revision through the democratic legislative process. For the most part, the rules are well known and widely followed. Society functions on the premise that its members are aware of and will follow the rules. Our criminal justice system, in turn, is designed to determine if a violation of society’s rules occurred and whether that violation warrants a sanction. If so, the justice system assesses the level of responsibility, culpability, and punishment appropriate for individual offenders. Given these responsibilities, the criminal justice system has to make decisions regarding individuals. These decisions often involve prediction. Indeed, most decisions in the criminal justice system involve some form of prediction. Consider, for example, the following decisions: choosing whether or not to grant bail, probation, or parole to an individual; establishing whether an individual is eligible for treatment; and determining his or her appropriate sentence. Each of these processes involves some type of evaluation of an individual in order to make a decision — ideally an informed, objective, and reliable decision — about what he or she is likely to do or to not do in the future.

A key concern for the criminal justice system is an individual’s likelihood of displaying future antisocial behavior, or behavior that involves a disregard for the rules and the well-being of others. The traditional assessments used to evaluate offenders for future risk of antisocial or violent behavior include self-reporting measures, various types of interviews, and expert-administered test batteries. These tools seek to assess possible intellectual and cognitive impairment and to measure psychological and neuropsychological constructs, including personality states and traits. But, given that the brain has the most proximal influence on behavior, direct measures of brain structure and function may be better than proxy measures in predicting future antisocial behavior. The question then becomes: If we can get information from neuroscience techniques, does that information add predictive utility to understanding and assessing antisocial behavior? To date, studies suggest that it does.

Part I of this Article reviews the tools currently available to predict antisocial behavior. Part II discusses legal precedent regarding the use of, and challenges to, various prediction methods. Part III introduces recent neuroscience work in this area and reviews two studies that have successfully used neuroimaging techniques to predict recidivism. Part IV discusses some criticisms that are commonly levied against the various prediction methods and highlights the disparity between the attitudes of the scientific and legal communities toward risk assessment generally and neuroscience specifically. Lastly, Part V explains why neuroscience methods will likely continue to help inform and, ideally, improve the tools we use to help assess, understand, and predict human behavior.

Keywords: Neuroscience, Neuroimaging, Neuroprediction, Future Dangerousness, Antisocial Behavior, Recidivism, Risk Assessment, MRI, fMRI,

Suggested Citation

Gaudet, Lyn M. and Kerkmans, Jason and Anderson, Nathaniel and Kiehl, Kent, Can Neuroscience Help Predict Future Antisocial Behavior? (September 29, 2016). Fordham Law Review, Vol. 85, No. 2, 2016, Available at SSRN:

Lyn M. Gaudet (Contact Author)


2441 Ridgecrest Dr SE
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Jason Kerkmans

MINDSET ( email )

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Nathaniel Anderson

The Mind Research Network ( email )

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Albuquerque, NM 87106
United States
505-272-5028 (Phone)

Kent Kiehl

University of New Mexico ( email )

107 Humanitites Building
Albuquerque, NM 87131-1221
United States

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