Predicting the knowledge–recklessness distinction in the human brain

Loading...
Thumbnail Image

Embargo Date

Related Collections

Degree type

Discipline

Subject

neurolaw
mental states
knowledge
recklessness
elastic-net model
Bioethics and Medical Ethics
Neuroscience and Neurobiology
Neurosciences

Funder

Grant number

License

Copyright date

Distributor

Related resources

Author

Vilaresa, Iris
Wesley, Michael J.
Ahn, Woo-Young
Bonnie, Richard J.
Hoffman, Morris
Jones, Owen D.
Yaffe, Gideon
Lohrenz, Terry
Montague, P. Read

Contributor

Abstract

Criminal convictions require proof that a prohibited act was performed in a statutorily specified mental state. Different legal consequences, including greater punishments, are mandated for those who act in a state of knowledge, compared with a state of recklessness. Existing research, however, suggests people have trouble classifying defendants as knowing, rather than reckless, even when instructed on the relevant legal criteria. We used a machine-learning technique on brain imaging data to predict, with high accuracy, which mental state our participants were in. This predictive ability depended on both the magnitude of the risks and the amount of information about those risks possessed by the participants. Our results 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. Some potential legal implications of this result are discussed.

Advisor

Date Range for Data Collection (Start Date)

Date Range for Data Collection (End Date)

Digital Object Identifier

Series name and number

Publication date

2017-03-21

Volume number

Issue number

Publisher

Publisher DOI

Journal Issues

Comments

Recommended citation

Collection