Browsing by Author "Wesley, Michael J."

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    Choosing Money over Drugs: The Neural Underpinnings of Difficult Choice in Chronic Cocaine Users
    Wesley, Michael J.; Lohrenz, Terry; Koffarnus, Mikhail N.; McClure, Samuel M.; De La Garza, Richard II; Salas, Ramiro; Thompson-Lake, Daisy G. Y.; Newton, Thomas F.; Bickel, Warren K.; Montague, P. Read (Hindawi, 2014-08-14)
    Addiction is considered a disorder that drives individuals to choose drugs at the expense of healthier alternatives. However, chronic cocaine users (CCUs)who meet addiction criteria retain the ability to choose money in the presence of the opportunity to choose cocaine. The neural mechanisms that differentiate CCUs from non-cocaine using controls (Controls) while executing these preferred choices remain unknown. Thus, therapeutic strategies aimed at shifting preferences towards healthier alternatives remain somewhat uninformed. This study used BOLD neuroimaging to examine brain activity as fifty CCUs and Controls performed single- and cross-commodity intertemporal choice tasks for money and/or cocaine. Behavioral analyses revealed preferences for each commodity type. Imaging analyses revealed the brain activity that differentiated CCUs from Controls while choosing money over cocaine. We observed thatCCUs devalued future commodities more than Controls. Choices for money as opposed to cocaine correlated with greater activity in dorsal striatum of CCUs, compared to Controls. In addition, choices for future money as opposed to immediate cocaine engaged the left dorsolateral prefrontal cortex (DLPFC) of CCUs more than Controls. These data suggest that the ability of CCUs to execute choices away from cocaine relies on activity in the dorsal striatum and left DLPFC.
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    Predicting the knowledge–recklessness distinction in the human brain
    Vilares, Iris; Wesley, Michael J.; Ahn, Woo-Young; Hoffman, Morris; Jones, Owen D.; Morse, Stephen J.; Yaffe, Gideon; Lohrenz, Terry; Montague, P. Read; Bonnie, Richard J. (NAS, 2017-02-09)
    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.