Predicting risky choices from brain activity patterns.

Abstract:

:Previous research has implicated a large network of brain regions in the processing of risk during decision making. However, it has not yet been determined if activity in these regions is predictive of choices on future risky decisions. Here, we examined functional MRI data from a large sample of healthy subjects performing a naturalistic risk-taking task and used a classification analysis approach to predict whether individuals would choose risky or safe options on upcoming trials. We were able to predict choice category successfully in 71.8% of cases. Searchlight analysis revealed a network of brain regions where activity patterns were reliably predictive of subsequent risk-taking behavior, including a number of regions known to play a role in control processes. Searchlights with significant predictive accuracy were primarily located in regions more active when preparing to avoid a risk than when preparing to engage in one, suggesting that risk taking may be due, in part, to a failure of the control systems necessary to initiate a safe choice. Additional analyses revealed that subject choice can be successfully predicted with minimal decrements in accuracy using highly condensed data, suggesting that information relevant for risky choice behavior is encoded in coarse global patterns of activation as well as within highly local activation within searchlights.

authors

Helfinstein SM,Schonberg T,Congdon E,Karlsgodt KH,Mumford JA,Sabb FW,Cannon TD,London ED,Bilder RM,Poldrack RA

doi

10.1073/pnas.1321728111

subject

Has Abstract

pub_date

2014-02-18 00:00:00

pages

2470-5

issue

7

eissn

0027-8424

issn

1091-6490

pii

1321728111

journal_volume

111

pub_type

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