Citation

Sacré P, Kerr MSD, Subramanian S, Fitzgerald Z, Kahn K, Johnson MA, Niebur E, Eden UT, González-Martínez JA, Gale JT, Sarma SV. Proc. Natl. Acad. Sci. U. S. A. 2019; 116(4): 1404-1413.

Affiliation

Institute for Computational Medicine, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218; psacre1@jhu.edu ssarma2@jhu.edu.

Copyright

(Copyright © 2019, National Academy of Sciences)

DOI

10.1073/pnas.1811259115

PMID

30617071

Abstract

A person's decisions vary even when options stay the same, like when a gambler changes bets despite constant odds of winning. Internal bias (e.g., emotion) contributes to this variability and is shaped by past outcomes, yet its neurobiology during decision-making is not well understood. To map neural circuits encoding bias, we administered a gambling task to 10 participants implanted with intracerebral depth electrodes in cortical and subcortical structures. We predicted the variability in betting behavior within and across patients by individual bias, which is estimated through a dynamical model of choice. Our analysis further revealed that high-frequency activity increased in the right hemisphere when participants were biased toward risky bets, while it increased in the left hemisphere when participants were biased away from risky bets. Our findings provide electrophysiological evidence that risk-taking bias is a lateralized push-pull neural system governing counterintuitive and highly variable decision-making in humans.

Copyright © 2019 the Author(s). Published by PNAS.

Language: en

Keywords

human decision-making; neural encoding; risk-taking dynamic bias; stereoelectroencephalography; stochastic dynamic model