Representation of probabilistic outcomes during risky decision-making

Castegnetti, Giuseppe; Tzovara, Athina; Khemka, Saurabh; Melinščak, Filip; Barnes, Gareth R.; Dolan, Raymond J.; Bach, Dominik R. (2020). Representation of probabilistic outcomes during risky decision-making. Nature Communications, 11(1), p. 2419. Springer Nature 10.1038/s41467-020-16202-y

Preview

Text s41467-020-16202-y.pdf - Published Version Available under License Creative Commons: Attribution (CC-BY). Download (3MB) | Preview

Goal-directed behaviour requires prospectively retrieving and evaluating multiple possible action outcomes. While a plethora of studies suggested sequential retrieval for deterministic choice outcomes, it remains unclear whether this is also the case when integrating multiple probabilistic outcomes of the same action. We address this question by capitalising on magnetoencephalography (MEG) in humans who made choices in a risky foraging task. We train classifiers to distinguish MEG field patterns during presentation of two probabilistic outcomes (reward, loss), and then apply these to decode such patterns during deliberation. First, decoded outcome representations have a temporal structure, suggesting alternating retrieval of the outcomes. Moreover, the probability that one or the other outcome is being represented depends on loss magnitude, but not on loss probability, and it predicts the chosen action. In summary, we demonstrate decodable outcome representations during probabilistic decision-making, which are sequentially structured, depend on task features, and predict subsequent action.

Interest & Impact

Downloads

50 since deposited on 01 Apr 2021
12 in the past 12 months

Citations

5 Citations in Web of Science ®
6 Citations in Scopus

Search

in Google Scholar™

Services

Actions (login required)

Edit item

Actions (login required)

Edit item