Year: 2020
Type: article
Abstract: 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.
Source: Nature Communications
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $5,380
Funders: National Science Foundation, University of Bern, Wellcome Trust, National Institute for Health and Care Research, European Commission, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Max-Planck-Gesellschaft, University College London Hospitals NHS Foundation Trust
Awards: Core support for the Wellcome Trust Centre for Neuroimaging, Neural and computational mechanisms of regularity extraction in the human brain, G33445216, G4113525484, G434337789, The neurobiology of motivation in health and disease., G574514749, Core support for the Wellcome Trust Centre for Neuroimaging., G7044017406, G8638694832, G880118091
OpenAlex ID: W3024804797