Intracerebral mechanisms explaining the impact of incidental feedback on mood state and risky choice
Abstract
Identifying factors whose fluctuations are associated with choice inconsistency is a major issue for rational decision theory. Here, we investigated the neuro-computational mechanisms through which mood fluctuations may bias human choice behavior. Intracerebral EEG data were collected in a large group of subjects (n = 30), while they were performing interleaved quiz and choice tasks that were designed to examine how a series of unrelated feedbacks affects decisions between safe and risky options. Neural baseline activity preceding choice onset was confronted first to mood level, estimated by a computational model integrating the feedbacks received in the quiz task, and then to the weighting of option attributes, in a computational model predicting risk attitude in the choice task. Results showed that 1) elevated broadband gamma activity (BGA) in the ventromedial prefrontal cortex (vmPFC) and dorsal anterior insula (daIns) was respectively signaling periods of high and low mood, 2) increased vmPFC and daIns BGA respectively promoted and tempered risk taking by overweighting gain versus loss prospects. Thus, incidental feedbacks induce brain states that correspond to different moods and bias the evaluation of risky options. More generally, these findings might explain why people experiencing positive (or negative) outcome in some part of their life tend to expect success (or failure) in any other.
Data availability
Due to ethical restrictions on data sharing, we are unable to share raw data for this manuscript to preserve participant anonymity. However, anonymized iEEG data in BIDS format can be made available upon request to the corresponding author (JB) and source data files with anonymized regression estimates are available for download.The custom codes used to (i) extract the different frequency envelopes, and in particular the broadband gamma activity (BGA), from the raw intracranial data, (ii) perform the regression analyses at recording site level, and (iii) compute the second level statistics (across all recording sites of a ROI) are available at: https://gitlab.com/romane-cecchi/publications-code/2022-ieeg-mood-and-risky-choice (Cecchi, 2022; copy archived at https://archive.softwareheritage.org/swh:1:dir:ec43d71a97bf2e3c56b38688eaea2dfde19ad573).
Article and author information
Author details
Funding
Université Grenoble Alpes (ANR-17-CE37-0018)
- Julien Bastin
Université Grenoble Alpes (ANR-18-CE28-0016)
- Julien Bastin
Université Grenoble Alpes (ANR-13-TECS-0013)
- Philippe Kahane
- Julien Bastin
The Czech Science Foundation (20-21339S)
- Jiri Hammer
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: All patients gave written, informed consent before their inclusion in the present study, which received approval from the local ethics committees (CPP 09-CHUG-12, study 0907; CPP18-001b / 2017-A03248-45; IRB00003888; CER No. 47-0913).
Copyright
© 2022, Cecchi et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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