ArticleCerebral cortex (New York, N.Y. : 1991)2022
Magnetoencephalographic correlates of mood and reward dynamics in human adolescents.
Article in Cerebral cortex (New York, N.Y. : 1991), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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4 citing papers in PubMed, 13 citations in OpenAlex.
- Magnetoencephalography in human neuroscience research: planning, piloting, implementation and quality assurance.Nature protocols · 2026Review
- Abnormal brain functional networks in systemic lupus erythematosus: a graph theory, network-based statistic and machine learning study.Brain communications · 2025Article
- Hedonism as a motive for information search: biased information-seeking leads to biased beliefs.Scientific reports · 2023Article
- Multi-site harmonization for magnetoencephalography spectral power data.Imaging neuroscience (Cambridge, Mass.)Article
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7 authors at 2 institutions in 1 country.
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Abstract
Despite its omnipresence in everyday interactions and its importance for mental health, mood and its neuronal underpinnings are poorly understood. Computational models can help identify parameters affecting self-reported mood during mood induction tasks. Here, we test if computationally modeled dynamics of self-reported mood during monetary gambling can be used to identify trial-by-trial variations in neuronal activity. To this end, we shifted mood in healthy (N = 24) and depressed (N = 30) adolescents by delivering individually tailored reward prediction errors while recording magnetoencephalography (MEG) data. Following a pre-registered analysis, we hypothesize that the expectation component of mood would be predictive of beta-gamma oscillatory power (25-40 Hz). We also hypothesize that trial variations in the source localized responses to reward feedback would be predicted by mood and by its reward prediction error component. Through our multilevel statistical analysis, we found confirmatory evidence that beta-gamma power is positively related to reward expectation during mood shifts, with localized sources in the posterior cingulate cortex. We also confirmed reward prediction error to be predictive of trial-level variations in the response of the paracentral lobule. To our knowledge, this is the first study to harness computational models of mood to relate mood fluctuations to variations in neural oscillations with MEG.
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