computational and neural model of momentary subjective well-being

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 111; no. 33; pp. 12252 - 12257
• Main Authors: Rutledge, Robb B., Skandali, Nikolina, Dayan, Peter, Dolan, Raymond J.
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 19.08.2014; National Acad Sciences
• Subjects: Adult; Basal ganglia; Behavioral neuroscience; Biological Sciences; Computational Biology; Computational modeling; demographic statistics; Dopamine; Emotional states; Emotions; Experimentation; Female; Happiness; Humans; life events; Magnetic Resonance Imaging; Male; Mathematical models; Modeling; Models, Psychological; Neurons; Neurons - physiology; prediction; Probability; Quality of life; Reward; Social Sciences; Well being; Wellbeing; Young Adult; reward prediction error; striatum; insula; dopamine
• ISSN: 0027-8424; 1091-6490; 1091-6490
• DOI: 10.1073/pnas.1407535111

The subjective well-being or happiness of individuals is an important metric for societies. Although happiness is influenced by life circumstances and population demographics such as wealth, we know little about how the cumulative influence of daily life events are aggregated into subjective feelings. Using computational modeling, we show that emotional reactivity in the form of momentary happiness in response to outcomes of a probabilistic reward task is explained not by current task earnings, but by the combined influence of recent reward expectations and prediction errors arising from those expectations. The robustness of this account was evident in a large-scale replication involving 18,420 participants. Using functional MRI, we show that the very same influences account for task-dependent striatal activity in a manner akin to the influences underpinning changes in happiness.