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Edited by Wolfram Schultz, University of Cambridge, Cambridge, United Kingdom, and accepted by the Editorial Board July 2, 2014 (received for review April 30, 2014)
Significance
A common question in the social science of well-being asks, “How happy do you feel on a scale of 0 to 10?” Responses are often related to life circumstances, including wealth. By asking people about their feelings as they go about their lives, ongoing happiness and life events have been linked, but the neural mechanisms underlying this relationship are unknown. To investigate it, we presented subjects with a decision-making task involving monetary gains and losses and repeatedly asked them to report their momentary happiness. We built a computational model in which happiness reports were construed as an emotional reactivity to recent rewards and expectations. Using functional MRI, we demonstrated that neural signals during task events account for changes in happiness.
Abstract
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.
Footnotes
- ↵1To whom correspondence should be addressed. Email: robb.rutledge{at}ucl.ac.uk.
Author contributions: R.B.R., N.S., P.D., and R.J.D. designed research; R.B.R. and N.S. performed research; R.B.R. analyzed data; and R.B.R., P.D., and R.J.D. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission. W.S. is a guest editor invited by the Editorial Board.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1407535111/-/DCSupplemental.
Freely available online through the PNAS open access option.
A computational and neural model of happiness
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- Biological Sciences
- Psychological and Cognitive Sciences
- Social Sciences
- Psychological and Cognitive Sciences
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