Neurobiology of value integration: When value impacts valuation (2011)
Authors
Abstract
Everyday choice options have advantages (positive values) and disadvantages (negative values) that need to be integrated into an overall subjective value. For decades, economic models have assumed that when a person evaluates a choice option, different values contribute independently to the overall subjective value of the option. However, human choice behavior often violates this assumption, suggesting interactions between values. To investigate how qualitatively different advantages and disadvantages are integrated into an overall subjective value, we measured the brain activity of human subjects using fMRI while they were accepting or rejecting choice options that were combinations of monetary reward and physical pain. We compared different subjective value models on behavioral and neural data. These models all made similar predictions of choice behavior, suggesting that behavioral data alone are not sufficient to uncover the underlying integration mechanism. Strikingly, a direct model comparison on brain data decisively demonstrated that interactive value integration (where values interact and affect overall valuation) predicts neural activity in value-sensitive brain regions significantly better than the independent mechanism. Furthermore, effective connectivity analyses revealed that value-dependent changes in valuation are associated with modulations in subgenual anterior cingulate cortex-amygdala coupling. These results provide novel insights into the neurobiological underpinnings of human decision making involving the integration of different values.
Bibliographic entry
Park, S. Q., Kahnt, T., Rieskamp, J., & Heekeren, H. R. (2011). Neurobiology of value integration: When value impacts valuation. The Journal of Neuroscience, 31, 9307-9314. doi:10.1523/JNEUROSCI.4973-10.2011 (Full text)
Miscellaneous
Publication year | 2011 | |
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Document type: | Article | |
Publication status: | Published | |
External URL: | http://dx.doi.org/10.1523/JNEUROSCI.4973-10.2011 View | |
Categories: | Forecasting | |
Keywords: |