Comparing Apples and Oranges: the search for a common subjective value representation in the brain

The ability of human subjects to choose between disparate kinds of rewards suggests that the neural circuits for valuing different reward types must converge. Economic theory suggests that these convergence points represent the subjective values (SVs) of different reward types on a common scale for comparison. I will describe two studies related to this theory. First, to directly examine this theory and to map the neural circuits for reward valuation, we had food and water deprived subjects make risky choices for money, food and water both in and out of a brain scanner. In the second study we sought to determine whether the risk preferences of these same rewards change as a function of internal state.

We found that risk preferences across reward types were highly correlated. We also found that partially distinct neural networks represent the SV of monetary and food rewards and that these distinct networks showed specific convergence points. In addition, we show that subjects tend to converge to a similar, weakly risk-averse attitude when deprived.

These results may suggest that partially distinct valuation networks for different reward types converge on a unified valuation network, which enables a direct comparison between different reward types and hence guides valuation and choice. When healthy humans are sated they show heterogeneity of risk preferences, but when deprived a convergence point appears to emerge. It is as if evolution pressure, when resources are scarce, drives humans to a similar level of risk aversion but allows heterogeneity when resources are plentiful.