Rational choice, neuroeconomy and mixed emotions

Abstract

Experimental psychology has shown differences between predictions of theory of decision and human choices. Emotions like regret can partly explain these differences. Neuroimagery used in combination with behavioural economics (neuroeconomics) has been used in order to try to disentangle the different emotional and rational factors (regret, rejoicing, reward, costs, uncertainty, trade-off between positive and negative aspects of different options). Emotions then appear as much more complex and mixed affective states than usually assumed. Not only might we feel a positive affect in punishing unfair partners, but mixed emotions can, for example, combine transmutation of previous anxiety into relief and elation by comparison with another less exciting option (elating relief). At the level of complexity of these mixed emotions--which we formally represent by comparisons between 'unexpected utilities' and expected ones--the main biases that Kahnemann and Tversky have shown can be explained. In spite of the complexity of these mixed emotions, some of these hypotheses might be partially tested by brain imagery.

Figure 1.

Elation: Expected bigger gain (G_max¹) = G_max¹ × p¹ = Black + Green, Unexpected G_max¹ = Violet + Yellow + Blue = G_max¹ × (1 − p¹), Expected G_max² = Red + Blue = G_max² × p², G_max² (p¹ × p² = Red = G_max² in S1, already subtracted when subtracting expected G¹_max, (G¹_max − G²_max) × (1 − p¹)p² = Yellow: unexpected G¹_max gain in comparison with G²_max in the realm of (1 − p¹) situations. G²_max × p¹(1 − p²) = Brown = in S2, expected G²_max in the realm of (1 − p¹), still to be subtracted, Elation = G¹_max(1 − p¹) − G²_max(1 − p¹)p² = Cube − (Black + Green + Blue) = Yellow + Violet. Additional anxiety: Missed expected bigger gain=G_max¹ × (1 − p¹) = Violet + Yellow + Blue. It has to be subtracted, letting p¹ situations. Missed unexpected bigger gain=G_max¹ × p¹ = Black + Green. Missed expected smaller gain (1 − p²) in the realm of p¹ = G²_max × p¹(1 − p²) = Brown: G²_max in S2. Additional Anxiety: (G_max¹ × p¹) − G_max² × p¹(1 − p²) = Cube − (Violet + Yellow + Blue + Brown) = Black + Green − Brown.