Cultural Neuroeconomics of Intertemporal Choice

The advantages of the presented q-generalized learning rule in a neural net-
work model (Cannas, Stariolo, & Tamarit, 1996; Hadzibeganovic & Cannas,
2007; submitted) span beyond classical learning applications. The model may
also help in studying other problems in cognitive (neuro)science such as neuro-
logical impairments. Moreover, the model could serve as an example of how to
generalize and improve other neural networks that have regularly been used in
several different areas of economics.

By means of estimating the index q in the presented q-exponential discount
model, the inconsistency in choice behavior may be expressed in a continuous
manner (where a whole spectrum of q indices may be obtained corresponding
to different inconsistencies in choice; with smaller q values indicating more in-
consistent choices). Future studies should also examine and model the behavior
of alcohol or drug addicted patients, people with orbitofrontal lesion, patho-
logical gamblers, and other individuals who were previously shown to have
impaired decision-making behavior in inter-temporal choice. By utilizing the
q-exponential discount function, one could diagnose the degree of inconsistency
in choice in these patients with greater sensitivity and accuracy than with many
currently available methods.

Finally, we note that no neuroeconomic theory of temporal discounting is
going to be complete until it can fully incorporate the cultural aspects of im-
pulsivity and inconsistency in decision making, the underlying cognitive and
neurocomputational processes, emotionally driven choice aspects, and other
(neuro)biological properties in humans that may drive the dynamics of eco-
nomic behavior.

References

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[2] Boettiger, C.A., Mitchell, J.M., Tavares, V.C., Robertson, M., Joslyn, G.,
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Fronto-parietal networks and a role for the catechol-O-methyltransferase
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[3] Cannas, S. A., Stariolo, D., & Tamarit, F. A. (1996). Learning dynamics
of simple perceptrons with non-extensive cost functions. Network: Com-
putation in Neural Sciences, 7, 141-149.

[4] Cajueiro, D.O. (2006). A note on the relevance of the q-exponential func-
tion in the context of intertemporal choices. Physica A: Statistical Me-
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[5] Chiao, J.Y., & Ambady, N. (2007). Cultural neuroscience: Parsing uni-
versality and diversity across levels of analysis. In Kitayama, S. & Cohen,
D. (Eds.) Handbook of Cultural Psychology (pp. 237-254). NY: Guilford
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