A Range-Normalization Model of Context-Dependent Choice: A New Model and Evidence

Abstract

Most utility theories of choice assume that the introduction of an irrelevant option (called the decoy) to a choice set does not change the preference between existing options. On the contrary, a wealth of behavioral data demonstrates the dependence of preference on the decoy and on the context in which the options are presented. Nevertheless, neural mechanisms underlying context-dependent preference are poorly understood. In order to shed light on these mechanisms, we design and perform a novel experiment to measure within-subject decoy effects. We find within-subject decoy effects similar to what have been shown previously with between-subject designs. More importantly, we find that not only are the decoy effects correlated, pointing to similar underlying mechanisms, but also these effects increase with the distance of the decoy from the original options. To explain these observations, we construct a plausible neuronal model that can account for decoy effects based on the trial-by-trial adjustment of neural representations to the set of available options. This adjustment mechanism, which we call range normalization, occurs when the nervous system is required to represent different stimuli distinguishably, while being limited to using bounded neural activity. The proposed model captures our experimental observations and makes new predictions about the influence of the choice set size on the decoy effects, which are in contrast to previous models of context-dependent choice preference. Critically, unlike previous psychological models, the computational resource required by our range-normalization model does not increase exponentially as the set size increases. Our results show that context-dependent choice behavior, which is commonly perceived as an irrational response to the presence of irrelevant options, could be a natural consequence of the biophysical limits of neural representation in the brain.

Author Summary

While faced with a decision between two options for which you have no clear preference (say, a small cheap TV and a large expensive TV), you are presented with a new but inferior option (say, a medium expensive TV). The mere presence of the new option, which you would not select anyway, shifts your preference toward the expensive large TV. This simple example shows how the introduction of an irrelevant option, called the “decoy,” to the choice set can change preference between existing options, a phenomenon often called the context-dependent preference reversal. A number of models have been proposed to explain context effects. Despite their success, they are either uninformative about the underlying neural mechanisms or they require comparison of every possible pair of option attributes, a computation that is unlikely to be implemented by the nervous system due to its high computational demand and undesirable outcomes when the choice set size increases. Here we present a novel account of the context-dependent preference based on the adjustment of neural response to the set of available options. Moreover, we show results from a novel behavioral task designed to test contrasting predictions of our model and a classic model of context effects.