The goal of this study was to characterize neural predictors of purchasing. We hypothesized and found that activation in regions associated with anticipating gain (the NAcc) correlated with product preference, while activation in regions associated with anticipating loss (the insula) correlated with excessive prices. Further, activation in a region implicated in integrating gains and losses (the MFPC) correlated with reduced prices. Analyses of time course data extracted from each of these regions indicated that while NAcc activation initially predicted subsequent purchasing decisions during product presentation, insula and MPFC activation initially predicted subsequent purchasing decisions during price presentation. Even after controlling for retrospective self-reported preference and purchasing price, activation in these brain regions independently predicted decisions to purchase. Validation analyses indicated that the ability of brain activation to predict purchasing would generalize to other purchasing scenarios. The results did not vary significantly as a function of subjects’ sex, and replicated across two different sets of products. Together, these findings suggest that activation of distinct brain regions related to anticipation of gain and loss precedes and can be used to predict purchasing decisions.
While several other brain regions have been implicated in decision-making in both
comparative and human research, these regions did not play central roles in the present study,
perhaps due to specific aspects of the SHOP task (Supplement 4
). For instance, the parietal cortex has been implicated in decision-making (Huettel et al., 2005
; Platt and Glimcher, 1999
). However, while many decision-making tasks that elicit parietal activation involve a spatial component, the SHOP task minimizes spatial demands by presenting items and prices sequentially in the center of the screen. Thus, parietal activation may play a role in mapping evaluative information to spatial action plans, but was not observed in relation to the variables of interest in this task. Anterior cingulate activation has also been implicated in decision-making (Volz et al., 2005
), but may be more related to conflict between potentially competing courses of action (Botvinick et al., 1999
). For instance, in a financial decision-making task, while anterior cingulate activation was related to response conflict, it did not predict subsequent risk-seeking versus risk-averse choices (Kuhnen and Knutson, 2005
). Similarly, in the SHOP task, anterior cingulate activation was greatest in situations involving high response conflict (e.g., long reaction times to choose, items with high preference but also high price, etc.), but did not significantly add to other brain regions’ ability to predict purchasing decisions. Thus, while anterior cingulate activation may facilitate conflict resolution, activation in this region does not necessarily predict how conflict will be resolved. Amygdalar and orbitofrontal cortex activation have also been implicated in decision-making (Bechara et al., 2000
), but did not significantly predict purchasing in this task. While activation of these regions has been most robustly elicited in situations involving learning, the SHOP task is designed to minimize learning demands. Unlike studies that focus on how preferences are established, this study instead focused on how people decide to purchase based on already-established preferences.
The study’s design and additional analyses ruled out a number of alternative
accounts of brain activation prior to the purchase decision. First, anticipatory activation
could not be attributed to increased motor preparation prior to purchasing, since subjects had
to press a button to indicate either the choice to purchase or not to purchase a product, and
did not know which button would indicate purchasing versus not purchasing until the choice
prompt appeared (thus sequestering motor preparation and execution to the choice period).
Further, reaction times did not differ between decisions to purchase or not to purchase.
Self-reported familiarity with products (collected in a subset of 20 subjects) also could not
account for the correlation between NAcc activation and preference, since additional
localization analyses indicated that familiarity was not correlated with NAcc activation during
the product and price periods, and prediction analyses including familiarity as an independent
variable did not reduce the ability of NAcc activation to predict purchasing, and only slightly
increased overall model fit (Supplement 5
). Additionally, the few trials involving previously-owned items were omitted from analyses. Similarly, price alone could not account for the correlation between MFPC activation and price differential, since additional localization analyses indicated that price was not significantly correlated with MPFC activation during the price period, and prediction analyses including price did not reduce the ability of MPFC activation to predict purchasing, although inclusion of price did increase overall model fit (Supplement 6
). These findings are consistent with the idea that people do not react as much to absolute price as to the price relative to what they think is acceptable for a given product (Thaler, 1985
) (making it difficult to determine whether prices are high or low without knowing their associated product). Finally, anticipatory activation could not be attributed to a global increase in neural recruitment (as might be expected in the case of general arousal), since while NAcc and MPFC showed increased activation prior to purchasing, insula instead showed decreased activation prior to purchasing.
To maximize subject engagement and minimize distraction, SHOP task trials progressed at
a fairly rapid pace (i.e., 4 sec per trial phase). While prior studies indicate that hemodynamic
responses in the volumes of interest (i.e., NAcc, MPFC, insula) typically peak from 4–6
sec after stimulus onset (Knutson et al., 2003
hemodynamic response can rise as early as 2 sec after stimulus onset, raising potential concerns
about the separability of signals during different trial phases. These concerns might
specifically affect inferences about localization (e.g., MPFC activation depends on the
revelation of price -- but not product -- information), and prediction (e.g., MPFC activation
begins to predict purchasing after price -- but not choice -- information is revealed). However,
reanalysis indicated that models in which the price differential regressor was lagged forward
(by 4 sec into the product period) no longer elicited correlated activation in the MPFC or right
insula (Supplement 7
). This finding
suggests that the correlation of MFPC activation with price differential depended upon the
revelation of price information. Additionally, brain activation extracted from the MPFC and
right insula during product presentation (i.e., prior to price presentation by 4 sec) did not
significantly predict purchasing. Two additional experiments were conducted to verify the
dependence of MPFC and right insula results on the appearance of price information (Supplements 8–9
). In a first
additional experiment (n=8 males), lagging the appearance of price information (by 4
sec) also lagged the correlation of MPFC and right insula activation with price differential.
Similarly, lagged MPFC activation also best predicted subsequent purchasing (Supplement 8
). In a second additional
experiment (n=8 males), lagging the onset of the choice period (by 4 sec) did not alter
MPFC or right insula activation’s correlation with price differential, and activation in
these regions during the price period continued to predict purchasing (Supplement 9
). Together, these findings suggest that whereas NAcc activation reflected subjects’ reaction to products, MPFC and insula activation reflected subjects’ reaction to price information. In all experiments, NAcc activation begins to predict purchasing during the product period, while MPFC and insula activation begin to predict purchasing during the price period.
Activation in the hypothesized regions (i.e., NAcc, MPFC, and insula) conformed to most,
but not all, predictions. Activation in all three regions correlated more robustly with
subjective variables (i.e., product preference, price differential) than with objective
variables (i.e., product identity, price) (Supplement 11
). NAcc activation correlated strongly with product preference, discriminating between eventually purchased and not purchased products as soon as the product was displayed, while MPFC activation correlated strongly with price differential, and did not discriminate between eventually purchased and not purchased products until the price was displayed. These findings are consistent with distinct gain prediction accounts of NAcc function and gain prediction error accounts of MPFC function (Knutson et al., 2003
). While right insula showed deactivation during the price period, activation in this region did not significantly correlate with price differential, although it did correlate nonsignificantly in the predicted direction (conjoined Z=−1.36), and also discriminated between eventually purchased and unpurchased products. These findings are not inconsistent with a loss prediction account of insula function (Paulus and Stein, 2006
), since validation analyses further indicated that insula deactivation predicted purchasing, but may suggest an influence of other factors besides excessive price on insula activation (e.g., responses to nonpreference or a more prolonged response). Thus, the specificity of the insula response to excessive prices remains to be clarified by future research.
The present findings have several implications. With respect to neuroscience, by implicating common circuits (i.e., NAcc, MPFC, and insula) in decisions to purchase diverse products, the findings are consistent with a “common currency” account of purchasing (Knutson et al., 2005
; Montague and Berns, 2002
; Shizgal, 1997
). However, they additionally suggest that decisions to purchase may involve distinct dimensions related to anticipated gain and loss, rather than just a single dimension related to anticipated gain. These findings not only add to prior studies of product preference, but also link to studies of social decisions that implicate NAcc activation in the intention to cooperate (King-Casas et al., 2005
; Rilling et al., 2002
) and insula activation in the intention to defect (Sanfey et al., 2003
). Thus, these findings further illustrate the power of the neuroeconomic approach to elucidate distinct neuropsychological components that may exert consistent collective influences on subsequent purchasing decisions. They also suggest that even commonplace purchasing decisions can be deconstructed with methods adopted from psychology, economics, and neuroscience.
With respect to economic theory, the findings support the historical notion that individuals have immediate affective reactions to potential gain and loss, which serve as inputs into decisions about whether or not to purchase a product (Kuhnen and Knutson, 2005
). This finding has implications for understanding behavioral anomalies, such as consumers’ growing tendency to overspend and undersave when purchasing with credit cards rather than cash. Specifically, the abstract nature of credit coupled with deferred payment may “anaesthetize” consumers against the pain of paying (Prelec and Loewenstein, 1998
). Neuroeconomic findings thus might eventually suggest methods of restructuring institutional incentives to facilitate increased saving.
Finally, the results illustrate a novel technical application of FMRI, in which brain activation is used to predict purchasing decisions on-line. Whether added information from FMRI data is more cost-effective than simple self-report remains to be established, and may depend upon future methodological and technical advances. FMRI prediction methods may eventually prove most useful in situations when people’s behavior and self-reported preferences diverge.
In summary, this study provides initial evidence that specific patterns of brain activation predict purchasing. Prior to the purchase decision, preference elicits NAcc activation, while excessive prices can elicit insula activation and MPFC deactivation. Anticipatory neural activation in these regions predicts subsequent purchasing decisions. The findings are consistent with the hypothesis that the brain frames preference as a potential benefit and price as a potential cost, and lend credence to the notion that consumer purchasing reflects an anticipatory combination of preference and price considerations. A physiological account of these factors may facilitate neurally-constrained theories of human decision-making (Glimcher and Rustichini, 2004
). Such theories may not only help scientists to decompose the components that go into decisions, but also to build neuroeconomic models that better predict choice and inform policy.