Neural responses to unattended products predict later consumer choices

Abstract

Imagine you are standing at a street with heavy traffic watching someone on the other side of the road. Do you think your brain is implicitly registering your willingness to buy any of the cars passing by outside your focus of attention? To address this question, we measured brain responses to consumer products (cars) in two experimental groups using functional magnetic resonance imaging. Participants in the first group (high attention) were instructed to closely attend to the products and to rate their attractiveness. Participants in the second group (low attention) were distracted from products and their attention was directed elsewhere. After scanning, participants were asked to state their willingness to buy each product. During the acquisition of neural data, participants were not aware that consumer choices regarding these cars would subsequently be required. Multivariate decoding was then applied to assess the choice-related predictive information encoded in the brain during product exposure in both conditions. Distributed activation patterns in the insula and the medial prefrontal cortex were found to reliably encode subsequent choices in both the high and the low attention group. Importantly, consumer choices could be predicted equally well in the low attention as in the high attention group. This suggests that neural evaluation of products and associated choice-related processing does not necessarily depend on attentional processing of available items. Overall, the present findings emphasize the potential of implicit, automatic processes in guiding even important and complex decisions.

Figure 1.

Experimental paradigms. A, In each trial, participants in group 1 (high attention) were presented with images of single cars for 2.4 s followed by a randomized response-button mapping screen (displayed for a variable duration of 7.2–12 s). Participants were instructed to closely attend to products and to actively evaluate the attractiveness of the particular car on a four-point scale by pressing the corresponding response button. B, Participants in group 2 (low attention) were asked to perform a demanding fixation task. They responded to the opening of a centrally presented fixation square (every 800 ms) with a corresponding left- or right-hand button press. The timing parameters applied in group 1 were retained. Every 7.6–12 s, a car was passively presented on the background of the screen for 2.4 s while the fixation task continued. C, After the scanning session, participants from both groups were instructed to realistically picture themselves in a consumer setting where they had to decide upon a new car. Participants were then asked to state their willingness to buy each product. During scanning, participants of both groups were not informed that such a consumer choice would subsequently be required.

Figure 2.

Brain regions encoding subsequent consumer choices in both groups. Multivariate searchlight decoding (radius of 4 voxels) was applied to functional brain responses obtained during product exposure to predict subsequent consumer choices (chance level 50%). Spatial activation patterns in the mPFC and the insula were found to encode these choices when participants did not explicitly deliberate on purchases (p < 0.05, FWE-corrected). Importantly, this applied to situations when participants closely attended to and actively evaluated products (“high attention” group 1, blue) as well as when products were passively presented outside the focus of attention (“low attention” group 2, red). The amount of predictive information in the brain responses was found to be comparably high in both groups. The graph displays mean decoding accuracies and SEs across participants for both regions and both groups. For illustrative purposes, the contrasts are shown at p < 0.0001 (uncorrected) with a cluster threshold of 10 voxels (L indicates left hemisphere).