As you stare blankly at the cursor, pondering the opening sentence of your next manuscript, you suddenly notice a familiar intrusion: a gray rectangle swiftly moves in from the upper-right-hand corner of your laptop screen. Within 100 ms of the notification's abrupt appearance, and without an accompanying eye movement, your visual system reflexively allocates attention to the digital notification's location, transiently biasing the processing of visual information emanating from that part of the visual field. Well-controlled, laboratory-based research has revealed a tremendous amount regarding the behavioral and neural consequences of such covert shifts of spatial attention (i.e., those occurring in the absence of observable eye movements), demonstrating that task-irrelevant, abrupt-onset stimuli, even those as simple as small colored circles, reliably elicit the involuntary allocation of visuospatial attention (for a comprehensive review, see
Carrasco, 2011).
As conveyed by the opening example, however, exogenous shifts of spatial attention in everyday life are often elicited by objects in our visual world that, through learning, have become associated with specific kinds of information. For example, if you use Gmail, a pop-up in the lower-right-hand corner captures your attention. Because you have encountered this pop-up many times in the past and have learned its meaning, this sudden onset also alerts you that a chat from a friend has appeared, even before you move your eyes to identify the sender and read the message. Might such meaning-imbued onsets, particularly those that signal the impending delivery of a rewarding stimulus, be more effective at biasing the allocation of spatial attention than those that carry no such associations?
Despite an abundance of interest in and research on the interrelationships between reward, learning, and visual attention over the past decade (for reviews, see
Anderson, 2018;
Awh, Belopolsky, & Theeuwes, 2012;
Chelazzi, Perlato, Santandrea, & Della Libera, 2013;
Failing & Theeuwes, 2018;
Le Pelley, Mitchell, Beesley, George, & Wills, 2016), very little is known about the impact of reward-based associative learning on an abrupt-onset cue's ability to elicit the reflexive allocation of covert spatial attention. Although some studies have used an exogenous spatial cueing paradigm and manipulated the availability of reward from block-to-block (
Bucker & Theeuwes, 2014;
Engelmann & Pessoa, 2007), and another has paired exogenous cues with monetary reward while voluntary spatial attention was reliably preallocated to the target location (
Munneke, Hoppenbrouwers, & Theeuwes, 2015), linking reward with specific features of an abrupt-onset cue itself and comparing the cue's efficacy with that of a nonreward-predictive onset in the absence of spatially informative endogenous cues would provide the empirical data needed to address the question asked earlier. Randomly interleaving the two cue types would also create rapid, trial-to-trial manipulation of reward availability in a way that does not rely on block-to-block changes in the incentive structure, thus allowing researchers to probe the transient impact of reward on task performance more generally (i.e., anytime the reward-predictive cue appears, regardless of its location).
In this study, we aimed to fill this gap in the literature by testing two related hypotheses. First, spatially uninformative, abrupt-onset cues that are predictive of monetary reward (as a result of associative learning), may elicit the involuntary allocation of covert spatial attention more effectively than nonreward-predictive onsets. Given the transient nature of exogenous attention (
Muller & Rabbitt, 1989;
Nakayama & Mackeben, 1989), we focused on the temporal dynamics of the cueing effect in addition to its overall magnitude: if reward-predictive cues capture attention more strongly, we would expect to see significantly larger attentional effects for reward-predictive cues, relative to nonreward-predictive cues; similarly, if reward-predictive onsets capture attention more quickly than do nonreward-predictive onsets, we would expect peak attentional effects for the reward-predictive cues to manifest earlier in time. Second, the presence of peripheral cues that are predictive of monetary reward, regardless of their validity, may impact global attentional processes in a spatially nonspecific manner (e.g., by transiently increasing arousal); if so, we would expect to see improvements in task performance when reward-predictive cues were present, relative to nonreward-predictive cues, irrespective of their location. Both hypotheses are inspired by a large body of research on reinforcement learning showing that the appearance of reward-predictive stimuli elicit a rapidly occurring, dopamine-dependent, reward-prediction signal (for an overview, see:
Daw & Tobler, 2013). In the context of reward-predictive, abrupt onset cues, such stimuli should do double duty (i.e., they should both bias the allocation of spatial attention and engender a reward prediction signal), something that nonreward-predictive, abrupt onset cues should not do. Such a dopamine-dependent, reward-prediction signal may serve to enhance the concomitant selective attention effect generated by these same visual cues (hypothesis 1), it may improve performance globally by, for example, modulating arousal (hypothesis 2), or it may have no impact on behavior in our visual task (the null hypothesis). Psychophysical data, collected using robust methods for manipulating exogenous spatial attention and measuring the resultant impact on behavior, are necessary to guide future research on any potential interaction and to make specific hypotheses related to the neural mechanisms underlying any observed behavioral effects.
To test these hypotheses, we paired monetary reward with one of two luminance-defined, abrupt-onset peripheral cues, each of which was presented at four distinct cue-to-target onset asynchrony durations (
Experiment 1). On each trial, two grating stimuli were briefly presented, one in the left and one in the right visual periphery, and participants were asked to report the orientation of the target grating, as indicated by a response cue. Irrespective of cue type (i.e., reward-predictive or nonreward-predictive), peripheral onsets appeared near the location of the forthcoming target (valid trials) and near the location of the forthcoming distractor (invalid trials) an equal number of times, thus providing no spatially relevant information. Irrespective of cue validity, a monetary bonus was delivered after a correct judgment if the cue on that trial was reward-predictive; no bonus was delivered on nonreward-predictive cue trials. This design allowed us to characterize the impact of reward learning on the reflexive allocation of covert exogenous spatial attention and to assess the temporal dynamics of reward's impact on task performance more generally.
To preview our main results, we found evidence for our second hypothesis: reward-predictive onsets enhanced task performance, regardless of their location, but this improvement took time to manifest, becoming statistically significant only at our final stimulus-onset-asynchrony (SOA). In a follow-up study (
Experiment 2), we replicated our primary finding in an independent group of naive observers and evaluated whether this boost in performance was maintained at longer SOA durations.