On the feature specificity of value-driven attention

Trichotomy revisited: A monolithic theory of attentional control

The control of attention was long held to reflect the influence of two competing mechanisms of assigning priority, one goal-directed and the other stimulus-driven. Learning-dependent influences on the control of attention that could not be attributed to either of those two established mechanisms of control gave rise to the concept of selection history and a corresponding third mechanism of attentional control. The trichotomy framework that ensued has come to dominate theories of attentional control over the past decade, replacing the historical dichotomy. In this theoretical review, I readily affirm that distinctions between the influence of goals, salience, and selection history are substantive and meaningful, and that abandoning the dichotomy between goal-directed and stimulus-driven mechanisms of control was appropriate. I do, however, question whether a theoretical trichotomy is the right answer to the problem posed by selection history. If we reframe the influence of goals and selection history as different flavors of memory-dependent modulations of attentional priority and if we characterize the influence of salience as a consequence of insufficient competition from such memory-dependent sources of priority, it is possible to account for a wide range of attention-related phenomena with only one mechanism of control. The monolithic framework for the control of attention that I propose offers several concrete advantages over a trichotomy framework, which I explore here.

Generalisation of value-based attentional priority is category-specific

A large body of research suggests that previously reward-associated stimuli can capture attention. Recent evidence also suggests that value-driven attentional biases can occur for a particular category of objects. However, it is unclear how broadly these category-level attentional biases can generalise. In the present study, we examined whether value-driven attentional biases can generalise to new exemplars of a category or semantically related categories using a modified version of the value-driven attentional capture paradigm. In an initial training phase, participants searched for two categories of objects and were rewarded for correctly fixating members of one target category. In a subsequent test phase, participants searched for two new categories of objects. A new exemplar of one of the previous target categories or a member of a semantically related category could appear as a critical distractor in this phase. Participants were more likely to initially fixate the critical distractor and fixated the distractor longer when it was a new exemplar of the previously rewarded category. However, similar findings were not observed for members of semantically related categories. Together, these findings suggest that the generalisation of value-based attentional priority is category-specific.

This is a test: Oculomotor capture when the experiment keeps score

Physically salient stimuli are difficult to ignore, frequently eliciting fixations even when they are known to be task-irrelevant. A recent study demonstrated that distractor fixation-contingent auditory feedback was highly effective in reducing the frequency of fixations on such stimuli. The present study explores more specifically what it is about feedback that makes it effective in curbing oculomotor behavior. In one experiment, we removed the immediacy of the feedback by informing participants after each trial via textual feedback if they had fixated the distractor. A comparable reduction in the frequency of oculomotor capture was observed. In a second experiment, we only provided summary feedback concerning the frequency of oculomotor capture after each block of trials. Not only were the benefits of feedback again robustly comparable, but a benefit was observed even in the first block before any feedback had actually been presented. Simply knowing that the frequency of distractor fixations was being monitored was sufficient to substantially reduce the frequency of oculomotor capture. Interestingly, trial-level feedback predominantly reduced the frequency of capture by slowing oculomotor responses, reflecting a speed-accuracy tradeoff, whereas block-wise feedback resulted in a reduction in the frequency of capture with saccadic reaction time equated, reflecting a bona fide improvement in task performance. Our findings have implications for our understanding of the role of motivation, strategy, and selection history in oculomotor control.

The past, present, and future of selection history

The last ten years of attention research have witnessed a revolution, replacing a theoretical dichotomy (top-down vs. bottom-up control) with a trichotomy (biased by current goals, physical salience, and selection history). This third new mechanism of attentional control, selection history, is multifaceted. Some aspects of selection history must be learned over time whereas others reflect much more transient influences. A variety of different learning experiences can shape the attention system, including reward, aversive outcomes, past experience searching for a target, target‒non-target relations, and more. In this review, we provide an overview of the historical forces that led to the proposal of selection history as a distinct mechanism of attentional control. We then propose a formal definition of selection history, with concrete criteria, and identify different components of experience-driven attention that fit within this definition. The bulk of the review is devoted to exploring how these different components relate to one another. We conclude by proposing an integrative account of selection history centered on underlying themes that emerge from our review.

Reward-driven attention alters perceived salience

Many studies have revealed that reward-associated features capture attention. Neurophysiological evidence further suggests that this reward-driven attention effect modulates visual processes by enhancing low-level visual salience. However, no behavioral study to date has directly examined whether reward-driven attention changes how people see. Combining the two-phase paradigm with a psychophysical method, the current study found that compared with nonsalient cues associated with lower reward, the nonsalient cues associated with higher reward captured more attention, and increased the perceived contrast of the subsequent stimuli. This is the first direct behavioral evidence of the effect of reward-driven attention on low-level visual perception.

Neurobiology of value-driven attention

What we pay attention to is influenced by reward learning. Converging evidence points to the idea that associative reward learning changes how visual stimuli are processed in the brain, rendering learned reward cues difficult to ignore. Behavioral evidence distinguishes value-driven attention from other established control mechanisms, suggesting a distinct underlying neurobiological process. Recently, studies have begun to explore the neural substrates of this value-driven attention mechanism. Here, I review the progress that has been made in this area, and synthesize the findings to provide an integrative account of the neurobiology of value-driven attention. The proposed account can explain both attentional capture by previously rewarded targets and the modulatory effect of reward on priming, as well as the decoupling of reward history and prior task relevance in value-driven attention.

Selection history: How reward modulates selectivity of visual attention

Visual attention enables us to selectively prioritize or suppress information in the environment. Prominent models concerned with the control of visual attention differentiate between goal-directed, top-down and stimulus-driven, bottom-up control, with the former determined by current selection goals and the latter determined by physical salience. In the current review, we discuss recent studies that demonstrate that attentional selection does not need to be the result of top-down or bottom-up processing but, instead, is often driven by lingering biases due to the "history" of former attention deployments. This review mainly focuses on reward-based history effects; yet other types of history effects such as (intertrial) priming, statistical learning and affective conditioning are also discussed. We argue that evidence from behavioral, eye-movement and neuroimaging studies supports the idea that selection history modulates the topographical landscape of spatial "priority" maps, such that attention is biased toward locations having the highest activation on this map.