Suppression history of distractor location biases attentional and oculomotor control

Reliability of individual differences in distractor suppression driven by statistical learning

A series of recent studies has demonstrated that attentional selection is modulated by statistical regularities, even when they concern task-irrelevant stimuli. Irrelevant distractors presented more frequently at one location interfere less with search than distractors presented elsewhere. To account for this finding, it has been proposed that through statistical learning, the frequent distractor location becomes suppressed relative to the other locations. Learned distractor suppression has mainly been studied at the group level, where individual differences are treated as unexplained error variance. Yet these individual differences may provide important mechanistic insights and could be predictive of cognitive and real-life outcomes. In the current study, we ask whether in an additional singleton task, the standard measures of attentional capture and learned suppression are reliable and stable at the level of the individual. In an online study, we assessed both the within- and between-session reliability of individual-level measures of attentional capture and learned suppression. We show that the measures of attentional capture, but not of distractor suppression, are moderately stable within the same session (i.e., split-half reliability). Test-retest reliability over a 2-month period was found to be moderate for attentional capture but weak or absent for suppression. RT-based measures proved to be superior to accuracy measures. While producing very robust findings at the group level, the predictive validity of these RT-based measures is still limited when it comes to individual-level performance. We discuss the implications for future research drawing on inter-individual variation in the attentional biases that result from statistical learning.

The dynamics of statistical learning in visual search and its interaction with salience processing: An EEG study

Visual attention can be guided by statistical regularities in the environment, that people implicitly learn from past experiences (statistical learning, SL). Moreover, a perceptually salient element can automatically capture attention, gaining processing priority through a bottom-up attentional control mechanism. The aim of our study was to investigate the dynamics of SL and if it shapes attentional target selection additively with salience processing, or whether these mechanisms interact, e.g. one gates the other. In a visual search task, we therefore manipulated target frequency (high vs. low) across locations while, in some trials, the target was salient in terms of colour. Additionally, halfway through the experiment, the high-frequency location changed to the opposite hemifield. EEG activity was simultaneously recorded, with a specific interest in two markers related to target selection and post-selection processing, respectively: N2pc and SPCN. Our results revealed that both SL and saliency significantly enhanced behavioural performance, but also interacted with each other, with an attenuated saliency effect at the high-frequency target location, and a smaller SL effect for salient targets. Concerning processing dynamics, the benefit of salience processing was more evident during the early stage of target selection and processing, as indexed by a larger N2pc and early-SPCN, whereas SL modulated the underlying neural activity particularly later on, as revealed by larger late-SPCN. Furthermore, we showed that SL was rapidly acquired and adjusted when the spatial imbalance changed. Overall, our findings suggest that SL is flexible to changes and, combined with salience processing, jointly contributes to establishing attentional priority.

Terms of debate: Consensus definitions to guide the scientific discourse on visual distraction

Hypothesis-driven research rests on clearly articulated scientific theories. The building blocks for communicating these theories are scientific terms. Obviously, communication - and thus, scientific progress - is hampered if the meaning of these terms varies idiosyncratically across (sub)fields and even across individual researchers within the same subfield. We have formed an international group of experts representing various theoretical stances with the goal to homogenize the use of the terms that are most relevant to fundamental research on visual distraction in visual search. Our discussions revealed striking heterogeneity and we had to invest much time and effort to increase our mutual understanding of each other's use of central terms, which turned out to be strongly related to our respective theoretical positions. We present the outcomes of these discussions in a glossary and provide some context in several essays. Specifically, we explicate how central terms are used in the distraction literature and consensually sharpen their definitions in order to enable communication across theoretical standpoints. Where applicable, we also explain how the respective constructs can be measured. We believe that this novel type of adversarial collaboration can serve as a model for other fields of psychological research that strive to build a solid groundwork for theorizing and communicating by establishing a common language. For the field of visual distraction, the present paper should facilitate communication across theoretical standpoints and may serve as an introduction and reference text for newcomers.

Statistical learning of target and distractor spatial probability shape a common attentional priority computation

Converging evidence recently put forward the notion that dedicated neurocognitive mechanisms do exist for the suppression of salient, but irrelevant distractors. Along this line, it is plausible to hypothesize that, in appropriate contexts, experience-dependent forms of attentional learning might selectively induce plastic changes within this dedicated circuitry, thus allowing an independent shaping of priorities at the service of attentional filtering. Conversely, previous work suggested that statistical learning (SL) of both target and distractor spatial probability distributions converge in adjusting only the overall attentional priority of locations: in fact, in the presence of an independent manipulation, either related to the target or to the distractor only, SL induces indirect effects (e.g., changes in filtering efficiency due to an uneven distribution of targets), suggesting that SL-induced plastic changes affect a shared neural substrate. Here we tested whether, when (conflicting) target- and distractor-related manipulations are concurrently applied to the very same locations, dedicated mechanisms might support the selective encoding of spatial priority in relation to the specific attentional operation involved. In three related experiments, human healthy participants discriminated the direction of a target arrow, while ignoring a salient distractor, if present; both target and distractor spatial probability distributions were concurrently manipulated in relation to each single location. Critically, the selection bias produced by the target-related SL was marginally reduced by an adverse distractor contingency, and the suppression bias generated by the distractor-related SL was erased, or even reversed, by an adverse target contingency. Our results suggest that even conflicting target- and distractor-related SL manipulations result in the adjustment of a unique spatial priority computation, likely because the process directly relies on direct plastic alterations of shared spatial priority map(s).

Statistical learning of target location and distractor location rely on different mechanisms during visual search

More studies have demonstrated that people have the capacity to learn and make use of environmental regularities. This capacity is known as statistical learning (SL). Despite rich empirical findings, it is not clear how the two forms of SL (SL of target location and SL of distractor location) influence visual search and whether they rely on the shared cognitive mechanism. In Experiment 1 and Experiment 2, we manipulated the probability of target location and the probability of distractor location, respectively. The results suggest that attentional guidance (they referred to overt attention) may mainly contribute to the SL effect of the target location and the distractor location, which is in line with the notion of priority mapping. To a small extent, facilitation of response selection may also contribute to the SL effect of the target location but does not contribute to the SL effect of the distractor location. However, the main difference between the two kinds of SL occurred in the early stage (it involved covert attention). Together, our findings indicate that the two forms of SL reflect partly shared and partly independent cognitive mechanisms.

What to expect where and when: how statistical learning drives visual selection

While the visual environment contains massive amounts of information, we should not and cannot pay attention to all events. Instead, we need to direct attention to those events that have proven to be important in the past and suppress those that were distracting and irrelevant. Experiences molded through a learning process enable us to extract and adapt to the statistical regularities in the world. While previous studies have shown that visual statistical learning (VSL) is critical for representing higher order units of perception, here we review the role of VSL in attentional selection. Evidence suggests that through VSL, attentional priority settings are optimally adjusted to regularities in the environment, without intention and without conscious awareness.

Statistical learning in visual search reflects distractor rarity, not only attentional suppression

In visual search tasks, salient distractors may capture attention involuntarily, but interference can be reduced when the salient distractor appears more frequently on one out of several possible positions. The reduction was attributed to attentional suppression of the high-probability position. However, all previous studies on this topic compared performance on the high-probability position to the remaining positions, which had a low probability of containing the distractor. Therefore, it is not clear whether the difference resulted from reduced interference on the high-probability position or from increased interference on the low-probability positions. To decide between these alternatives, we compared high-probability and low-probability with equal-probability positions. Consistent with attentional suppression, interference was reduced on the high-probability position compared with equal-probability positions. However, there was also an increase in interference on low-probability positions compared with equal-probability positions. The increase is in line with previous reports of boosted interference when distractors are rare. Our results show that the experimental design used in previous research is insufficient to separate effects of attentional suppression and those of distractor rarity.

Is Statistical Learning of a Salient Distractor's Color Implicit, Inflexible and Distinct From Inter-Trial Priming?

Being able to overcome distraction by salient distractors is critical in order to allocate our attention efficiently. Previous research showed that observers can learn to ignore salient distractors endowed with some regularity, such as a high-probability location or feature - a phenomenon known as distractor statistical learning. Unlike goal-directed attentional guidance, the bias induced by statistical learning is thought to be implicit, long-lasting and inflexible. We tested these claims with regard to statistical learning of distractor color in a high-power (N = 160) pre-registered experiment. Participants searched for a known-shape singleton target and a color singleton distractor, when present, appeared most often in one color during the learning phase, but equally often in all possible colors during the extinction phase. We used a sensitive measure of participants' awareness of the probability manipulation. The awareness test was administered after the extinction phase for one group, and after the leaning phase for another group - which was informed that the probability imbalance would be discontinued in the upcoming extinction phase. Participants learned to suppress the high-probability distractor color very fast, an effect partly due to intertrial priming. Crucially, there was only little evidence that the bias survived during extinction. Awareness of the manipulation was associated with reduced color suppression, suggesting that the bias was implicit. Finally, results showed that the awareness test was more sensitive when administered early vs. late. We conclude that learnt color suppression is an implicit bias that emerges and decays rapidly, and discuss the methodological implications of our findings.

Spatial suppression due to statistical regularities in a visual detection task

Increasing evidence demonstrates that observers can learn the likely location of salient singleton distractors during visual search. To date, the reduced attentional capture at high-probability distractor locations has typically been examined using so called compound search, in which by design a target is always present. Here, we explored whether statistical distractor learning can also be observed in a visual detection task, in which participants respond target present if the singleton target is present and respond target absent when the singleton target is absent. If so, this allows us to examine suppression of the location that is likely to contain a distractor both in the presence, but critically also in the absence, of a priority signal generated by the target singleton. In an online variant of the additional singleton paradigm, observers had to indicate whether a unique shape was present or absent, while ignoring a colored singleton, which appeared with a higher probability in one specific location. We show that attentional capture was reduced, but not absent, at high-probability distractor locations, irrespective of whether the display contained a target or not. By contrast, target processing at the high-probability distractor location was selectively impaired on distractor-present displays. Moreover, all suppressive effects were characterized by a gradient such that suppression scaled with the distance to the high-probability distractor location. We conclude that statistical distractor learning can be examined in visual detection tasks, and discuss the implications for attentional suppression due to statistical learning.

Statistical Learning of Frequent Distractor Locations in Visual Search Involves Regional Signal Suppression in Early Visual Cortex

Observers can learn locations where salient distractors appear frequently to reduce potential interference-an effect attributed to better suppression of distractors at frequent locations. But how distractor suppression is implemented in the visual cortex and within the frontoparietal attention networks remains unclear. We used fMRI and a regional distractor-location learning paradigm with two types of distractors defined in either the same (orientation) or a different (color) dimension to the target to investigate this issue. fMRI results showed that BOLD signals in early visual cortex were significantly reduced for distractors (as well as targets) occurring at the frequent versus rare locations, mirroring behavioral patterns. This reduction was more robust with same-dimension distractors. Crucially, behavioral interference was correlated with distractor-evoked visual activity only for same- (but not different-) dimension distractors. Moreover, with different- (but not same-) dimension distractors, a color-processing area within the fusiform gyrus was activated more when a distractor was present in the rare region versus being absent and more with a distractor in the rare versus frequent locations. These results support statistical learning of frequent distractor locations involving regional suppression in early visual cortex and point to differential neural mechanisms of distractor handling with different- versus same-dimension distractors.

Statistical distractor learning modulates perceptual sensitivity

The present study used perceptual sensitivity (d′) to determine the spatial distribution of attention in displays in which participants have learned to suppress a location that is most likely to contain a distractor. Participants had to indicate whether a horizontal or a vertical line, which was shown only briefly before it was masked, was present within a target shape. Critically, the target shape could be accompanied by a singleton distractor color, which when present appeared with a high probability at one display location. The results show that perceptual sensitivity was reduced for locations likely to contain a distractor, as d′ was lower for this location than for all other locations in the display. We also found that the presence of an irrelevant color singleton reduced the gain for input at the target location, particularly when the irrelevant singleton was close to the target singleton. We conclude that, through the repeated encounter with a distractor at a particular location, the weights within the attentional priority map are changed such that the perceptual sensitivity for objects presented at that location is reduced relative to all other locations. This reduction of perceptual sensitivity signifies that this location competes less for attention than all other locations.

Statistical learning of target selection and distractor suppression shape attentional priority according to different timeframes

Recent findings suggest that attentional and oculomotor control is heavily affected by past experience, giving rise to selection and suppression history effects, so that target selection is facilitated if they appear at frequently attended locations, and distractor filtering is facilitated at frequently ignored locations. While selection history effects once instantiated seem to be long-lasting, whether suppression history is similarly durable is still debated. We assessed the permanence of these effects in a unique experimental setting investigating eye-movements, where the locations associated with statistical unbalances were exclusively linked with either target selection or distractor suppression. Experiment 1 and 2 explored the survival of suppression history in the long and in the short term, respectively, revealing that its lingering traces are relatively short lived. Experiment 3 showed that in the very same experimental context, selection history effects were long lasting. These results seem to suggest that different mechanisms support the learning-induced plasticity triggered by selection and suppression history. Specifically, while selection history may depend on lasting changes within stored representations of the visual space, suppression history effects hinge instead on a functional plasticity which is transient in nature, and involves spatial representations which are constantly updated and adaptively sustain ongoing oculomotor control.

Acquisition and Use of 'Priors' in Autism: Typical in Deciding Where to Look, Atypical in Deciding What Is There

Individuals with Autism Spectrum Disorder (ASD) are thought to under-rely on prior knowledge in perceptual decision-making. This study examined whether this applies to decisions of attention allocation, of relevance for ‘predictive-coding’ accounts of ASD. In a visual search task, a salient but task-irrelevant distractor appeared with higher probability in one display half. Individuals with ASD learned to avoid ‘attentional capture’ by distractors in the probable region as effectively as control participants—indicating typical priors for deploying attention. However, capture by a ‘surprising’ distractor at an unlikely location led to greatly slowed identification of a subsequent target at that location—indicating that individuals with ASD attempt to control surprise (unexpected attentional capture) by over-regulating parameters in post-selective decision-making.

Post-capture processes contribute to statistical learning of distractor locations in visual search

People can learn to ignore salient distractors that occur frequently at particular locations, making them interfere less with task performance. This effect has been attributed to learnt suppression of the likely distractor locations at a pre-selective stage of attentional-priority computation. However, rather than distractors at frequent (vs rare) locations being just less likely to capture attention, attention may possibly also be disengaged faster from such distractors - a post-selective contribution to their reduced interference. Eye-movement studies confirm that learnt suppression, evidenced by a reduced rate of oculomotor capture by distractors at frequent locations, is a major factor, whereas the evidence is mixed with regard to a role of rapid disengagement However, methodological choices in these studies limited conclusions as to the contribution of a post-capture effect. Using an adjusted design, here we positively establish the rapid-disengagement effect, while corroborating the oculomotor-capture effect. Moreover, we examine distractor-location learning effects not only for distractors defined in a different visual dimension to the search target, but also for distractors defined within the same dimension, which are known to cause particularly strong interference and probability-cueing effects. Here, we show that both oculomotor-capture and disengagement dynamics contribute to this pattern. Additionally, on distractor-absent trials, the slowed responses to targets at frequent distractor locations-that we observe only in same-, but not different-, dimension conditions-arise pre-selectively, in prolonged latencies of the very first saccade. This supports the idea that learnt suppression is implemented at a different level of priority computation with same-versus different-dimension distractors.

Modulating the influence of recent trial history on attentional capture via transcranial magnetic stimulation (TMS) of right TPJ

In visual search, salient yet task-irrelevant distractors in the stimulus array interfere with target selection. This is due to the unwanted shift of attention towards the salient stimulus-the so-called attentional capture effect, which delays deployment of attention onto the target. Although powerful and automatic, attentional capture by a salient distractor is nonetheless antagonized by distractor-filtering mechanisms and is further modulated by cross-trial contingencies: The distractor cost is typically more robust when no distraction has been experienced in the immediate past, compared to when a distractor was present on the immediately preceding trial. Here, we used transcranial magnetic stimulation (TMS) to shed light on the causal role of two crucial nodes of the ventral attention network, namely the Temporo-Parietal Junction (TPJ) and the Middle Frontal Gyrus (MFG), in the exogenous control of attention (i.e., attentional capture) and its history-dependent modulation. Participants were asked to discriminate the direction of a target arrow while ignoring a task-irrelevant salient distractor, when present. Immediately after display onset, 10 Hz triple-pulse TMS was delivered either to TPJ or MFG on the right hemisphere. Results demonstrated that stimulation of right TPJ-but not of right MFG, strongly modulated attentional capture as a function of the type of previous trial, by somewhat enhancing the distractor-related cost when the preceding trial was a distractor-absent trial and significantly decreasing the cost when the preceding trial was a distractor-present trial. These findings indicate that TMS of right TPJ exacerbates the effect of the recent history, likely reflecting enhanced updating of the predictive model that dynamically governs proactive distractor-filtering mechanisms. More generally, the results attest to a role of TPJ in mediating the history-dependent modulation of attentional capture.