Neural mechanisms underlying expectation-dependent inhibition of distracting information

Distractor inhibition by alpha oscillations is controlled by an indirect mechanism governed by goal-relevant information

The role of alpha oscillations (8-13 Hz) in cognition is intensively investigated. While intracranial animal recordings demonstrate that alpha oscillations are associated with decreased neuronal excitability, it is been questioned whether alpha oscillations are under direct control from frontoparietal areas to suppress visual distractors. We here point to a revised mechanism in which alpha oscillations are controlled by an indirect mechanism governed by the load of goal-relevant information - a view compatible with perceptual load theory. We will outline how this framework can be further tested and discuss the consequences for network dynamics and resource allocation in the working brain.

The Reactivation of working memory representations affects attentional guidance

Recent studies have suggested that the neural activity that supported working memory (WM) storage is dynamic over time and this dynamic storage decides memory performance. Does the temporal dynamic of the WM representation also affect visual search, and how does it interact with distractor suppression over time? To address these issues, we tracked the time course of the reactivation of WM representations during visual search by analyzing the electroencephalogram (EEG) and event-related optical signals (EROS) in Experiments 1 and 2, respectively, and investigated the interaction between the representation reactivation and distractor suppression in Experiment 3. Participants had to maintain a color in WM under high- or low-precision requirement and perform a subsequent search task. The reactivation of WM representations was defined by the above-chance decoding accuracy. The EEG results showed that compared with the low-precision requirement, WM-matching distractors captured more attention and the WM representation were reactivated more frequently under high-precision requirement. The EROS results showed that compared with the low-precision requirement, the increased activity in occipital cortex in the WM-matching versus WM-mismatching conditions was observed at 224 ms during visual search under high-precision requirement. Regression analysis showed that the representation reactivation during visual search directly predicted the behavioral WM-based attentional capture effect, while the representation reactivation before visual search impacted the WM-based attentional capture effect through the mediation of distractor suppression during visual search. These results suggest that the reactivation of WM representations and distractor suppression collectively determine WM-based attentional capture.

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.

The Electrophysiological Markers of Statistically Learned Attentional Enhancement: Evidence for a Saliency-based Mechanism

It is well established that attention can be sharpened through the process of statistical learning (e.g., visual search becomes faster when targets appear at high-relative-to-low probability locations). Although this process of statistically learned attentional enhancement differs behaviorally from the well-studied top-down and bottom-up forms of attention, relatively little work has been done to characterize the electrophysiological correlates of statistically learned attentional enhancement. It thus remains unclear whether statistically learned enhancement recruits any of the same cognitive mechanisms as top-down or bottom-up attention. In the current study, EEG data were collected while participants searched for an ambiguous unique shape in a visual array (the additional singleton task). Unbeknownst to the participants, targets appeared more frequently in one location in space (probability cuing). Encephalographic data were then analyzed in two phases: an anticipatory phase and a reactive phase. In the anticipatory phase preceding search stimuli onset, alpha lateralization as well as the Anterior Directing Attention Negativity and Late Directing Attention Positivity components-signs of preparatory attention known to characterize top-down enhancement-were tested. In the reactive phase, the N2pc component-a well-studied marker of target processing-was examined following stimuli onset. Our results showed that statistically learned attentional enhancement is not characterized by any of the well-known anticipatory markers of top-down attention; yet targets at high probability locations did reliably evoke larger N2pc amplitudes, a finding that is associated with bottom-up attention and saliency. Overall, our findings are consistent with the notion that statistically learned attentional enhancement increases the perceptual salience of items appearing at high-probability locations relative to low-probability locations.

The Distractor Positivity Component and the Inhibition of Distracting Stimuli

There has been a long-lasting debate about whether salient stimuli, such as uniquely colored objects, have the ability to automatically distract us. To resolve this debate, it has been suggested that salient stimuli do attract attention but that they can be suppressed to prevent distraction. Some research supporting this viewpoint has focused on a newly discovered ERP component called the distractor positivity (PD), which is thought to measure an inhibitory attentional process. This collaborative review summarizes previous research relying on this component with a specific emphasis on how the PD has been used to understand the ability to ignore distracting stimuli. In particular, we outline how the PD component has been used to gain theoretical insights about how search strategy and learning can influence distraction. We also review alternative accounts of the cognitive processes indexed by the PD component. Ultimately, we conclude that the PD component is a useful tool for understanding inhibitory processes related to distraction and may prove to be useful in other areas of study related to cognitive control.

Long-term (statistically learnt) and short-term (inter-trial) distractor-location effects arise at different pre- and post-selective processing stages

A salient distractor interferes less with visual search if it appears at a location where it is likely to occur, referred to as distractor-location probability cueing. Conversely, if the current target appears at the same location as a distractor on the preceding trial, search is impeded. While these two location-specific "suppression" effects reflect long-term, statistically learnt and short-term, inter-trial adaptations of the system to distractors, it is unclear at what stage(s) of processing they arise. Here, we adopted the additional-singleton paradigm and examined lateralized event-related potentials (L-ERPs) and lateralized alpha (8-12 Hz) power to track the temporal dynamics of these effects. Behaviorally, we confirmed both effects: reaction times (RTs) interference was reduced for distractors at frequent versus rare (distractor) locations, and RTs were delayed for targets that appeared at previous distractor versus non-distractor locations. Electrophysiologically, the statistical-learning effect was not associated with lateralized alpha power during the pre-stimulus period. Rather, it was seen in an early N1pc referenced to the frequent distractor location (whether or not a distractor or a target occurred there), indicative of a learnt top-down prioritization of this location. This early top-down influence was systematically modulated by (competing) target- and distractor-generated bottom-up saliency signals in the display. In contrast, the inter-trial effect was reflected in an enhanced SPCN when the target was preceded by a distractor at its location. This suggests that establishing that an attentionally selected item is a task-relevant target, rather than an irrelevant distractor, is more demanding at a previously "rejected" distractor location.

Fluctuations in alpha and beta power provide neural states favourable for contextually relevant anticipatory processes

Cued sensory input occasionally fails to immediately ensue its respective trigger. Given that our environments are rich in sensory cues, we often end up processing other contextually relevant information in the meantime. The experimental design of the present study allowed us to investigate how such temporal delays and visual interferences may impact anticipatory processes. Thirty-four participants were trained to remember an individualised set of eight paired-up faces. These paired-up faces were presented pseudorandomly in sequences of unpaired face images. To keep participants engaged throughout the electroencephalography study, they were instructed to classify each face image, according to its sex, as fast as possible without compromising accuracy. We observed dissimilar modulations in alpha and beta power between the 6-s timeframe encompassing the onsets of predictive and expected images (temporal delay block) and the 6-s timeframe encompassing the predictive, interference and expected images (visual interference block). Furthermore, an expectation-facilitated reduction of the face-sensitive N170 component was only observed if an anticipated face image directly followed its corresponding predictive counterpart. This effect was no longer evident when the expected face was preceded by a distracting face image. Regardless of the block type, behavioural measures confirmed that anticipated faces were classified significantly faster and with fewer erroneous responses than faces not foretold by a predictive face. Collectively, these results demonstrate that whilst the brain continuously adjusts internal hierarchical generative models to account for temporal delays in stimulus onset and visual interferences, the higher levels, and subsequent predictions, fundamental for expectation-facilitated behaviours remain intact.

Alpha oscillations protect working memory against distracters in a modality-specific way

Alpha oscillations are thought to be involved in suppressing distracting input in working-memory tasks. Yet, the spatial-temporal dynamics of such suppression remain unclear. Key questions are whether such suppression reflects a domain-general inattentiveness mechanism, or occurs in a stimulus- or modality-specific manner within cortical areas most responsive to the distracters; and whether the suppression is proactive (i.e., preparatory) or reactive. Here, we addressed these questions using a working-memory task where participants had to memorize an array of visually presented digits and reproduce one of them upon being probed. We manipulated the presence of distracters and the sensory modality in which distracters were presented during memory maintenance. Our results show that sensory areas most responsive to visual and auditory distracters exhibited stronger alpha power increase after visual and auditory distracter presentation respectively. These results suggest that alpha oscillations underlie distracter suppression in a reactive, modality-specific manner.

Prior Knowledge Uses Prestimulus Alpha Band Oscillations and Persistent Poststimulus Neural Templates for Conscious Perception

Prior knowledge has a profound impact on the way we perceive the world. However, it remains unclear how the prior knowledge is maintained in our brains and thereby influences the subsequent conscious perception. The Dalmatian dog illusion is a perfect tool to study prior knowledge, where the picture is initially perceived as noise. Once the prior knowledge was introduced, a Dalmatian dog could be consciously seen, and the picture immediately became meaningful. Using pictures with hidden objects as standard stimuli and similar pictures without hidden objects as deviant stimuli, we investigated the neural representation of prior knowledge and its impact on conscious perception in an oddball paradigm using electroencephalogram (EEG) in both male and female human subjects. We found that the neural patterns between the prestimulus alpha band oscillations and poststimulus EEG activity were significantly more similar for the standard stimuli than for the deviant stimuli after prior knowledge was provided. Furthermore, decoding analysis revealed that persistent neural templates were evoked after the introduction of prior knowledge, similar to that evoked in the early stages of visual processing. In conclusion, the current study suggests that prior knowledge uses alpha band oscillations in a multivariate manner in the prestimulus period and induces specific persistent neural templates in the poststimulus period, enabling the conscious perception of the hidden objects.SIGNIFICANCE STATEMENT The visual world we live in is not always optimal. In dark or noisy environments, prior knowledge can help us interpret imperfect sensory signals and enable us to consciously perceive hidden objects. However, we still know very little about how prior knowledge works at the neural level. Using the Dalmatian dog illusion and multivariate methods, we found that prior knowledge uses prestimulus alpha band oscillations to carry information about the hidden object and exerts a persistent influence in the poststimulus period by inducing specific neural templates. Our findings provide a window into the neural underpinnings of prior knowledge and offer new insights into the role of alpha band oscillations and neural templates associated with conscious perception.

Pinging the brain to reveal the hidden attentional priority map using encephalography

Attention has been usefully thought of as organized in priority maps - putative maps of space where attentional priority is weighted across spatial regions in a winner-take-all competition for attentional deployment. Recent work has highlighted the influence of past experiences on the weighting of spatial priority - called selection history. Aside from being distinct from more well-studied, top-down forms of attentional enhancement, little is known about the neural substrates of history-mediated attentional priority. Using a task known to induce statistical learning of target distributions, in an EEG study we demonstrate that this otherwise invisible, latent attentional priority map can be visualized during the intertrial period using a 'pinging' technique in conjunction with multivariate pattern analyses. Our findings not only offer a method of visualizing the history-mediated attentional priority map, but also shed light on the underlying mechanisms allowing our past experiences to influence future behavior.

Causal investigation of mid-frontal theta activity in memory guided visual search

Midfrontal theta activity is crucial for attentional and cognitive control. However, its causal role in facilitating visual search, particularly from the perspective of distractor inhibition, is yet to be discovered. We applied theta band transcranial alternate current stimulation (tACS) over frontocentral regions when participants searched for targets among heterogeneous distractors with foreknowledge of distractor features. The results demonstrated improved visual search performance in the theta stimulation group compared to the active sham group. Moreover, we observed the facilitation effect of the distractor cue only in participants who exhibited larger inhibition benefits, which further confirms the role of theta stimulation in precise attentional control. Taken together, our results provide compelling causal evidence for the involvement of midfrontal theta activity in memory-guided visual search.

Slow neural oscillations explain temporal fluctuations in distractibility

Human environments comprise various sources of distraction, which often occur unexpectedly in time. The proneness to distraction (i.e., distractibility) is posited to be independent of attentional sampling of targets, but its temporal dynamics and neurobiological basis are largely unknown. Brain oscillations in the theta band (3 - 8Hz) have been associated with fluctuating neural excitability, which is hypothesised here to explain rhythmic modulation of distractibility. In a pitch discrimination task (N = 30) with unexpected auditory distractors, we show that distractor-evoked neural responses in the electroencephalogram and perceptual susceptibility to distraction were co-modulated and cycled approximately 3 - 5 times per second. Pre-distractor neural phase in left inferior frontal and insular cortex regions explained fluctuating distractibility. Thus, human distractibility is not constant but fluctuates on a subsecond timescale. Furthermore, slow neural oscillations subserve the behavioural consequences of a hitherto largely unexplained but ever-increasing phenomenon in modern environments - distraction by unexpected sound.

Attentional suppression is in place before display onset

Recent studies have shown that observers can learn to suppress a location that is most likely to contain a distractor. The current study investigates whether the statistically learned suppression is already in place, before, or implemented exactly at the moment participants expect the display to appear. Participants performed a visual search task in which a distractor was presented more frequently at the high-probability location (HPL) in a search display. Occasionally, the search display was replaced by a probe display in which participants needed to detect a probe offset. The temporal relationship between the probe display and the search display was manipulated by varying the stimulus onset asynchronies (SOAs) in the probe task. In this way, the attentional distribution in space was probed before, exactly at, or after the moment when the search display was expected to be presented. The results showed a statistically learned suppression at the HPL, as evidenced by faster and more accurate search when a distractor was presented at this location. Crucially, irrespective of the SOA, probe detection was always slower at the HPL than at the low-probability locations, indicating that the spatial suppression induced by statistical learning is proactively implemented not just at the moment the display is expected, but prior to display onset. We conclude that statistical learning affects the weights within the priority map relatively early in time, well before the availability of the search display.

Differential modulation of visual responses by distractor or target expectations

Discriminating relevant from irrelevant information in a busy visual scene is supported by statistical regularities in the environment. However, it is unclear to what extent immediate stimulus repetitions and higher order expectations (whether a repetition is statistically probable or not) are supported by the same neural mechanisms. Moreover, it is also unclear whether target and distractor-related processing are mediated by the same or different underlying neural mechanisms. Using a speeded target discrimination task, the present study implicitly cued subjects to the location of the target or the distractor via manipulations in the underlying stimulus predictability. In separate studies, we collected EEG and MEG alongside behavioural data. Results showed that reaction times were reduced with increased expectations for both types of stimuli and that these effects were driven by expected repetitions in both cases. Despite the similar behavioural pattern across target and distractors, neurophysiological measures distinguished the two stimuli. Specifically, the amplitude of the P1 was modulated by stimulus relevance, being reduced for repeated distractors and increased for repeated targets. The P1 was not, however, modulated by higher order stimulus expectations. These expectations were instead reflected in modulations in ERP amplitude and theta power in frontocentral electrodes. Finally, we observed that a single repetition of a distractor was sufficient to reduce decodability of stimulus spatial location and was also accompanied by diminished representation of stimulus features. Our results highlight the unique mechanisms involved in distractor expectation and suppression and underline the importance of studying these processes distinctly from target-related attentional control.

Hierarchy of Intra- and Cross-modal Redundancy Gains in Visuo-tactile Search: Evidence from the Posterior Contralateral Negativity

Redundant combination of target features from separable dimensions can expedite visual search. The dimension-weighting account explains these "redundancy gains" by assuming that the attention-guiding priority map integrates the feature-contrast signals generated by targets within the respective dimensions. The present study investigated whether this hierarchical architecture is sufficient to explain the gains accruing from redundant targets defined by features in different modalities, or whether an additional level of modality-specific priority coding is necessary, as postulated by the modality-weighting account (MWA). To address this, we had observers perform a visuo-tactile search task in which targets popped out by a visual feature (color or shape) or a tactile feature (vibro-tactile frequency) as well as any combination of these features. The RT gains turned out larger for visuo-tactile versus visual redundant targets, as predicted by the MWA. In addition, we analyzed two lateralized event-related EEG components: the posterior (PCN) and central (CCN) contralateral negativities, which are associated with visual and tactile attentional selection, respectively. The CCN proved to be a stable somatosensory component, unaffected by cross-modal redundancies. In contrast, the PCN was sensitive to cross-modal redundancies, evidenced by earlier onsets and higher amplitudes, which could not be explained by linear superposition of the earlier CCN onto the later PCN. Moreover, linear mixed-effect modeling of the PCN amplitude and timing parameters accounted for approximately 25% of the behavioral RT variance. Together, these behavioral and PCN effects support the hierarchy of priority-signal computation assumed by the MWA.

Statistical Learning of Distractor Suppression Downregulates Prestimulus Neural Excitability in Early Visual Cortex

Visual attention is highly influenced by past experiences. Recent behavioral research has shown that expectations about the spatial location of distractors within a search array are implicitly learned, with expected distractors becoming less interfering. Little is known about the neural mechanism supporting this form of statistical learning. Here, we used magnetoencephalography (MEG) to measure human brain activity to test whether proactive mechanisms are involved in the statistical learning of distractor locations. Specifically, we used a new technique called rapid invisible frequency tagging (RIFT) to assess neural excitability in early visual cortex during statistical learning of distractor suppression while concurrently investigating the modulation of posterior alpha band activity (8-12 Hz). Male and female human participants performed a visual search task in which a target was occasionally presented alongside a color-singleton distractor. Unbeknown to the participants, the distracting stimuli were presented with different probabilities across the two hemifields. RIFT analysis showed that early visual cortex exhibited reduced neural excitability in the prestimulus interval at retinotopic locations associated with higher distractor probabilities. In contrast, we did not find any evidence of expectation-driven distractor suppression in alpha band activity. These findings indicate that proactive mechanisms of attention are involved in predictive distractor suppression and that these mechanisms are associated with altered neural excitability in early visual cortex. Moreover, our findings indicate that RIFT and alpha band activity might subtend different and possibly independent attentional mechanisms.SIGNIFICANCE STATEMENT What we experienced in the past affects how we perceive the external world in the future. For example, an annoying flashing light might be better ignored if we know in advance where it usually appears. This ability of extracting regularities from the environment is called statistical learning. In this study, we explore the neuronal mechanisms allowing the attentional system to overlook items that are unequivocally distracting based on their spatial distribution. By recording brain activity using MEG while probing neural excitability with a novel technique called RIFT, we show that the neuronal excitability in early visual cortex is reduced in advance of stimulus presentation for locations where distracting items are more likely to occur.

Suppression of distracting inputs by visual-spatial cues is driven by anticipatory alpha activity

A growing body of research demonstrates that distracting inputs can be proactively suppressed via spatial cues, nonspatial cues, or experience, which are governed by more than one top-down mechanism of attention. However, how the neural mechanisms underlying spatial distractor cues guide proactive suppression of distracting inputs remains unresolved. Here, we recorded electroencephalography signals from 110 participants in 3 experiments to identify the role of alpha activity in proactive distractor suppression induced by spatial cues and its influence on subsequent distractor inhibition. Behaviorally, we found novel changes in the spatial proximity of the distractor: Cueing distractors far away from the target improves search performance for the target, while cueing distractors close to the target hampers performance. Crucially, we found dynamic characteristics of spatial representation for distractor suppression during anticipation. This result was further verified by alpha power increased relatively contralateral to the cued distractor. At both the between- and within-subjects levels, we found that these activities further predicted the decrement of the subsequent PD component, which was indicative of reduced distractor interference. Moreover, anticipatory alpha activity and its link with the subsequent PD component were specific to the high predictive validity of distractor cue. Together, our results reveal the underlying neural mechanisms by which cueing the spatial distractor may contribute to reduced distractor interference. These results also provide evidence supporting the role of alpha activity as gating by proactive suppression.

General deficits of attentional inhibition in high trait anxiety: ERP evidence

Behavioral evidence shows that individuals with high trait anxiety tend to be distracted by irrelevant stimulation not only for threat-related stimuli but also for non-emotional neutral stimuli. These findings suggest that there may be a general deficit of attentional control in trait anxiety. However, the neural mechanism underlying the anxiety-related deficit in attentional control, especially inhibition function, is still unclear. Here, we examined the attentional processing of the non-emotional neutral distractor on 66 young adults with different levels of trait anxiety, using the ERP indices of attentional selection (N2pc) and top-down inhibition (Pd) in a search task with geometric stimuli. We found that the distractor-evoked N2pc amplitude did not vary with anxiety levels, but increased anxiety was associated with smaller Pds (i.e. worse inhibition). Besides, delayed attentional selection of targets was associated with higher anxiety levels. These correlations of trait anxiety remained significant even after controlling for state anxiety, and state anxiety did not affect the attentional processing of distractors and targets, suggesting that trait anxiety, not current anxiety, affects attentional function. Our findings clarify the mechanism underlying the general attentional deficits in trait anxiety, e.g. reduced distractor inhibition and delayed target selection.

Target templates and the time course of distractor location learning

When searching for a shape target, colour distractors typically capture our attention. Capture is smaller when observers search for a fixed target that allows for a feature-specific target template compared to a varying shape singleton target. Capture is also reduced when observers learn to predict the likely distractor location. We investigated how the precision of the target template modulates distractor location learning in an additional singleton search task. As observers are less prone to capture with a feature-specific target, we assumed that distractor location learning is less beneficial and therefore less pronounced than with a mixed-feature target. Hierarchical Bayesian parameter estimation was used to fit fine-grained distractor location learning curves. A model-based analysis of the time course of distractor location learning revealed an effect on the asymptotic performance level: when searching for a fixed-feature target, the asymptotic distractor cost indicated smaller distractor interference than with a mixed-feature target. Although interference was reduced for distractors at the high-probability location in both tasks, asymptotic distractor suppression was less pronounced with fixed-feature compared to mixed-feature targets. We conclude that with a more precise target template less distractor location learning is required, likely because the distractor dimension is down-weighted and its salience signal reduced.

Attentional capture is modulated by stimulus saliency in visual search as evidenced by event-related potentials and alpha oscillations

This study used a typical four-item search display to investigate top-down control over attentional capture in an additional singleton paradigm. By manipulating target and distractor color and shape, stimulus saliency relative to the remaining items was systematically varied. One group of participants discriminated the side of a dot within a salient orange target (ST group) presented with green circles (fillers) and a green diamond distractor. A second group discriminated the side of the dot within a green diamond target presented with green circle fillers and a salient orange square distractor (SD group). Results showed faster reaction times and a shorter latency of the N2pc component in the event-related potential (ERP) to the more salient targets in the ST group. Both salient and less salient distractors elicited Pd components of equal amplitude. Behaviorally, no task interference was observed with the less salient distractor, indicating the prevention of attentional capture. However, reaction times were slower in the presence of the salient distractor, which conflicts with the hypothesis that the Pd reflects proactive distractor suppression. Contrary to recent proposals that elicitation of the Pd requires competitive interactions with a target, we found a greater Pd amplitude when the distractor was presented alone. Alpha-band amplitudes decreased during target processing (event-related desynchronization), but no significant amplitude enhancement was observed at electrodes contralateral to distractors regardless of their saliency. The results demonstrate independent neural mechanisms for target and distractor processing and support the view that top-down guidance of attention can be offset (counteracted) by relative stimulus saliency.

Aging and distractor resistance in working memory: Does emotional valence matter?

Background

Emotional stimuli used as targets of working memory (WM) tasks can moderate age-related differences in WM performance, showing that aging is associated with reductions in negativity bias. This phenomenon is referred to as the positivity effect. However, there is little research on whether emotional distractors have a similar moderating effect. Moreover, the underlying neural mechanism of this effect has not been studied. In this study, we examined the behavioral and neurophysiological basis for age differences in resistance to emotional distractors within WM.

Methods

Older adults (n = 30, ages 60–74) and young adults (n = 35, ages 19–26) performed a 2-back task in which a digit was superimposed on a face with a happy, angry, or neutral expression as a distractor. Event-related potential (ERP) was simultaneously recorded to assess P2, N2, and later positive potential (LPP) amplitudes.

Results

Older adults were less accurate and slower than young adults on the WM task. Moreover, the results demonstrated a significant interaction between age and emotional valence on response accuracy, young adults' performance was worse when the distractor was neutral or positive than when it was negative, but there was no effect of the emotional valence of distractors on older adults’ WM performance. ERP analyses revealed greater P2 amplitude in older adults than young adults, regardless of the emotional valence of distractors. However, older adults and young adults did not differ on N2 or LPP amplitude, and negative distractors elicited greater N2 than positive distractors in both age groups.

Conclusions

The behavioral findings provided evidence of age-related reductions in negativity bias. Thus, the behavioral measures indicated a positivity effect in WM. However, the ERP results did not show this same interaction. These discrepant results raise questions about whether and to what extent older and young adults differ in controlling the effect of emotional distractors in WM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40359-022-00953-y.

Selection history and task predictability determine the precision expectations in attentional control

Predictive processing frameworks have demonstrated the central role that prediction plays in a range of cognitive processes including bottom-up and top-down mechanisms of attention control. However, relatively little is understood about how predictive processes interact with the third main determinant of attentional priority - selection history. In this experiment, participants developed a history of either color or shape selection while we observed the impact of these histories in an additional singleton search task using behavioral measures and ERP measures of attentional control. Throughout the experiment, participants were encouraged to predict the upcoming display, but prediction errors were either high or low depending on session. Persistent group differences in our results showed that selection history contributes to the precision weighting of a stimulus, and that this is mediated by overall prediction error. Color-singleton distractors captured attention and required greater suppression when participants had a history of color selection; however, these participants gained large benefits when the upcoming stimuli were highly predictable. We suggest that selection history modulates the precision expectations for a feature in a persistent and implicit way, producing an attentional bias that predictability can help to counteract, but cannot prevent or eliminate entirely.

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.

Ten simple rules to study distractor suppression

Distractor suppression refers to the ability to filter out distracting and task-irrelevant information. Distractor suppression is essential for survival and considered a key aspect of selective attention. Despite the recent and rapidly evolving literature on distractor suppression, we still know little about how the brain suppresses distracting information. What limits progress is that we lack mutually agreed upon principles of how to study the neural basis of distractor suppression and its manifestation in behavior. Here, we offer ten simple rules that we believe are fundamental when investigating distractor suppression. We provide guidelines on how to design conclusive experiments on distractor suppression (Rules 1-3), discuss different types of distractor suppression that need to be distinguished (Rules 4-6), and provide an overview of models of distractor suppression and considerations of how to evaluate distractor suppression statistically (Rules 7-10). Together, these rules provide a concise and comprehensive synopsis of promising advances in the field of distractor suppression. Following these rules will propel research on distractor suppression in important ways, not only by highlighting prominent issues to both new and more advanced researchers in the field, but also by facilitating communication between sub-disciplines.

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.

Ten simple rules to study distractor suppression

Distractor suppression refers to the ability to filter out distracting and task-irrelevant information. Distractor suppression is essential for survival and considered a key aspect of selective attention. Despite the recent and rapidly evolving literature on distractor suppression, we still know little about how the brain suppresses distracting information. What limits progress is that we lack mutually agreed upon principles of how to study the neural basis of distractor suppression and its manifestation in behavior. Here, we offer ten simple rules that we believe are fundamental when investigating distractor suppression. We provide guidelines on how to design conclusive experiments on distractor suppression (Rules 1–3), discuss different types of distractor suppression that need to be distinguished (Rules 4–6), and provide an overview of models of distractor suppression and considerations of how to evaluate distractor suppression statistically (Rules 7–10). Together, these rules provide a concise and comprehensive synopsis of promising advances in the field of distractor suppression. Following these rules will propel research on distractor suppression in important ways, not only by highlighting prominent issues to both new and more advanced researchers in the field, but also by facilitating communication between sub-disciplines.

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Distractor suppression is the ability to filter out irrelevant information.

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At present, we know little about how the brain suppresses distraction.

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We offer ten rules that are fundamental when investigating distractor suppression.

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Following the rules will propel research and foster interaction between disciplines.

Memory precision for salient distractors decreases with learned suppression

Attention operates as a cognitive gate that selects sensory information for entry into memory and awareness (Driver, 2001, British Journal of Psychology, 92, 53-78). Under many circumstances, the selected information is task-relevant and important to remember, but sometimes perceptually salient nontarget objects will capture attention and enter into awareness despite their irrelevance (Adams & Gaspelin, 2020, Attention, Perception, & Psychophysics, 82[4], 1586-1598). Recent studies have shown that repeated exposures with salient distractor will diminish their ability to capture attention, but the relationship between suppression and later cognitive processes such as memory and awareness remains unclear. If learned attentional suppression (indicated by reduced capture costs) occurs at the sensory level and prevents readout to other cognitive processes, one would expect memory and awareness to dimmish commensurate with improved suppression. Here, we test this hypothesis by measuring memory precision and awareness of salient nontargets over repeated exposures as capture costs decreased. Our results show that stronger learned suppression is accompanied by reductions in memory precision and confidence in having seen a color singleton at all, suggesting that such suppression operates at the sensory level to prevent further processing of the distractor object.

Electrophysiological Evidence for the Suppression of Highly Salient Distractors

There has been a longstanding debate as to whether salient stimuli have the power to involuntarily capture attention. As a potential resolution to this debate, the signal suppression hypothesis proposes that salient items generate a bottom-up signal that automatically attracts attention, but that salient items can be suppressed by top-down mechanisms to prevent attentional capture. Despite much support, the signal suppression hypothesis has been challenged on the grounds that many prior studies may have used color singletons with relatively low salience that are too weak to capture attention. The current study addressed this by using previous methods to study suppression but increased the set size to improve the relative salience of the color singletons. To assess whether salient distractors captured attention, electrophysiological markers of attentional allocation (the N2pc component) and suppression (the PD component) were measured. The results provided no evidence of attentional capture, but instead indicated suppression of the highly salient singleton distractors, as indexed by the PD component. This suppression occurred even though a computational model of saliency confirmed that the color singleton was highly salient. Altogether, this supports the signal suppression hypothesis and is inconsistent with stimulus-driven models of attentional capture.

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.

Attention and distraction in the predictive brain

Whether it is possible to ignore a physically salient distractor has been a topic of active debate over the past 25 years, with empirical evidence for and against each of the theoretical stances. We put forward that predictive processing may provide a unified theoretical perspective that can account reasonably well for the empirical literature on attentional capture. In this perspective, capture is a logical consequence of the overall imperative of the brain to predict what sensory signals provide precise information to achieve goal-directed behaviour.

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.

Attention and distraction in the predictive brain

Whether it is possible to ignore a physically salient distractor has been a topic of active debate over the past 25 years, with empirical evidence for and against each of the theoretical stances. We put forward that predictive processing may provide a unified theoretical perspective that can account reasonably well for the empirical literature on attentional capture. In this perspective, capture is a logical consequence of the overall imperative of the brain to predict what sensory signals provide precise information to achieve goal-directed behaviour.

Strategic Distractor Suppression Improves Selective Control in Human Vision

Our visual environment is complicated, and our cognitive capacity is limited. As a result, we must strategically ignore some stimuli to prioritize others. Common sense suggests that foreknowledge of distractor characteristics, like location or color, might help us ignore these objects. But empirical studies have provided mixed evidence, often showing that knowing about a distractor before it appears counterintuitively leads to its attentional selection. What has looked like strategic distractor suppression in the past is now commonly explained as a product of prior experience and implicit statistical learning, and the long-standing notion the distractor suppression is reflected in α band oscillatory brain activity has been challenged by results appearing to link α to target resolution. Can we strategically, proactively suppress distractors? And, if so, does this involve α? Here, we use the concurrent recording of human EEG and eye movements in optimized experimental designs to identify behavior and brain activity associated with proactive distractor suppression. Results from three experiments show that knowing about distractors before they appear causes a reduction in electrophysiological indices of covert attentional selection of these objects and a reduction in the overt deployment of the eyes to the location of the objects. This control is established before the distractor appears and is predicted by the power of cue-elicited α activity over the visual cortex. Foreknowledge of distractor characteristics therefore leads to improved selective control, and α oscillations in visual cortex reflect the implementation of this strategic, proactive mechanism.SIGNIFICANCE STATEMENT To behave adaptively and achieve goals we often need to ignore visual distraction. Is it easier to ignore distracting objects when we know more about them? We recorded eye movements and electrical brain activity to determine whether foreknowledge of distractor characteristics can be used to limit processing of these objects. Results show that knowing the location or color of a distractor stops us from attentionally selecting it. A neural signature of this inhibition emerges in oscillatory alpha band brain activity, and when this signal is strong, selective processing of the distractor decreases. Knowing about the characteristics of task-irrelevant distractors therefore increases our ability to focus on task-relevant information, in this way gating information processing in the brain.

Neural mechanisms underlying distractor inhibition on the basis of feature and/or spatial expectations

A rapidly growing body of research indicates that inhibition of distracting information may not be under flexible, top-down control, but instead heavily relies on expectations derived from past experience about the likelihood of events. Yet, how expectations about distracting information influence distractor inhibition at the neural level remains unclear. To determine how expectations induced by distractor features and/or location regularities modulate distractor processing, we measured EEG while participants performed two variants of the additional singleton paradigm. Critically, in these different variants, target and distractor features either randomly swapped across trials, or were fixed, allowing for the development of distractor feature-based expectations. Moreover, the task was initially performed without any spatial regularity, after which a high probability distractor location was introduced. Our results show that both distractor feature- and location regularities contributed to distractor inhibition, as indicated by corresponding reductions in distractor costs during visual search and an earlier distractor-evoked Pd component. Yet, control analyses showed that while observers were sensitive to regularities across longer time scales, the observed effects to a large extent reflected intertrial repetition. Large individual differences further suggest a functional dissociation between early and late Pd components, with the former reflecting early sensory suppression related to intertrial priming and the latter reflecting suppression sensitive to expectations derived over a longer time scale. Also, counter to some previous findings, no increase in anticipatory alpha-band activity was observed over visual regions representing the expected distractor location, although this effect should be interpreted with caution as the effect of spatial statistical learning was also less pronounced than in other studies. Together, these findings suggest that intertrial priming and statistical learning may both contribute to distractor suppression and reveal the underlying neural mechanisms.