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

Spatial transfer of object-based statistical learning

A large number of recent studies have demonstrated that efficient attentional selection depends to a large extent on the ability to extract regularities present in the environment. Through statistical learning, attentional selection is facilitated by directing attention to locations in space that were relevant in the past while suppressing locations that previously were distracting. The current study shows that we are not only able to learn to prioritize locations in space but also locations within objects independent of space. Participants learned that within a specific object, particular locations within the object were more likely to contain relevant information than other locations. The current results show that this learned prioritization was bound to the object as the learned bias to prioritize a specific location within the object stayed in place even when the object moved to a completely different location in space. We conclude that in addition to spatial attention prioritization of locations in space, it is also possible to learn to prioritize relevant locations within specific objects. The current findings have implications for the inferred spatial priority map of attentional weights as this map cannot be strictly retinotopically organized.

Task-irrelevant valence-preferred colors boost visual search for a singleton-shape target

Some studies have suggested that emotion-associated features might influence attentional capture. However, demonstrating valence-dependent distractor interference has proven challenging, possibly due to the neglect of individuals' color-valence preferences in standard, averaged reaction-time (RT) measures. To address this, we investigated valence-driven attentional-capture using an association phase in which emotionally neutral vs. positive-feedback photographs were paired with two alternative target colors, red vs. green. This was followed by a test phase requiring participants to search for a pop-out shape target in the presence or absence of an emotion-associated color. In Experiments 1 and 2, this color could only appear in a distractor, while in Experiment 3, it appeared in the target. Analyzing the standard, averaged RT measures, we found no significant valence association or valence-modulated attentional capture. However, correlational analyses revealed a positive relationship between individual participants' color-valence preference during the association phase and their valence-based effect during the test phase. Moreover, most individuals favored red over green in the association phase, leading to marked color-related asymmetries in the average measures. Crucially, the presence of the valence-preferred color anywhere in the test display facilitated RTs. This effect persisted even when the color appeared in one of the distractors (Experiments 1 and 2), at variance with this distractor capturing attention. These findings suggest that task-irrelevant valence-preferred color signals were registered pre-attentively and boosted performance, likely by raising the general (non-spatial) alertness level. However, these signals were likely kept out of attentional-priority computation to prevent inadvertent attentional capture.

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.

Separate and overlapping mechanisms of statistical regularities and salience processing in the occipital cortex and dorsal attention network

Attention selects behaviorally relevant inputs for in-depth processing. Beside the role of traditional signals related to goal-directed and stimulus-driven control, a debate exists regarding the mechanisms governing the effect of statistical regularities on attentional selection, and how these are integrated with other control signals. Using a visuo-spatial search task under fMRI, we tested the joint effects of statistical regularities and stimulus-driven salience. We found that both types of signals modulated occipital activity in a spatially specific manner. Salience acted primarily by reducing the attention bias towards the target location when associated with irrelevant distractors, while statistical regularities reduced this attention bias when the target was presented at a low probability location, particularly at the lower levels of the visual hierarchy. In addition, we found that both statistical regularities and salience activated the dorsal frontoparietal network. Additional exploratory analyses of functional connectivity revealed that only statistical regularities modulated the inter-regional coupling between the posterior parietal cortex and the occipital cortex. These results show that statistical regularities and salience signals are both spatially represented at the occipital level, but that their integration into attentional processing priorities relies on dissociable brain mechanisms.

Little engagement of attention by salient distractors defined in a different dimension or modality to the visual search target

Singleton distractors may inadvertently capture attention, interfering with the task at hand. The underlying neural mechanisms of how we prevent or handle distractor interference remain elusive. Here, we varied the type of salient distractor introduced in a visual search task: the distractor could be defined in the same (shape) dimension as the target, a different (color) dimension, or a different (tactile) modality (intra-dimensional, cross-dimensional, and, respectively, cross-modal distractor, all matched for physical salience); and besides behavioral interference, we measured lateralized electrophysiological indicators of attentional selectivity (the N2pc, Ppc, PD , CCN/CCP, CDA, and cCDA). The results revealed the intra-dimensional distractor to produce the strongest reaction-time interference, associated with the smallest target-elicited N2pc. In contrast, the cross-dimensional and cross-modal distractors did not engender any significant interference, and the target-elicited N2pc was comparable to the condition in which the search display contained only the target singleton, thus ruling out early attentional capture. Moreover, the cross-modal distractor elicited a significant early CCN/CCP, but did not influence the target-elicited N2pc, suggesting that the tactile distractor is registered by the somatosensory system (rather than being proactively suppressed), without, however, engaging attention. Together, our findings indicate that, in contrast to distractors defined in the same dimension as the target, distractors singled out in a different dimension or modality can be effectively prevented to engage attention, consistent with dimension- or modality-weighting accounts of attentional priority computation.

Habituation to visual onsets is affected by local and global distractors rate

Recent findings demonstrate that habituation of capture is stronger where onset distractors are frequent and weaker where they are rare, thus showing that habituation to onsets has a spatial selective nature. However, a debated question is whether habituation at a specific location is exclusively determined by the distractors' local rate, or whether instead local habituation is also affected by the global rate of the distractors, which may occur also at other locations. Here, we report the results from a between-participants experiment involving three groups of participants exposed to visual onsets during a visual search task. In two groups, onsets appeared at a single location with a high 60% rate or a low 15% rate, respectively, whereas in a third group, distractors could appear in four distinct locations with the same 15% local rate, leading to a 60% global rate. Our results confirmed that locally, habituation of capture was stronger the higher the distractors rate. However, the key finding was that we found a clear and robust modulation of the global distractors rate on the local habituation level. Taken together, our results unambiguously show that habituation has both a spatially selective and a spatially nonselective nature.

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.

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.

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.

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.

Revealing Whole-Brain Causality Networks During Guided Visual Searching

In our daily lives, we use eye movements to actively sample visual information from our environment ("active vision"). However, little is known about how the underlying mechanisms are affected by goal-directed behavior. In a study of 31 participants, magnetoencephalography was combined with eye-tracking technology to investigate how interregional interactions in the brain change when engaged in two distinct forms of active vision: freely viewing natural images or performing a guided visual search. Regions of interest with significant fixation-related evoked activity (FRA) were identified with spatiotemporal cluster permutation testing. Using generalized partial directed coherence, we show that, in response to fixation onset, a bilateral cluster consisting of four regions (posterior insula, transverse temporal gyri, superior temporal gyrus, and supramarginal gyrus) formed a highly connected network during free viewing. A comparable network also emerged in the right hemisphere during the search task, with the right supramarginal gyrus acting as a central node for information exchange. The results suggest that all four regions are vital to visual processing and guiding attention. Furthermore, the right supramarginal gyrus was the only region where activity during fixations on the search target was significantly negatively correlated with search response times. Based on our findings, we hypothesize that, following a fixation, the right supramarginal gyrus supplies the right supplementary eye field (SEF) with new information to update the priority map guiding the eye movements during the search task.

L-DOPA administration shifts the stability-flexibility balance towards attentional capture by distractors during a visual search task

RATIONALE

The cognitive control dilemma describes the necessity to balance two antagonistic modes of attention: stability and flexibility. Stability refers to goal-directed thought, feeling, or action and flexibility refers to the complementary ability to adapt to an ever-changing environment. Their balance is thought to be maintained by neurotransmitters such as dopamine, most likely in a U-shaped rather than linear manner. However, in humans, studies on the stability-flexibility balance using a dopaminergic agent and/or measurement of brain dopamine are scarce.

OBJECTIVE

The study aimed to investigate the causal involvement of dopamine in the stability-flexibility balance and the nature of this relationship in humans.

METHODS

Distractibility was assessed as the difference in reaction time (RT) between distractor and non-distractor trials in a visual search task. In a randomized, placebo-controlled, double-blind, crossover study, 65 healthy participants performed the task under placebo and a dopamine precursor (L-DOPA). Using ¹⁸F-DOPA-PET, dopamine availability in the striatum was examined at baseline to investigate its relationship to the RT distractor effect and to the L-DOPA-induced change of the RT distractor effect.

RESULTS

There was a pronounced RT distractor effect in the placebo session that increased under L-DOPA. Neither the RT distractor effect in the placebo session nor the magnitude of its L-DOPA-induced increase were related to baseline striatal dopamine.

CONCLUSIONS

L-DOPA administration shifted the stability-flexibility balance towards attentional capture by distractors, suggesting causal involvement of dopamine. This finding is consistent with current theories of prefrontal cortex dopamine function. Current data can neither confirm nor falsify the inverted U-shaped function hypothesis with regard to cognitive control.