When searching for objects, our sensory resources are limited. According to the zoom lens model of attention, the visual system can flexibly adapt the size of the attentional spotlight applied to an array of items depending on task difficulty. When search tasks are relatively straightforward, attention can be distributed widely across space to process several items simultaneously. However, when discrimination becomes more difficult, the attentional spotlight constricts to concentrate resources to a limited area resulting in the processing of only one or very few items simultaneously at any one time. The present study aimed to empirically test the zoom lens account by assessing search performance while systematically altering the visible area in the search display (field of view [FOV]). We presented two search tasks of contrasting difficulty in a virtual reality environment with a head-contingent display. When the FOV became smaller, there were no differences in search times between the two search tasks, a result which seems to contradict the predictions of the zoom lens model. The zoom lens model predicts that restricted viewing in a demanding search task should exact a smaller cost because of the presence of the smaller attentional window. However, we did not find any evidence of such an effect. Results from an analysis of head and eye movements also suggested that when using both fixations and head movements to scan their environment, participants used head movements to reveal new areas of the visual scene in a manner largely disconnected from classic eye movement and attentional processes. Once the head came to rest, attentional shifts and eye movements were used to search within the newly revealed area.

Attention can be attracted to salient items in a visual scene. Recent studies have shown that when the feature of an irrelevant salient item is known, it can be suppressed below baseline leading to facilitated search. Wang and Theeuwes (Experimental Psychology: Human Perception and Performance, 46(10), 1051-1057, 2020) criticised previous inhibition studies by claiming that the sparse displays attenuated the salience of the distractors. In their study they increased the number of display items (i.e., set size), and found that an irrelevant salient distractor captured attention. The current paper argues that the displays used by Wang and Theeuwes encouraged participants to use a singleton search mode, in which participants actively look for salient regions to find the target and consequently do not inhibit salient items. Specifically, their displays included multiple repeated non-target shapes, so that the target became a singleton. We used two search displays with ten items, one with repeated non-targets (R-NT displays), allowing a singleton search mode, and one with heterogeneous non-targets, encouraging a feature search mode. In Experiment 1 the singleton distractor was inhibited in the heterogeneous condition, but not in the R-NT condition. Experiment 2 intermixed the two display types in unbalanced blocks. When the majority of trials had heterogeneous non-targets, inhibition was observed for both the heterogeneous displays and the R-NT displays. Conversely, when R-NT displays were the majority, inhibition was attenuated for both display types. These results show that distractor features can be suppressed at large set sizes dependant on the search strategy promoted by the displays.

The most prominent models of visual attention assume that we tune attention to the specific feature value of a sought-after object (e.g., a specific colour or orientation) to aid search. However, subsequent research has shown that attention is often tuned to the relative feature of the target, that the target has in relation to other items in the surround (e.g., redder/greener, darker/lighter, larger/smaller), in line with a Relational Account of Attention. Previous research is still limited though, as it used repeated-target designs and relatively sparse displays. With this, it is still unknown whether we can indeed tune attention to relative features prior to the first eye movement, or whether this requires context knowledge gained from experience. Moreover, it is unclear how search progresses from one item to the next. The present study tested these questions in a 36-item search display with multiple distractors and variable target and non-target colours. The first fixations on a trial showed that these displays still reliably evoked relational search, even when observers had no knowledge of the context. Moreover, the first five fixations within a trial showed that we tend to select the most extreme items first, followed by the next-extreme, until the target is found, in line with the relational account. These findings show that information about the relative target feature can be rapidly extracted and is used to guide attention in the first fixation(s) of search, whereby attention only hones in on the target colour after multiple fixations on relatively more extreme distractors.

Research on visual search for emotional faces has yielded discrepant results, with some studies reporting advantages for angry faces (anger superiority effect) and others reporting a happy face advantage (happiness superiority effect). Researchers have sought to explain these phenomena through an emotional factors account: attributing the anger superiority effect to an innate threat detector, and the happiness superiority effect to a positivity bias that gives preference to positive stimuli. The alternative perceptual factors account proposes that salient perceptual features inherent to angry and happy faces drive these search asymmetries. As emotional and perceptual factors are intrinsically confounded in emotional faces, it has proven difficult to distinguish between the two accounts. In the present experiments, we distinguished between the two accounts by manipulating participant mood across three different conditions (neutral, angry, and happy), and asked participants to locate a variable emotional (angry or happy) target face. Eye-tracking measures revealed a significant mood-congruency effect for search efficiency, where fewer fixations were required to locate a mood-congruent target than a mood-incongruent target. These findings were obtained across two experiments using different face stimuli (dynamic vs. static faces), emotional and neutral nontargets, and different search requirements, indicating that participant mood can influence attention across a wide range of conditions. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

It has been repeatedly claimed that emotional faces readily capture attention, and that they may be processed without awareness. Yet some observations cast doubt on these assertions. Part of the problem may lie in the experimental paradigms employed. Here, we used a free viewing visual search task during electroencephalographic recordings, where participants searched for either fearful or neutral facial expressions among distractor expressions. Fixation-related potentials were computed for fearful and neutral targets and the response compared for stimuli consciously reported or not. We showed that awareness was associated with an electrophysiological negativity starting at around 110 ms, while emotional expressions were distinguished on the N170 and early posterior negativity only when stimuli were consciously reported. These results suggest that during unconstrained visual search, the earliest electrical correlate of awareness may emerge as early as 110 ms, and fixating at an emotional face without reporting it may not produce any unconscious processing.

As the number of unlabeled or mislabeled electroencephalogram (EEG) increases dramatically in such applications as cerebral disease diagnosis, rehabilitation, and brain-computer interfaces, the supervised approaches that require labels or markers become inapplicable. Unfortunately, there are few reports on unsupervised studies for unlabeled EEG data, especially for unlabeled EEG clustering. To address the challenging task, we propose an effective approach named ShVEEGc for EEG clustering inspired by an improved Shapley value in cooperative game theory. The idea of ShVEEGc is first utilizing an improved cosine similarity to measure the correlations of EEG data and then calculating the improved Shapley value based on the inherent connection between unlabeled EEG data, which considers both global connections and local relationships potentially hidden in EEG data. Thus, ShVEEGc not only has good anti-interference ability but also can mine potential relationships among unlabeled EEG data. The comparison experiments with fourteen state-of-the-art EEG time series clustering algorithms on eleven real-world EEG datasets with four standard evaluation criteria demonstrate the efficacy and superiority of ShVEEGc for EEG clustering. Besides, the discussion on the impact of several different similarity measures on ShVEEGc also illustrates that the improved cosine similarity proposed in this paper is more suitable for EEG data.

Visual attention and visual working memory (VWM) are intertwined processes that allow navigation of the visual world. These systems can compete for highly limited cognitive resources, creating interference effects when both operate in tandem. Performing an attentional task while maintaining a VWM load often leads to a loss of memory information. These losses are seen even with very simple visual search tasks. Previous research has argued that this may be due to the attentional selection process, of choosing the target item out of surrounding nontarget items. Over two experiments, the current study disentangles the roles of search and selection in visual search and their influence on a retained VWM load. Experiment 1 revealed that, when search stimuli were relatively simple, target-absent searches (which did not require attentional selection) did not provoke memory interference, whereas target-present search did. In Experiment 2, the number of potential targets was varied in the search displays. In one condition, participants were required to select any one of the items displayed, requiring an attentional selection but no need to search for a specific item. Importantly, this condition led to memory interference to the same extent as a condition where a single target was presented among nontargets. Together, these results show that the process of attentional selection is a sufficient cause for interference with a concurrently maintained VWM load.

It is well known that visual search for a mirror target (i.e., a horizontally flipped item) is more difficult than search for other-oriented items (e.g., vertically flipped items). Previous studies have typically attributed costs of mirror search to early, attention-guiding processes but could not rule out contributions from later processes. In the present study we used eye tracking to distinguish between early, attention-guiding processes and later target identification processes. The results of four experiments revealed a marked human weakness in identifying mirror targets: Observers appear to frequently fail to classify a mirror target as a target on first fixation and to continue with search even after having directly looked at the target. Awareness measures corroborated that the location of a mirror target could not be reported above chance level after it had been fixated once. This mirror blindness effect explained a large proportion (45-87%) of the overall costs of mirror search, suggesting that part of the difficulties with mirror search are rooted in later, object identification processes (not attentional guidance). Mirror blindness was significantly reduced but not completely eliminated when both the target and non-targets were held constant, which shows that perfect top-down knowledge can reduce mirror blindness, without completely eliminating it. The finding that non-target certainty reduced mirror blindness suggests that object identification is not solely achieved by comparing a selected item to a target template. These results demonstrate that templates that guide search toward targets are not identical to the templates used to conclusively identify those targets.

Theories of attention posit that attentional guidance operates on information held in a target template within memory. The template is often thought to contain veridical target features, akin to a photograph, and to guide attention to objects that match the exact target features. However, recent evidence suggests that attentional guidance is highly flexible and often guided by non-veridical features, a subset of features, or only associated features. We integrate these findings and propose that attentional guidance maximizes search efficiency based on a 'good-enough' principle to rapidly localize candidate target objects. Candidates are then serially interrogated to make target-match decisions using more precise information. We suggest that good-enough guidance optimizes the speed-accuracy-effort trade-offs inherent in each stage of visual search.

Electroencephalogram (EEG)-based applications in Brain-Computer Interfaces (BCIs, or Human-Machine Interfaces, HMIs), diagnosis of neurological disease, rehabilitation, etc , rely on supervised techniques such as EEG classification that requires given class labels or markers. Incomplete or incorrectly labeled or unlabeled EEG data are increasing with the ever-expanding amount of EEG data generated by such applications and the ambiguities these generate degrade the performance of supervised techniques. To address the challenging task of clustering EEG data with limited priori knowledge, we introduce a semi-supervised graph embedding EEG clustering approach termed ConsEEGc with multiple constraints, i.e. , label-transformed connectivity constraints that constrains the connection or disconnection among EEG data, compactness-and-scatter constraint that constrains the intra-cluster compactness and inter-cluster scatter of EEG clusters, and fairness constraint that constrains the fair ratio of elements between EEG clusters, to make best use of limited priori knowledge of EEG data and to achieve better EEG clustering results. ConsEEGc is conducted with an optimization objective function that integrates pseudo label learning, least-square error minimization and multiple constraints, and it can quickly converge to local optima. The experiments demonstrate that ConsEEGc can efficiently yield good clustering results on various types of real-world EEG datasets, compared to state-of-the-art standard unsupervised and semi-supervised EEG/time series clustering algorithms.

Previous research on emotional face processing has shown that emotional faces such as fearful faces may be processed without visual awareness. However, evidence for nonconscious attention capture by fearful faces is limited. In fact, studies using sensory manipulation of awareness (e.g., backward masking paradigms) have shown that fearful faces do not attract attention during subliminal viewings nor when they were task-irrelevant. Here, we used a three-phase inattentional blindness paradigm and electroencephalography to examine whether faces (fearful and neutral) capture attention under different conditions of awareness and task-relevancy. We found that the electrophysiological marker for attention capture, the N2-posterior-contralateral (N2pc), was elicited by face stimuli only when participants were aware of the faces and when they were task-relevant (phase 3). When participants were unaware of the presence of faces (phase 1) or when the faces were irrelevant to the task (phase 2), no N2pc was observed. Together with our previous work, we concluded that fearful faces, or faces in general, do not attract attention unless we want them to.

Visual working memory (VWM) allows for the brief retention of approximately three to four items. Interestingly, when these items are similar to each other in a feature domain, memory recall performance is elevated compared to when they are dissimilar. This similarity benefit is currently not accounted for by models of VWM. Previous research has suggested that this similarity benefit may arise from selective attentional prioritisation in the maintenance phase. However, the similarity effect has not been contrasted under circumstances where dissimilar item types can adequately compete for memory resources. In Experiment 1, similarity benefits were seen for all-similar over all-dissimilar displays. This was also seen in mixed displays, change detection performance was higher when one of the two similar items changed, compared to when the dissimilar item changed. Surprisingly, the similarity effect was stronger in these mixed displays then when comparing the all-similar and all-dissimilar. Experiment 2 investigated this further by examining how attention was allocated in the memory encoding phase via eye movements. Results revealed that attention prioritised similar over dissimilar items in the mixed displays. Similar items were more likely to receive the first fixation and were fixated more often than dissimilar items. Furthermore, dwell times were elongated for dissimilar items, suggesting that encoding was less efficient. These results suggest that there is an attentional strategy towards prioritising similar items over dissimilar items, and that this strategy’s influence can be observed in the memory encoding phase.

It is well-known that visual attention can be tuned in a context-dependent manner to elementary features, such as searching for all redder items or the reddest item, supporting a relational theory of visual attention. However, in previous studies, the conditions were often conducive for relational search, allowing successfully selecting the target relationally on 50% of trials or more. Moreover, the search displays were often only sparsely populated and presented repeatedly, rendering it possible that relational search was based on context learning and not spontaneous. The present study tested the shape of the attentional tuning function in 36-item search displays, when the target never had a maximal feature value (e.g., was never the reddest or yellowest item), and when only the target colour but not the context colour was known. The first fixations on a trial showed that these displays still reliably evoked relational search, even when participants had no advance information about the context and no on-task training. Context learning further strengthened relational tuning on subsequent trials, but was not necessary for relational search. Analysing the progression of visual search within a singe trial showed that attention is first guided to the relationally maximal item (e.g., reddest), then the next-maximal (e.g., next-reddest) item, and so forth, before attention can hone in on target-matching features. In sum, the results support two tenets of the relational account, that information about the dominant feature in a display can be rapidly extracted and used to guide attention to the relatively best-matching features.

When searching for a lost item, we tune attention to the known properties of the object. Previously, it was believed that attention is tuned to the veridical attributes of the search target (e.g., orange), or an attribute that is slightly shifted away from irrelevant features towards a value that can more optimally distinguish the target from the distractors (e.g., red-orange; optimal tuning). However, recent studies showed that attention is often tuned to the relative feature of the search target (e.g., redder), so that all items that match the relative features of the target equally attract attention (e.g., all redder items; relational account). Optimal tuning was shown to occur only at a later stage of identifying the target. However, the evidence for this division mainly relied on eye tracking studies that assessed the first eye movements. The present study tested whether this division can also be observed when the task is completed with covert attention and without moving the eyes. We used the N2pc in the EEG of participants to assess covert attention, and found comparable results: Attention was initially tuned to the relative colour of the target, as shown by a significantly larger N2pc to relatively matching distractors than a target-coloured distractor. However, in the response accuracies, a slightly shifted, "optimal" distractor interfered most strongly with target identification. These results confirm that early (covert) attention is tuned to the relative properties of an item, in line with the relational account, while later decision-making processes may be biased to optimal features.

Previous research has identified three mechanisms that guide visual attention: bottom-up feature contrasts, top-down tuning, and the trial history (e.g., priming effects). However, only few studies have simultaneously examined all three mechanisms. Hence, it is currently unclear how they interact or which mechanisms dominate over others. With respect to local feature contrasts, it has been claimed that a pop-out target can only be selected immediately in dense displays when the target has a high local feature contrast, but not when the displays are sparse, which leads to an inverse set-size effect. The present study critically evaluated this view by systematically varying local feature contrasts (i.e., set size), top-down knowledge, and the trial history in pop-out search. We used eye tracking to distinguish between early selection and later identification-related processes. The results revealed that early visual selection was mainly dominated by top-down knowledge and the trial history: When attention was biased to the target feature, either by valid pre-cueing (top-down) or automatic priming, the target could be localised immediately, regardless of display density. Bottom-up feature contrasts only modulated selection when the target was unknown and attention was biased to the non-targets. We also replicated the often-reported finding of reliable feature contrast effects in the mean RTs, but showed that these were due to later, target identification processes (e.g., in the target dwell times). Thus, contrary to the prevalent view, bottom-up feature contrasts in dense displays do not seem to directly guide attention, but only facilitate nontarget rejection, probably by facilitating nontarget grouping.

In the current EEG study, we used a dot-probe task in conjunction with backward masking to examine the neural activity underlying awareness and spatial processing of fearful faces and the neural processes for subsequent cued spatial targets. We presented face images under different viewing conditions (subliminal and supraliminal) and manipulated the relation between a fearful face in the pair and a subsequent target. Our mass univariate analysis showed that fearful faces elicit the N2-posterior-contralateral, indexing spatial attention capture, only when they are presented supraliminally. Consistent with this, the multivariate pattern analysis revealed a successful decoding of the location of the fearful face only in the supraliminal viewing condition. Additionally, the spatial attention capture by fearful faces modulated the processing of subsequent lateralised targets that were spatially congruent with the fearful face, in both al and electrophysiological data. There was no evidence for nonconscious processing of the fearful faces in the current paradigm. We conclude that spatial attentional capture by fearful faces requires visual awareness and it is modulated by top-down task demands.

It remains unclear to date whether spatial attention towards emotional faces is contingent on, or independent of visual awareness. To investigate this question, a bilateral attentional blink paradigm was used in which lateralised fearful faces were presented at various levels of detectability. Twenty-six healthy participants were presented with two rapid serial streams of human faces, while they attempted to detect a pair of target faces (T2) displayed in close or distant succession of a first target pair (T1). Spatial attention shifting to the T2 fearful faces, indexed by the N2-posterior-contralateral component, was dependent on visual awareness and its magnitude covaried with the visual awareness negativity, a neural marker of awareness at the perceptual level. Additionally, information consolidation in working memory, indexed by the sustained posterior contralateral negativity, positively correlated with the level of visual awareness and spatial attention shifting. These findings demonstrate that spatial attention shifting to fearful faces depends on visual awareness, and these early processes are closely linked to information maintenance in working memory.

It is well known that attention can be automatically attracted to salient items. However, recent studies show that it is possible to avoid distraction by a salient item (with a known feature), leading to facilitated search. This article tests a proposed mechanism for distractor inhibition: that a mental representation of the distractor feature held in visual working memory (VWM) allows attention to be guided away from the distractor. We tested this explanation by examining color-based inhibition in visual search for a shape target with and without VWM load. In Experiment 1 the presence of a distractor facilitated visual search under low and high VWM loads, as reflected in faster response times when the distractor was present (compared to absent), and in fewer eye movements to the salient distractor than the non-target items. However, the eye movement inhibition effect was noticeably weakened in the load conditions. Experiment 2 explored further, to distinguish between inhibition of the distractor color and activation of the (irrelevant) target color. Intermittently presenting single-color search trials that contained only either a target, distractor or a neutral-colored singleton revealed that the distractor color attracted attention less than the neutral color with and without VWM load. The target color, however, only attracted attention more than neutral colors under no load, whereas a VWM load completely eliminated this effect. This suggests that although VWM plays a role in guiding attention to the (irrelevant) target color, distractor-feature inhibition can operate independently.

In visual search attention can be directed towards items matching top-down goals, but this must compete with factors such as salience that can capture attention. However, under some circumstances it appears that attention can avoid known distractor features. Chang and Egeth (Psychological Science, 30 (12), 1724-1732, 2019) found that such inhibitory effects reflect a combination of distractor-feature suppression and target-feature enhancement. In the present study (N = 48), we extend these findings by revealing that suppression and enhancement effects guide overt attention. On search trials (75% of trials) participants searched for a diamond shape among several other shapes. On half of the search trials all objects were the same colour (e.g., green) and on the other half of the search trials one of the non-target shapes appeared in a different colour (e.g., red). On interleaved probe trials (25% of trials), subjects were presented with four ovals. One of the ovals was in either the colour of the target or the colour of the distractor from the search trials. The other three ovals were on neutral colours. Critically, we found that attention was overtly captured by target colours and avoided distractor colours when they were viewed in a background of neutral colours. In addition, we provided a time course of attentional control. Within visual search tasks we observed inhibition aiding early attentional effects, indexed by the time it took gaze to first reach the target, as well as later decision-making processes indexed by the time for a decision to be made once the target as found.