Intrusive effects of semantic information on visual selective attention

Task-irrelevant semantic relationship between objects and scene influence attentional allocation

Recent behavioral evidence suggests that the semantic relationships between isolated objects can influence attentional allocation, with highly semantically related objects showing an increase in processing efficiency. This semantic influence is present even when it is task-irrelevant (i.e., when semantic information is not central to the task). However, given that objects exist within larger contexts, i.e., scenes, it is critical to understand whether the semantic relationship between a scene and its objects continuously influence attention. Here, we investigated the influence of task-irrelevant scene semantic properties on attentional allocation and the degree to which semantic relationships between scenes and objects interact. Results suggest that task-irrelevant associations between scenes and objects continuously influence attention and that this influence is directly predicted by the perceived strength of semantic associations.

Predicting attentional allocation in real-world environments: The need to investigate crossmodal semantic guidance

Real-world environments are multisensory, meaningful, and highly complex. To parse these environments in a highly efficient manner, a subset of this information must be selected both within and across modalities. However, the bulk of attention research has been conducted within sensory modalities, with a particular focus on vision. Visual attention research has made great strides, with over a century of research methodically identifying the underlying mechanisms that allow us to select critical visual information. Spatial attention, attention to features, and object-based attention have all been studied extensively. More recently, research has established semantics (meaning) as a key component to allocating attention in real-world scenes, with the meaning of an item or environment affecting visual attentional selection. However, a full understanding of how semantic information modulates real-world attention requires studying more than vision in isolation. The world provides semantic information across all senses, but with this extra information comes greater complexity. Here, we summarize visual attention (including semantic-based visual attention), crossmodal attention, and argue for the importance of studying crossmodal semantic guidance of attention. This article is categorized under: Psychology > Attention Psychology > Perception and Psychophysics.

Learned associations serve as target proxies during difficult but not easy visual search

The target template contains information in memory that is used to guide attention during visual search and is typically thought of as containing features of the actual target object. However, when targets are hard to find, it is advantageous to use other information in the visual environment that is predictive of the target's location to help guide attention. The purpose of these studies was to test if newly learned associations between face and scene category images lead observers to use scene information as a proxy for the face target. Our results showed that scene information was used as a proxy for the target to guide attention but only when the target face was difficult to discriminate from the distractor face; when the faces were easy to distinguish, attention was no longer guided by the scene unless the scene was presented earlier. The results suggest that attention is flexibly guided by both target features as well as features of objects that are predictive of the target location. The degree to which each contributes to guiding attention depends on the efficiency with which that information can be used to decode the location of the target in the current moment. The results contribute to the view that attentional guidance is highly flexible in its use of information to rapidly locate the target.

Object-based inhibition of return in three-dimensional space: From simple drawings to real objects

Cued to an object in space, inhibition of the attended location can spread to the entire object. Although object-based inhibition of return (IOR) studies in a two-dimensional plane have been documented, the IOR has not been explored when objects cross depth in three-dimensional (3D) space. In the present study, we used a virtual reality technique to adapt the double-rectangle paradigm to a 3D space, and manipulated the cue validity and target location to examine the difference in object-based IOR between far and near spaces under different object representations. The study showed that the object-based IOR of simple drawings existed only in near space, whereas object-based IOR of real objects existed only in far space at first, and as the object similarity decreases, it appeared in both far and near spaces.

Generalisation of value-based attentional priority is category-specific

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

Objects are selected for attention based upon meaning during passive scene viewing

While object meaning has been demonstrated to guide attention during active scene viewing and object salience guides attention during passive viewing, it is unknown whether object meaning predicts attention in passive viewing tasks and whether attention during passive viewing is more strongly related to meaning or salience. To answer this question, we used a mixed modeling approach where we computed the average meaning and physical salience of objects in scenes while statistically controlling for the roles of object size and eccentricity. Using eye-movement data from aesthetic judgment and memorization tasks, we then tested whether fixations are more likely to land on high-meaning objects than low-meaning objects while controlling for object salience, size, and eccentricity. The results demonstrated that fixations are more likely to be directed to high meaning objects than low meaning objects regardless of these other factors. Further analyses revealed that fixation durations were positively associated with object meaning irrespective of the other object properties. Overall, these findings provide the first evidence that objects are, in part, selected by meaning for attentional selection during passive scene viewing.

The association of targets modulates the search efficiency in multitarget searches

Previous studies have found that distractors can affect visual search efficiency when associated with the target in a single-target search. However, multitarget searches are frequently necessary in daily life. In the present study, we examined how the association of targets in a multitarget search affected performance when searching for two targets simultaneously (Experiment 1). In addition, we explored whether the association affected switch cost (Experiment 2) and preparation cost (Experiment 3). Participants were required to learn associations between different colors or shapes and then performed feature search and conjunction search tasks. For all experiments, the results of search efficiency showed that for conjunction search, the search efficiency under the associated condition was significantly higher than that under the neutral condition. Similarly, the response times in the associated condition were significantly faster than those in the neutral condition under the conjunction search condition in Experiments 1 and 2. However, in Experiment 3, the response times in the associated condition were longer than those in the neutral condition. These results indicate that the association between targets can improve the efficiency of multitarget searches. Furthermore, associations can reduce the time spent searching for individual targets and the switch cost; however, the preparation cost increases.

The effects of search-irrelevant working memory content on visual search

Previous experiments investigating visual search have shown that distractors that are semantically related to a search target can capture attention and slow the search process. In two experiments, we examine if distractors exactly matching, or semantically related to, search-irrelevant information held in working memory (WM) can also influence visual search while ruling out potential effects of color similarity. Participants first viewed and memorized an image of an everyday object, then they determined if a target item was present or absent in a two-object search array. On exact-match trials, the memorized object appeared as a distractor; on semantic-match trials, an object semantically related to the memorized object appeared as a distractor. Both exact-match and semantic-match distractors slowed search when the target was present in the search array. Our findings extend previous findings by demonstrating WM-driven attentional guidance by complex objects rather than simple features. The results also suggest that visual search can be influenced by distractors sharing only semantic features with a search-irrelevant, but active, WM representation.

Attention and platypuses

This perspective piece discusses a set of attentional phenomena that are not easily accommodated within current theories of attentional selection. We call these phenomena attentional platypuses, as they allude to an observation that within biological taxonomies the platypus does not fit into either mammal or bird categories. Similarly, attentional phenomena that do not fit neatly within current attentional models suggest that current models are in need of a revision. We list a few instances of the "attentional platypuses" and then offer a new approach, that we term dynamically weighted prioritization, stipulating that multiple factors impinge onto the attentional priority map, each with a corresponding weight. The interaction between factors and their corresponding weights determines the current state of the priority map which subsequently constrains/guides attentional allocation. We propose that this new approach should be considered as a supplement to existing models of attention, especially those that emphasize categorical organizations. This article is categorized under: Psychology > Attention Psychology > Perception and Psychophysics Neuroscience > Cognition.

How much is a cow like a meow? A novel database of human judgements of audiovisual semantic relatedness

Semantic information about objects, events, and scenes influences how humans perceive, interact with, and navigate the world. The semantic information about any object or event can be highly complex and frequently draws on multiple sensory modalities, which makes it difficult to quantify. Past studies have primarily relied on either a simplified binary classification of semantic relatedness based on category or on algorithmic values based on text corpora rather than human perceptual experience and judgement. With the aim to further accelerate research into multisensory semantics, we created a constrained audiovisual stimulus set and derived similarity ratings between items within three categories (animals, instruments, household items). A set of 140 participants provided similarity judgments between sounds and images. Participants either heard a sound (e.g., a meow) and judged which of two pictures of objects (e.g., a picture of a dog and a duck) it was more similar to, or saw a picture (e.g., a picture of a duck) and selected which of two sounds it was more similar to (e.g., a bark or a meow). Judgements were then used to calculate similarity values of any given cross-modal pair. An additional 140 participants provided word judgement to calculate similarity of word-word pairs. The derived and reported similarity judgements reflect a range of semantic similarities across three categories and items, and highlight similarities and differences among similarity judgments between modalities. We make the derived similarity values available in a database format to the research community to be used as a measure of semantic relatedness in cognitive psychology experiments, enabling more robust studies of semantics in audiovisual environments.

Meaning maps detect the removal of local semantic scene content but deep saliency models do not

Meaning mapping uses human raters to estimate different semantic features in scenes, and has been a useful tool in demonstrating the important role semantics play in guiding attention. However, recent work has argued that meaning maps do not capture semantic content, but like deep learning models of scene attention, represent only semantically-neutral image features. In the present study, we directly tested this hypothesis using a diffeomorphic image transformation that is designed to remove the meaning of an image region while preserving its image features. Specifically, we tested whether meaning maps and three state-of-the-art deep learning models were sensitive to the loss of semantic content in this critical diffeomorphed scene region. The results were clear: meaning maps generated by human raters showed a large decrease in the diffeomorphed scene regions, while all three deep saliency models showed a moderate increase in the diffeomorphed scene regions. These results demonstrate that meaning maps reflect local semantic content in scenes while deep saliency models do something else. We conclude the meaning mapping approach is an effective tool for estimating semantic content in scenes.

The past, present, and future of selection history

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

To Grasp the World at a Glance: The Role of Attention in Visual and Semantic Associative Processing

Associative relations among words, concepts and percepts are the core building blocks of high-level cognition. When viewing the world ‘at a glance’, the associative relations between objects in a scene, or between an object and its visual background, are extracted rapidly. The extent to which such relational processing requires attentional capacity, however, has been heavily disputed over the years. In the present manuscript, I review studies investigating scene–object and object–object associative processing. I then present a series of studies in which I assessed the necessity of spatial attention to various types of visual–semantic relations within a scene. Importantly, in all studies, the spatial and temporal aspects of visual attention were tightly controlled in an attempt to minimize unintentional attention shifts from ‘attended’ to ‘unattended’ regions. Pairs of stimuli—either objects, scenes or a scene and an object—were briefly presented on each trial, while participants were asked to detect a pre-defined target category (e.g., an animal, a nonsense shape). Response times (RTs) to the target detection task were registered when visual attention spanned both stimuli in a pair vs. when attention was focused on only one of two stimuli. Among non-prioritized stimuli that were not defined as to-be-detected targets, findings consistently demonstrated rapid associative processing when stimuli were fully attended, i.e., shorter RTs to associated than unassociated pairs. Focusing attention on a single stimulus only, however, largely impaired this relational processing. Notably, prioritized targets continued to affect performance even when positioned at an unattended location, and their associative relations with the attended items were well processed and analyzed. Our findings portray an important dissociation between unattended task-irrelevant and task-relevant items: while the former require spatial attentional resources in order to be linked to stimuli positioned inside the attentional focus, the latter may influence high-level recognition and associative processes via feature-based attentional mechanisms that are largely independent of spatial attention.

Meaning maps capture the density of local semantic features in scenes: A reply to Pedziwiatr, Kümmerer, Wallis, Bethge & Teufel (2021)

Pedziwiatr, Kümmerer, Wallis, Bethge, & Teufel (2021) contend that Meaning Maps do not represent the spatial distribution of semantic features in scenes. We argue that Pesziwiatr et al. provide neither logical nor empirical support for that claim, and we conclude that Meaning Maps do what they were designed to do: represent the spatial distribution of meaning in scenes.

Task-Irrelevant Semantic Properties of Objects Impinge on Sensory Representations within the Early Visual Cortex

Objects can be described in terms of low-level (e.g., boundaries) and high-level properties (e.g., object semantics). While recent behavioral findings suggest that the influence of semantic relatedness between objects on attentional allocation can be independent of task-relevance, the underlying neural substrate of semantic influences on attention remains ill-defined. Here, we employ behavioral and functional magnetic resonance imaging measures to uncover the mechanism by which semantic information increases visual processing efficiency. We demonstrate that the strength of the semantic relatedness signal decoded from the left inferior frontal gyrus: 1) influences attention, producing behavioral semantic benefits; 2) biases spatial attention maps in the intraparietal sulcus, subsequently modulating early visual cortex activity; and 3) directly predicts the magnitude of behavioral semantic benefit. Altogether, these results identify a specific mechanism driving task-independent semantic influences on attention.

Semantically predictable input streams impede gaze-orientation to surprising locations

When available, people use prior knowledge to predict dimensions of future events such as their location and semantic features. However, few studies have examined how multi-dimensional predictions are implemented, and mechanistic accounts are absent. Using eye tracking, we evaluated whether predictions of target-location and target-category interact during the earliest stages of orientation. We presented stochastic series so that across four conditions, participants could predict either the location of the next target-image, its semantic category, both dimensions, or neither. Participants observed images in absence of any task involving their semantic content. We modeled saccade latencies using ELATER, a rise-to-threshold model that accounts for accumulation rate (AR), variance of AR over trials, and variance of decision baseline. The main findings were: 1) AR scaled with the degree of surprise associated with a target's location; 2) predictability of semantic-category hindered saccade latencies, suggesting a bottleneck in implementing joint predictions; 3) saccades to targets that satisfied semantic expectations were associated with greater AR-variance than saccades to semantically-surprising images, consistent with a richer repertoire of early evaluative processes for semantically-expected images. Predictability of target-category also impacted gaze pre-positioning prior to target presentation. The results indicate a strong interaction between foreknowledge of object location and semantics during stimulus-guided saccades, and suggest statistical regularities in an input stream can also impact anticipatory, non-stimulus-guided processes.

Vision at a glance: The role of attention in processing object-to-object categorical relations

When viewing a scene at a glance, the visual and categorical relations between objects in the scene are extracted rapidly. In the present study, the involvement of spatial attention in the processing of such relations was investigated. Participants performed a category detection task (e.g., "is there an animal") on briefly flashed object pairs. In one condition, visual attention spanned both stimuli, and in another, attention was focused on a single object while its counterpart object served as a task-irrelevant distractor. The results showed that when participants attended to both objects, a categorical relation effect was obtained (Exp. 1). Namely, latencies were shorter to objects from the same category than to those from different superordinate categories (e.g., clothes, vehicles), even if categories were not prioritized by the task demands. Focusing attention on only one of two stimuli, however, largely eliminated this effect (Exp. 2). Some relational processing was seen when categories were narrowed to the basic level and were highly distinct from each other (Exp. 3), implying that categorical relational processing necessitates attention, unless the unattended input is highly predictable. Critically, when a prioritized (to-be-detected) object category, positioned in a distractor's location, differed from an attended object, a robust distraction effect was consistently observed, regardless of category homogeneity and/or of response conflict factors (Exp. 4). This finding suggests that object relations that involve stimuli that are highly relevant to the task settings may survive attentional deprivation at the distractor location. The involvement of spatial attention in object-to-object categorical processing is most critical in situations that include wide categories that are irrelevant to one's current goals.

Different temporal dynamics of object-based attentional allocation for reward and non-reward objects

Previous studies have confirmed that both non-reward objects (such as rectangles) and reward objects (such as banknotes) can guide the allocation of our attention; however, it is unclear whether the allocation mode of attention for reward objects is the same as for non-reward objects. This study aims to evaluate different modes of object-based attentional selection elicited by two types of objects: reward objects and non-reward objects. In our analysis, we used a two-rectangle paradigm in which two objects were presented visually. In a series of four experiments, we found a constant object-based effect with non-reward objects, such as rectangles and umbrellas, as stimuli in all of the stimulus onset asynchrony (SOA) conditions (Experiments 1 and 4), but the object-based effect disappeared only at longer SOA with reward objects such as monetary and food objects as stimuli (Experiments 2 and 3). Moreover, we found that monetary and food objects induced similar object-based effects. These results suggest that the temporal dynamics of object-based attentional allocation are different with respect to reward and non-reward objects, and different types of reward objects can guide attentional allocation in a similar way.

The influence of object similarity on real object-based attention: The disassociation of perceptual and semantic similarity

Perceptual and semantic similarity have an impact on object-based attention for the geometric objects. However, no previous studies have disassociated perceptual properties from the semantic ones of real objects that combine perceptual and semantic properties. It is unclear whether the perceptual and semantic similarity of real objects jointly or independently guides attentional deployment. The aim of the present study was to explore the influence of object similarity on object-based attention by using a variant of the two-rectangle paradigm and disassociating the perceptual and semantic similarity of real objects. The results indicated that when the semantic of objects was similar, the object-based effect was larger for the perceptually dissimilar condition than for the perceptually similar condition, because of slower response to invalid different-object location in a dissimilar condition. Moreover, when the perception of objects was similar, the object-based effect was larger for the semantically dissimilar condition than for the semantically similar condition, due to slower response to invalid different-object location in a dissimilar condition. These results suggest that perceptual and semantic similarity can independently guide attentional allocation to real objects and the similarity may constrain the object-based attention in a way of grouping. The current study implies that the attentional prioritization hypothesis is more flexible and effective to explain the real object-based attention and also has some implication to advertising design.

Functional Imaging of Visuospatial Attention in Complex and Naturalistic Conditions

One of the ultimate goals of cognitive neuroscience is to understand how the brain works in the real world. Functional imaging with naturalistic stimuli provides us with the opportunity to study the brain in situations similar to the everyday life. This includes the processing of complex stimuli that can trigger many types of signals related both to the physical characteristics of the external input and to the internal knowledge that we have about natural objects and environments. In this chapter, I will first outline different types of stimuli that have been used in naturalistic imaging studies. These include static pictures, short video clips, full-length movies, and virtual reality, each comprising specific advantages and disadvantages. Next, I will turn to the main issue of visual-spatial orienting in naturalistic conditions and its neural substrates. I will discuss different classes of internal signals, related to objects, scene structure, and long-term memory. All of these, together with external signals about stimulus salience, have been found to modulate the activity and the connectivity of the frontoparietal attention networks. I will conclude by pointing out some promising future directions for functional imaging with naturalistic stimuli. Despite this field of research is still in its early days, I consider that it will play a major role in bridging the gap between standard laboratory paradigms and mechanisms of brain functioning in the real world.

The functional arrangement of objects biases gaze direction

A growing number of studies suggest that semantic knowledge can influence the control of gaze in scenes. For example, observers are more likely to look toward objects that are semantically related to the currently fixated object. Recent evidence also suggests that an object's functional orientation can bias gaze direction. However, it is unknown whether these semantic and functional relationships can interact to determine gaze control. To address this issue, the present study assessed whether the functional arrangement of multiple objects can influence gaze control. Participants fixated a central object (e.g., a key) flanked by two peripheral objects. After a brief delay, participants were free to shift their gaze toward the peripheral object of their choice. One of the peripheral objects was semantically related to the central object (e.g., a lock), and the objects were arranged to depict a functional or non-functional interaction (e.g., a key pointing toward or away from a lock). When the orientation of the central object was manipulated, participants were more likely to look in the direction this object was pointing. Moreover, the functional arrangement of objects modulated this central orienting bias. However, when the orientation of the peripheral objects was manipulated, only the peripheral objects' semantic relationships influenced gaze control. Together, these findings suggest that functional relationships play an important role in the allocation of gaze, and can interact with semantic relationships to determine gaze control.

Attention scales according to inferred real-world object size

Natural scenes consist of objects of varying shapes and sizes. The impact of object size on visual perception has been well-demonstrated, from classic mental imagery experiments¹, to recent studies of object representations reporting topographic organization of object size in the occipito-temporal cortex². While the role of real-world physical size in perception is clear, the effect of inferred size on attentional selection is ill-defined. Here, we investigate whether inferred real-world object size influences attentional allocation. Across five experiments, attentional allocation was measured in objects of equal retinal size, but varied in inferred real-world size (for example, domino, bulldozer). Following each experiment, participants rated the real-world size of each object. We hypothesized that, if inferred real-world size influences attention, selection in retinal size-matched objects should be less efficient in larger objects. This effect should increase with greater attentional demand. Predictions were supported by faster identified targets in objects inferred to be small than large, with costlier attentional shifting in large than small objects when attentional demand was high. Critically, there was a direct correlation between the rated size of individual objects and response times (and shifting costs). Finally, systematic degradation of size inference proportionally reduced object size effect. It is concluded that, along with retinal size, inferred real-world object size parametrically modulates attention. These findings have important implications for models of attentional control and invite sensitivity to object size for future studies that use real-world images in psychological research.

Intrusive effects of task-irrelevant information on visual selective attention: semantics and size

Attentional selection is a mechanism by which incoming sensory information is prioritized for further, detailed, and more effective, processing. Given that attended information is privileged by the sensory system, understanding and predicting what information is granted prioritization becomes an important endeavor. It has been argued that salient events as well as information that is related to the current goal of the organism (i.e., task-relevant) receive such a priority. Here, we propose that attentional prioritization is not limited to task-relevance, and discuss evidence showing that task-irrelevant, non-salient, high-level properties of unattended objects, namely object meaning and size, influence attentional allocation. Such an intrusion of non-salient, task-irrelevant, high-level information points to the need to re-conceptualize and formally modify current models of attentional guidance.

Cognitive Performance in Indian School-Going Adolescents Is Positively Affected by Consumption of Iron-Biofortified Pearl Millet: A 6-Month Randomized Controlled Efficacy Trial

BACKGROUND

Iron deficiency remains the most prevalent micronutrient deficiency globally, but few studies have examined how iron status relates to cognition in adolescents. Iron biofortification of staple food crops is being scaled up, yet it is unknown whether consuming biofortified crops can benefit cognition.

Objective

Our objective was to determine the efficacy of iron-biofortified pearl millet in improving attention and memory in Indian school-going adolescents.

Methods

A double-blind, randomized, intervention study was conducted in 140 Indian boys and girls, aged 12-16 y, who were assigned to consume iron-biofortified [Fe = 86 parts per million (ppm)] or conventional (Fe = 21-52 ppm) pearl millet. Hemoglobin, ferritin, and transferrin receptor (TfR) were measured and body iron (BI) was calculated at baseline and after 4 and 6 mo. Five measures of cognitive function were obtained at baseline and 6 mo: simple reaction time (SRT), Go/No-Go (GNG) task, Attentional Network Task (ANT), Composite Face Effect (CFE) task, and Cued Recognition Task (CRT). Intention-to-treat analysis was used.

Results

Daily iron intake from pearl millet was higher in those consuming biofortified compared with conventional pearl millet (19.6 compared with 4.8 mg/d). Effects on ferritin, TfR, and BI at 4 mo, and on TfR at 6 mo (all P < 0.05), indicated efficacy of biofortified pearl millet over conventional pearl millet in improving iron status. Compared with conventional pearl millet, the consumption of biofortified pearl millet resulted in greater improvement in attention (SRT, GNG, and ANT) and memory (CFE and CRT). Reaction time decreased twice as much from 0 to 6 mo in those consuming biofortified compared with conventional pearl millet on attention tasks (SRT: -123 compared with -63 ms; GNG: -67 compared with -30 ms; ANT double cue: -74 compared with -32 ms; all P < 0.01).

Conclusion

Consuming iron-biofortified pearl millet improves iron status and some measures of cognitive performance in Indian adolescents. This trial was registered at http://www.clinicaltrials.gov as NCT02152150.