Meaning guides attention in real-world scene images: Evidence from eye movements and meaning maps

Finding the meaning in meaning maps: Quantifying the roles of semantic and non-semantic scene information in guiding visual attention

In real-world vision, people prioritise the most informative scene regions via eye-movements. According to the cognitive guidance theory of visual attention, viewers allocate visual attention to those parts of the scene that are expected to be the most informative. The expected information of a scene region is coded in the semantic distribution of that scene. Meaning maps have been proposed to capture the spatial distribution of local scene semantics in order to test cognitive guidance theories of attention. Notwithstanding the success of meaning maps, the reason for their success has been contested. This has led to at least two possible explanations for the success of meaning maps in predicting visual attention. On the one hand, meaning maps might measure scene semantics. On the other hand, meaning maps might measure scene features, overlapping with, but distinct from, scene semantics. This study aims to disentangle these two sources of information by considering both conceptual information and non-semantic scene entropy simultaneously. We found that both semantic and non-semantic information is captured by meaning maps, but scene entropy accounted for more unique variance in the success of meaning maps than conceptual information. Additionally, some explained variance was unaccounted for by either source of information. Thus, although meaning maps may index some aspect of semantic information, their success seems to be better explained by non-semantic information. We conclude that meaning maps may not yet be a good tool to test cognitive guidance theories of attention in general, since they capture non-semantic aspects of local semantic density and only a small portion of conceptual information. Rather, we suggest that researchers should better define the exact aspect of cognitive guidance theories they wish to test and then use the tool that best captures that desired semantic information. As it stands, the semantic information contained in meaning maps seems too ambiguous to draw strong conclusions about how and when semantic information guides visual attention.

Don't look now! Social elements are harder to avoid during scene viewing

Regions of social importance (i.e., other people) attract attention in real world scenes, but it is unclear how automatic this bias is and how it might interact with other guidance factors. To investigate this, we recorded eye movements while participants were explicitly instructed to avoid looking at one of two objects in a scene (either a person or a non-social object). The results showed that, while participants could follow these instructions, they still made errors (especially on the first saccade). Crucially, there were about twice as many erroneous looks towards the person than there were towards the other object. This indicates that it is hard to suppress the prioritization of social information during scene viewing, with implications for how quickly and automatically this information is perceived and attended to.

Brief Report: Differences in Naturalistic Attention to Real-World Scenes in Adolescents with 16p.11.2 Deletion

Sensory differences are nearly universal in autism, but their genetic origins are poorly understood. Here, we tested how individuals with an autism-linked genotype, 16p.11.2 deletion ("16p"), attend to visual information in immersive, real-world photospheres. We monitored participants' (N = 44) gaze while they actively explored 360° scenes via headmounted virtual reality. We modeled the visually salient and semantically meaningful information in scenes and quantified the relative bottom-up vs. top-down influences on attentional deployment. We found, when compared to typically developed control (TD) participants, 16p participants' attention was less dominantly predicted by semantically meaningful scene regions, relative to visually salient regions. These results suggest that a reduction in top-down relative to bottom-up attention characterizes how individuals with 16p.11.2 deletions engage with naturalistic visual environments.

The role of local meaning in infants' fixations of natural scenes

As infants view visual scenes every day, they must shift their eye gaze and visual attention from location to location, sampling information to process and learn. Like adults, infants' gaze when viewing natural scenes (i.e., photographs of everyday scenes) is influenced by the physical features of the scene image and a general bias to look more centrally in a scene. However, it is unknown how infants' gaze while viewing such scenes is influenced by the semantic content of the scenes. Here, we tested the relative influence of local meaning, controlling for physical salience and center bias, on the eye gaze of 4- to 12-month-old infants (N = 92) as they viewed natural scenes. Overall, infants were more likely to fixate scene regions rated as higher in meaning, indicating that, like adults, the semantic content, or local meaning, of scenes influences where they look. More importantly, the effect of meaning on infant attention increased with age, providing the first evidence for an age-related increase in the impact of local meaning on infants' eye movements while viewing natural scenes.

Learning modifies attention during bumblebee visual search

Abstract

The role of visual search during bee foraging is relatively understudied compared to the choices made by bees. As bees learn about rewards, we predicted that visual search would be modified to prioritise rewarding flowers. To test this, we ran an experiment testing how bee search differs in the initial and later part of training as they learn about flowers with either higher- or lower-quality rewards. We then ran an experiment to see how this prior training with reward influences their search on a subsequent task with different flowers. We used the time spent inspecting flowers as a measure of attention and found that learning increased attention to rewards and away from unrewarding flowers. Higher quality rewards led to decreased attention to non-flower regions, but lower quality rewards did not. Prior experience of lower rewards also led to more attention to higher rewards compared to unrewarding flowers and non-flower regions. Our results suggest that flowers would elicit differences in bee search behaviour depending on the sugar content of their nectar. They also demonstrate the utility of studying visual search and have important implications for understanding the pollination ecology of flowers with different qualities of reward.

Significance statement

Studies investigating how foraging bees learn about reward typically focus on the choices made by the bees. How bees deploy attention and visual search during foraging is less well studied. We analysed flight videos to characterise visual search as bees learn which flowers are rewarding. We found that learning increases the focus of bees on flower regions. We also found that the quality of the reward a flower offers influences how much bees search in non-flower areas. This means that a flower with lower reward attracts less focussed foraging compared to one with a higher reward. Since flowers do differ in floral reward, this has important implications for how focussed pollinators will be on different flowers. Our approach of looking at search behaviour and attention thus advances our understanding of the cognitive ecology of pollination.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00265-024-03432-z.

Strategies for highlighting items within visual scene displays to support augmentative and alternative communication access for those with physical impairments

PURPOSE

In contrast to the traditional grid-based display, visual scene displays (VSDs) offer a new paradigm for aided communication. For individuals who cannot select items from an AAC display by direct selection due to physical impairments, AAC access can be supported via methods such as item scanning. Item scanning sequentially highlights items on a display until the individual signals for selection. How items are highlighted or scanned for AAC access can impact performance outcomes. Further, the effectiveness of a VSD interface may be enhanced through consultation with experts in visual communication. Therefore, to support AAC access for those with physical impairments, the aim of this study was to evaluate the perspectives of experts in visual communication regarding effective methods for highlighting VSD elements.

METHODS

Thirteen participants with expertise related to visual communication (e.g., photographers, artists) completed semi-structured interviews regarding techniques for item highlighting.

RESULTS

Study findings identified four main themes to inform how AAC items may be highlighted or scanned, including (1) use of contrast related to light and dark, (2) use of contrast as it relates to colour, (3) outline highlighting, and (4) use of scale and motion.

CONCLUSION

By identifying how compositional techniques can be utilized to highlight VSD elements, study findings may inform current practice for scanning-based AAC access, along with other selection techniques where feedback or highlighting is used (e.g., eye-gaze, brain-computer interface). Further, avenues for just-in-time programming are discussed to support effective implementation for those with physical impairments.IMPLICATIONS FOR REHABILITATIONFindings identify multiple potential techniques to improve scanning through items in a photograph for individuals with severe motor impairments using alternative access strategies.Study findings inform current practice for scanning-based AAC access, along with other selection techniques where feedback or highlighting is used (e.g., eye-gaze, brain-computer interface).Avenues for just in time programming of AAC displays are discussed to decrease programming demands and support effective implementation of study findings.

Reading in the city: mobile eye-tracking and evaluation of text in an everyday setting

Reading is often regarded as a mundane aspect of everyday life. However, little is known about the natural reading experiences in daily activities. To fill this gap, this study presents two field studies (N = 39 and 26, respectively), where we describe how people explore visual environments and divide their attention toward text elements in highly ecological settings, i.e., urban street environments, using mobile eye-tracking glasses. Further, the attention toward the text elements (i.e., shop signs) as well as their memorability, measured via follow-up recognition test, were analysed in relation to their aesthetic quality, which is assumed to be key for attracting visual attention and memorability. Our results revealed that, within these urban streets, text elements were looked at most, and looking behaviour was strongly directed, especially toward shop signs, across both street contexts; however, aesthetic values were not correlated either with the most looked at signs or the viewing time for the signs. Aesthetic ratings did however have an effect on memorability, with signs rated higher being better recognised. The results will be discussed in terms aesthetic reading experiences and implications for future field studies.

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.

Working memory control predicts fixation duration in scene-viewing

When viewing scenes, observers differ in how long they linger at each fixation location and how far they move their eyes between fixations. What factors drive these differences in eye-movement behaviors? Previous work suggests individual differences in working memory capacity may influence fixation durations and saccade amplitudes. In the present study, participants (N = 98) performed two scene-viewing tasks, aesthetic judgment and memorization, while viewing 100 photographs of real-world scenes. Working memory capacity, working memory processing ability, and fluid intelligence were assessed with an operation span task, a memory updating task, and Raven's Advanced Progressive Matrices, respectively. Across participants, we found significant effects of task on both fixation durations and saccade amplitudes. At the level of each individual participant, we also found a significant relationship between memory updating task performance and participants' fixation duration distributions. However, we found no effect of fluid intelligence and no effect of working memory capacity on fixation duration or saccade amplitude distributions, inconsistent with previous findings. These results suggest that the ability to flexibly maintain and update working memory is strongly related to fixation duration behavior.

The influence of scene tilt on saccade directions is amplitude dependent

When exploring a visual scene, humans make more saccades in the horizontal direction than any other direction. While many have shown that the horizontal saccade bias rotates in response to scene tilt, it is unclear whether this effect depends on saccade amplitude. We addressed this question by examining the effect of image tilt on the saccade direction distributions recorded during freely viewing natural scenes. Participants (n = 20) viewed scenes tilted at -30°, 0°, and 30°. Saccade distributions during free viewing rotated by an angle of 12.1° ± 6.7° (t(19) = 8.04, p < 0.001) in the direction of the image tilt. When we partitioned the saccades according to their amplitude we found that small amplitude saccades occurred most in the horizontal direction while large amplitude saccades were more oriented to the scene tilt (p < 0.001). To further study the characteristics of small saccades and how they are affected by scene tilt, we looked at the effect of image tilt on small fixational saccades made while fixating a central target amidst a larger scene and found that fixational saccade distributions did not rotate with scene tilt (-0.3° ±1.7° degrees; t(19) = -0.8, p = 0.39). These results suggest a combined effect of two reference frames in saccade generation: one egocentric reference frame that dominates for small saccades, biases them horizontally, and may be common for different tasks, and another allocentric reference frame that biases larger saccades along the orientation of an image during free viewing.

Recent Advances at the Interface of Neuroscience and Artificial Neural Networks

Biological neural networks adapt and learn in diverse behavioral contexts. Artificial neural networks (ANNs) have exploited biological properties to solve complex problems. However, despite their effectiveness for specific tasks, ANNs are yet to realize the flexibility and adaptability of biological cognition. This review highlights recent advances in computational and experimental research to advance our understanding of biological and artificial intelligence. In particular, we discuss critical mechanisms from the cellular, systems, and cognitive neuroscience fields that have contributed to refining the architecture and training algorithms of ANNs. Additionally, we discuss how recent work used ANNs to understand complex neuronal correlates of cognition and to process high throughput behavioral data.

Long-term memory and working memory compete and cooperate to guide attention

Multiple types of memory guide attention: Both long-term memory (LTM) and working memory (WM) effectively guide visual search. Furthermore, both types of memories can capture attention automatically, even when detrimental to performance. It is less clear, however, how LTM and WM cooperate or compete to guide attention in the same task. In a series of behavioral experiments, we show that LTM and WM reliably cooperate to guide attention: Visual search is faster when both memories cue attention to the same spatial location (relative to when only one memory can guide attention). LTM and WM competed to guide attention in more limited circumstances: Competition only occurred when these memories were in different dimensions - particularly when participants searched for a shape and held an accessory color in mind. Finally, we found no evidence for asymmetry in either cooperation or competition: There was no evidence that WM helped (or hindered) LTM-guided search more than the other way around. This lack of asymmetry was found despite differences in LTM-guided and WM-guided search overall, and differences in how two LTMs and two WMs compete or cooperate with each other to guide attention. This work suggests that, even if only one memory is currently task-relevant, WM and LTM can cooperate to guide attention; they can also compete when distracting features are salient enough. This work elucidates interactions between WM and LTM during attentional guidance, adding to the literature on costs and benefits to attention from multiple active memories.

Look at what I can do: Object affordances guide visual attention while speakers describe potential actions

As we act on the world around us, our eyes seek out objects we plan to interact with. A growing body of evidence suggests that overt visual attention selects objects in the environment that could be interacted with, even when the task precludes physical interaction. In previous work, objects that afford grasping interactions influenced attention when static scenes depicted reachable spaces, and attention was otherwise better explained by general informativeness. Because grasping is but one of many object interactions, previous work may have downplayed the influence of object affordances on attention. The current study investigated the relationship between overt visual attention and object affordances versus broadly construed semantic information in scenes as speakers describe or memorize scenes. In addition to meaning and grasp maps-which capture informativeness and grasping object affordances in scenes, respectively-we introduce interact maps, which capture affordances more broadly. In a mixed-effects analysis of 5 eyetracking experiments, we found that meaning predicted fixated locations in a general description task and during scene memorization. Grasp maps marginally predicted fixated locations during action description for scenes that depicted reachable spaces only. Interact maps predicted fixated regions in description experiments alone. Our findings suggest observers allocate attention to scene regions that could be readily interacted with when talking about the scene, while general informativeness preferentially guides attention when the task does not encourage careful consideration of objects in the scene. The current study suggests that the influence of object affordances on visual attention in scenes is mediated by task demands.

The polarized mind in context: Interdisciplinary approaches to the psychology of political polarization

Existing research into the psychological roots of political polarization centers around two main approaches: one studying cognitive traits that predict susceptibility to holding polarized beliefs and one studying contextual influences that spread and reinforce polarized attitudes. Although both accounts have made valuable progress, political polarization is neither a purely cognitive trait nor a contextual issue. We argue that a new approach aiming to uncover interactions between cognition and context will be fruitful for understanding how polarization arises. Furthermore, recent developments in neuroimaging methods can overcome long-standing issues of measurement and ecological validity to critically help identify in which psychological processing steps-e.g., attention, semantic understanding, emotion-polarization takes hold. This interdisciplinary research agenda can thereby provide new avenues for interventions against the political polarization that plagues democracies around the world. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Humans represent the precision and utility of information acquired across fixations

Our environment contains an abundance of objects which humans interact with daily, gathering visual information using sequences of eye-movements to choose which object is best-suited for a particular task. This process is not trivial, and requires a complex strategy where task affordance defines the search strategy, and the estimated precision of the visual information gathered from each object may be used to track perceptual confidence for object selection. This study addresses the fundamental problem of how such visual information is metacognitively represented and used for subsequent behaviour, and reveals a complex interplay between task affordance, visual information gathering, and metacogntive decision making. People fixate higher-utility objects, and most importantly retain metaknowledge about how much information they have gathered about these objects, which is used to guide perceptual report choices. These findings suggest that such metacognitive knowledge is important in situations where decisions are based on information acquired in a temporal sequence.

Semantic object-scene inconsistencies affect eye movements, but not in the way predicted by contextualized meaning maps

Semantic information is important in eye movement control. An important semantic influence on gaze guidance relates to object-scene relationships: objects that are semantically inconsistent with the scene attract more fixations than consistent objects. One interpretation of this effect is that fixations are driven toward inconsistent objects because they are semantically more informative. We tested this explanation using contextualized meaning maps, a method that is based on crowd-sourced ratings to quantify the spatial distribution of context-sensitive “meaning” in images. In Experiment 1, we compared gaze data and contextualized meaning maps for images, in which objects-scene consistency was manipulated. Observers fixated more on inconsistent versus consistent objects. However, contextualized meaning maps did not assign higher meaning to image regions that contained semantic inconsistencies. In Experiment 2, a large number of raters evaluated image-regions, which were deliberately selected for their content and expected meaningfulness. The results suggest that the same scene locations were experienced as slightly less meaningful when they contained inconsistent compared to consistent objects. In summary, we demonstrated that — in the context of our rating task — semantically inconsistent objects are experienced as less meaningful than their consistent counterparts and that contextualized meaning maps do not capture prototypical influences of image meaning on gaze guidance.

Meaning and expected surfaces combine to guide attention during visual search in scenes

How do spatial constraints and meaningful scene regions interact to control overt attention during visual search for objects in real-world scenes? To answer this question, we combined novel surface maps of the likely locations of target objects with maps of the spatial distribution of scene semantic content. The surface maps captured likely target surfaces as continuous probabilities. Meaning was represented by meaning maps highlighting the distribution of semantic content in local scene regions. Attention was indexed by eye movements during the search for target objects that varied in the likelihood they would appear on specific surfaces. The interaction between surface maps and meaning maps was analyzed to test whether fixations were directed to meaningful scene regions on target-related surfaces. Overall, meaningful scene regions were more likely to be fixated if they appeared on target-related surfaces than if they appeared on target-unrelated surfaces. These findings suggest that the visual system prioritizes meaningful scene regions on target-related surfaces during visual search in scenes.

What's in a Photograph? The Perspectives of Composition Experts on Factors Impacting Visual Scene Display Complexity for Augmentative and Alternative Communication and Strategies for Improving Visual Communication

Purpose Visual scene displays (VSDs) can support augmentative and alternative communication (AAC) success for children and adults with complex communication needs. Static VSDs incorporate contextual photographs that include meaningful events, places, and people. Although the processing of VSDs has been studied, their power as a medium to effectively convey meaning may benefit from the perspective of individuals who regularly engage in visual storytelling. The aim of this study was to evaluate the perspectives of individuals with expertise in photographic and/or artistic composition regarding factors contributing to VSD complexity and how to limit the time and effort required to apply principles of photographic composition. Method Semistructured interviews were completed with 13 participants with expertise in photographic and/or artistic composition. Results Four main themes were noted, including (a) factors increasing photographic image complexity and decreasing cohesion, (b) how complexity impacts the viewer, (c) composition strategies to decrease photographic image complexity and increase cohesion, and (d) strategies to support the quick application of composition strategies in a just-in-time setting. Findings both support and extend existing research regarding best practice for VSD design. Conclusions Findings provide an initial framework for understanding photographic image complexity and how it differs from drawn AAC symbols. Furthermore, findings outline a toolbox of composition principles that may help limit VSD complexity, along with providing recommendations for AAC development to support the quick application of compositional principles to limit burdens associated with capturing photographic images. Supplemental Material https://doi.org/10.23641/asha.15032700.

Deep saliency models learn low-, mid-, and high-level features to predict scene attention

Deep saliency models represent the current state-of-the-art for predicting where humans look in real-world scenes. However, for deep saliency models to inform cognitive theories of attention, we need to know how deep saliency models prioritize different scene features to predict where people look. Here we open the black box of three prominent deep saliency models (MSI-Net, DeepGaze II, and SAM-ResNet) using an approach that models the association between attention, deep saliency model output, and low-, mid-, and high-level scene features. Specifically, we measured the association between each deep saliency model and low-level image saliency, mid-level contour symmetry and junctions, and high-level meaning by applying a mixed effects modeling approach to a large eye movement dataset. We found that all three deep saliency models were most strongly associated with high-level and low-level features, but exhibited qualitatively different feature weightings and interaction patterns. These findings suggest that prominent deep saliency models are primarily learning image features associated with high-level scene meaning and low-level image saliency and highlight the importance of moving beyond simply benchmarking performance.

Developmental changes in natural scene viewing in infancy

We extend decades of research on infants' visual processing by examining their eye gaze during viewing of natural scenes. We examined the eye movements of a racially diverse group of 4- to 12-month-old infants (N = 54; 27 boys; 24 infants were White and not Hispanic, 30 infants were African American, Asian American, mixed race and/or Hispanic) as they viewed images selected from the MIT Saliency Benchmark Project. In general, across this age range infants' fixation distributions became more consistent and more adult-like, suggesting that infants' fixations in natural scenes become increasingly more systematic. Evaluation of infants' fixation patterns with saliency maps generated by different models of physical salience revealed that although over this age range there was an increase in the correlations between infants' fixations and saliency, the amount of variance accounted for by salience actually decreased. At the youngest age, the amount of variance accounted for by salience was very similar to the consistency between infants' fixations, suggesting that the systematicity in these youngest infants' fixations was explained by their attention to physically salient regions. By 12 months, in contrast, the consistency between infants was greater than the variance accounted for by salience, suggesting that the systematicity in older infants' fixations reflected more than their attention to physically salient regions. Together these results show that infants' fixations when viewing natural scenes becomes more systematic and predictable, and that predictability is due to their attention to features other than physical salience. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Knowledge guides attention to goal-relevant information in older adults

How does viewers’ knowledge guide their attention while they watch everyday events, how does it affect their memory, and does it change with age? Older adults have diminished episodic memory for everyday events, but intact semantic knowledge. Indeed, research suggests that older adults may rely on their semantic memory to offset impairments in episodic memory, and when relevant knowledge is lacking, older adults’ memory can suffer. Yet, the mechanism by which prior knowledge guides attentional selection when watching dynamic activity is unclear. To address this, we studied the influence of knowledge on attention and memory for everyday events in young and older adults by tracking their eyes while they watched videos. The videos depicted activities that older adults perform more frequently than young adults (balancing a checkbook, planting flowers) or activities that young adults perform more frequently than older adults (installing a printer, setting up a video game). Participants completed free recall, recognition, and order memory tests after each video. We found age-related memory deficits when older adults had little knowledge of the activities, but memory did not differ between age groups when older adults had relevant knowledge and experience with the activities. Critically, results showed that knowledge influenced where viewers fixated when watching the videos. Older adults fixated less goal-relevant information compared to young adults when watching young adult activities, but they fixated goal-relevant information similarly to young adults, when watching more older adult activities. Finally, results showed that fixating goal-relevant information predicted free recall of the everyday activities for both age groups. Thus, older adults may use relevant knowledge to more effectively infer the goals of actors, which guides their attention to goal-relevant actions, thus improving their episodic memory for everyday activities.

Spontaneous perception: a framework for task-free, self-paced perception

Flipping through social media feeds, viewing exhibitions in a museum, or walking through the botanical gardens, people consistently choose to engage with and disengage from visual content. Yet, in most laboratory settings, the visual stimuli, their presentation duration, and the task at hand are all controlled by the researcher. Such settings largely overlook the spontaneous nature of human visual experience, in which perception takes place independently from specific task constraints and its time course is determined by the observer as a self-governing agent. Currently, much remains unknown about how spontaneous perceptual experiences unfold in the brain. Are all perceptual categories extracted during spontaneous perception? Does spontaneous perception inherently involve volition? Is spontaneous perception segmented into discrete episodes? How do different neural networks interact over time during spontaneous perception? These questions are imperative to understand our conscious visual experience in daily life. In this article we propose a framework for spontaneous perception. We first define spontaneous perception as a task-free and self-paced experience. We propose that spontaneous perception is guided by four organizing principles that grant it temporal and spatial structures. These principles include coarse-to-fine processing, continuity and segmentation, agency and volition, and associative processing. We provide key suggestions illustrating how these principles may interact with one another in guiding the multifaceted experience of spontaneous perception. We point to testable predictions derived from this framework, including (but not limited to) the roles of the default-mode network and slow cortical potentials in underlying spontaneous perception. We conclude by suggesting several outstanding questions for future research, extending the relevance of this framework to consciousness and spontaneous brain activity. In conclusion, the spontaneous perception framework proposed herein integrates components in human perception and cognition, which have been traditionally studied in isolation, and opens the door to understand how visual perception unfolds in its most natural context.

Looking for Semantic Similarity: What a Vector-Space Model of Semantics Can Tell Us About Attention in Real-World Scenes

The visual world contains more information than we can perceive and understand in any given moment. Therefore, we must prioritize important scene regions for detailed analysis. Semantic knowledge gained through experience is theorized to play a central role in determining attentional priority in real-world scenes but is poorly understood. Here, we examined the relationship between object semantics and attention by combining a vector-space model of semantics with eye movements in scenes. In this approach, the vector-space semantic model served as the basis for a concept map, an index of the spatial distribution of the semantic similarity of objects across a given scene. The results showed a strong positive relationship between the semantic similarity of a scene region and viewers' focus of attention; specifically, greater attention was given to more semantically related scene regions. We conclude that object semantics play a critical role in guiding attention through real-world scenes.

Neural Correlates of Subsequent Memory-Related Gaze Reinstatement

Mounting evidence linking gaze reinstatement-the recapitulation of encoding-related gaze patterns during retrieval-to behavioral measures of memory suggests that eye movements play an important role in mnemonic processing. Yet, the nature of the gaze scanpath, including its informational content and neural correlates, has remained in question. In this study, we examined eye movement and neural data from a recognition memory task to further elucidate the behavioral and neural bases of functional gaze reinstatement. Consistent with previous work, gaze reinstatement during retrieval of freely viewed scene images was greater than chance and predictive of recognition memory performance. Gaze reinstatement was also associated with viewing of informationally salient image regions at encoding, suggesting that scanpaths may encode and contain high-level scene content. At the brain level, gaze reinstatement was predicted by encoding-related activity in the occipital pole and BG, neural regions associated with visual processing and oculomotor control. Finally, cross-voxel brain pattern similarity analysis revealed overlapping subsequent memory and subsequent gaze reinstatement modulation effects in the parahippocampal place area and hippocampus, in addition to the occipital pole and BG. Together, these findings suggest that encoding-related activity in brain regions associated with scene processing, oculomotor control, and memory supports the formation, and subsequent recapitulation, of functional scanpaths. More broadly, these findings lend support to scanpath theory's assertion that eye movements both encode, and are themselves embedded in, mnemonic representations.

Memory for spatio-temporal contextual details during the retrieval of naturalistic episodes

Episodic memory entails the storage of events together with their spatio-temporal context and retrieval comprises the subjective experience of a link between the person who remembers and the episode itself. We used an encoding procedure with mobile-phones to generate experimentally-controlled episodes in the real world: object-images were sent to the participants' phone, with encoding durations up to 3 weeks. In other groups of participants, the same objects were encoded during the exploration of a virtual town (45 min) or using a standard laboratory paradigm, with pairs of object/place-images presented in a sequence of unrelated trials (15 min). At retrieval, we tested subjective memory for the objects (remember/familiar) and memory for the context (place and time). We found that accurate and confident context-memory increased the likelihood of "remember" responses, in all encoding contexts. We also tested the participants' ability to judge the temporal-order of the encoded episodes. Using a model of temporal similarity, we demonstrate scale-invariant properties of order-retrieval, but also highlight the contribution of non-chronological factors. We conclude that the mechanisms governing episodic memory retrieval can operate across a wide range of spatio-temporal contexts and that the multi-dimensional nature of the episodic traces contributes to the subjective experience of retrieval.

Does task-irrelevant music affect gaze allocation during real-world scene viewing?

Gaze control manifests from a dynamic integration of visual and auditory information, with sound providing important cues for how a viewer should behave. Some past research suggests that music, even if entirely irrelevant to the current task demands, may also sway the timing and frequency of fixations. The current work sought to further assess this idea as well as investigate whether task-irrelevant music could also impact how gaze is spatially allocated. In preparation for a later memory test, participants studied pictures of urban scenes in silence or while simultaneously listening to one of two types of music. Eye tracking was recorded, and nine gaze behaviors were measured to characterize the temporal and spatial aspects of gaze control. Findings showed that while these gaze behaviors changed over the course of viewing, music had no impact. Participants in the music conditions, however, did show better memory performance than those who studied in silence. These findings are discussed within theories of multimodal gaze control.

Overt attentional correlates of memorability of scene images and their relationships to scene semantics

Computer vision-based research has shown that scene semantics (e.g., presence of meaningful objects in a scene) can predict memorability of scene images. Here, we investigated whether and to what extent overt attentional correlates, such as fixation map consistency (also called inter-observer congruency of fixation maps) and fixation counts, mediate the relationship between scene semantics and scene memorability. First, we confirmed that the higher the fixation map consistency of a scene, the higher its memorability. Moreover, both fixation map consistency and its correlation to scene memorability were the highest in the first 2 seconds of viewing, suggesting that meaningful scene features that contribute to producing more consistent fixation maps early in viewing, such as faces and humans, may also be important for scene encoding. Second, we found that the relationship between scene semantics and scene memorability was partially (but not fully) mediated by fixation map consistency and fixation counts, separately as well as together. Third, we found that fixation map consistency, fixation counts, and scene semantics significantly and additively contributed to scene memorability. Together, these results suggest that eye-tracking measurements can complement computer vision-based algorithms and improve overall scene memorability prediction.

There is no evidence that meaning maps capture semantic information relevant to gaze guidance: Reply to Henderson, Hayes, Peacock, and Rehrig (2021)

The concerns raised by Henderson, Hayes, Peacock, and Rehrig (2021) are based on misconceptions of our work. We show that Meaning Maps (MMs) do not predict gaze guidance better than a state-of-the-art saliency model that is based on semantically-neutral, high-level features. We argue that there is therefore no evidence to date that MMs index anything beyond these features. Furthermore, we show that although alterations in meaning cause changes in gaze guidance, MMs fail to capture these alterations. We agree that semantic information is important in the guidance of eye-movements, but the contribution of MMs for understanding its role remains elusive.

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.

Saliency Prediction in the Deep Learning Era: Successes and Limitations

Visual saliency models have enjoyed a big leap in performance in recent years, thanks to advances in deep learning and large scale annotated data. Despite enormous effort and huge breakthroughs, however, models still fall short in reaching human-level accuracy. In this work, I explore the landscape of the field emphasizing on new deep saliency models, benchmarks, and datasets. A large number of image and video saliency models are reviewed and compared over two image benchmarks and two large scale video datasets. Further, I identify factors that contribute to the gap between models and humans and discuss the remaining issues that need to be addressed to build the next generation of more powerful saliency models. Some specific questions that are addressed include: in what ways current models fail, how to remedy them, what can be learned from cognitive studies of attention, how explicit saliency judgments relate to fixations, how to conduct fair model comparison, and what are the emerging applications of saliency models.

The spatial distribution of attention predicts familiarity strength during encoding and retrieval

The memories we form are determined by what we attend to, and conversely, what we attend to is influenced by our memory for past experiences. Although we know that shifts of attention via eye movements are related to memory during encoding and retrieval, the role of specific memory processes in this relationship is unclear. There is evidence that attention may be especially important for some forms of memory (i.e., conscious recollection), and less so for others (i.e., familiarity-based recognition and unconscious influences of memory), but results are conflicting with respect to both the memory processes and eye movement patterns involved. To address this, we used a confidence-based method of isolating eye movement indices of spatial attention that are related to different memory processes (i.e., recollection, familiarity strength, and unconscious memory) during encoding and retrieval of real-world scenes. We also developed a new method of measuring the dispersion of eye movements, which proved to be more sensitive to memory processing than previously used measures. Specifically, in 2 studies, we found that familiarity strength-that is, changes in subjective reports of memory confidence-increased with (a) more dispersed patterns of viewing during encoding, (b) less dispersed viewing during retrieval, and (c) greater overlap in regions viewed between encoding and retrieval (i.e., resampling). Recollection was also related to these eye movements in a similar manner, though the associations with recollection were less consistent across experiments. Furthermore, we found no evidence for effects related to unconscious influences of memory. These findings indicate that attentional processes during viewing may not preferentially relate to recollection, and that the spatial distribution of eye movements is directly related to familiarity-based memory during encoding and retrieval. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Meaning maps and saliency models based on deep convolutional neural networks are insensitive to image meaning when predicting human fixations

Eye movements are vital for human vision, and it is therefore important to understand how observers decide where to look. Meaning maps (MMs), a technique to capture the distribution of semantic information across an image, have recently been proposed to support the hypothesis that meaning rather than image features guides human gaze. MMs have the potential to be an important tool far beyond eye-movements research. Here, we examine central assumptions underlying MMs. First, we compared the performance of MMs in predicting fixations to saliency models, showing that DeepGaze II - a deep neural network trained to predict fixations based on high-level features rather than meaning - outperforms MMs. Second, we show that whereas human observers respond to changes in meaning induced by manipulating object-context relationships, MMs and DeepGaze II do not. Together, these findings challenge central assumptions underlying the use of MMs to measure the distribution of meaning in images.

Neural Correlates of Fixated Low- and High-level Scene Properties during Active Scene Viewing

During real-world scene perception, viewers actively direct their attention through a scene in a controlled sequence of eye fixations. During each fixation, local scene properties are attended, analyzed, and interpreted. What is the relationship between fixated scene properties and neural activity in the visual cortex? Participants inspected photographs of real-world scenes in an MRI scanner while their eye movements were recorded. Fixation-related fMRI was used to measure activation as a function of lower- and higher-level scene properties at fixation, operationalized as edge density and meaning maps, respectively. We found that edge density at fixation was most associated with activation in early visual areas, whereas semantic content at fixation was most associated with activation along the ventral visual stream including core object and scene-selective areas (lateral occipital complex, parahippocampal place area, occipital place area, and retrosplenial cortex). The observed activation from semantic content was not accounted for by differences in edge density. The results are consistent with active vision models in which fixation gates detailed visual analysis for fixated scene regions, and this gating influences both lower and higher levels of scene analysis.

Gravitational models explain shifts on human visual attention

Visual attention refers to the human brain’s ability to select relevant sensory information for preferential processing, improving performance in visual and cognitive tasks. It proceeds in two phases. One in which visual feature maps are acquired and processed in parallel. Another where the information from these maps is merged in order to select a single location to be attended for further and more complex computations and reasoning. Its computational description is challenging, especially if the temporal dynamics of the process are taken into account. Numerous methods to estimate saliency have been proposed in the last 3 decades. They achieve almost perfect performance in estimating saliency at the pixel level, but the way they generate shifts in visual attention fully depends on winner-take-all (WTA) circuitry. WTA is implemented by the biological hardware in order to select a location with maximum saliency, towards which to direct overt attention. In this paper we propose a gravitational model to describe the attentional shifts. Every single feature acts as an attractor and the shifts are the result of the joint effects of the attractors. In the current framework, the assumption of a single, centralized saliency map is no longer necessary, though still plausible. Quantitative results on two large image datasets show that this model predicts shifts more accurately than winner-take-all.

When scenes speak louder than words: Verbal encoding does not mediate the relationship between scene meaning and visual attention

The complexity of the visual world requires that we constrain visual attention and prioritize some regions of the scene for attention over others. The current study investigated whether verbal encoding processes influence how attention is allocated in scenes. Specifically, we asked whether the advantage of scene meaning over image salience in attentional guidance is modulated by verbal encoding, given that we often use language to process information. In two experiments, 60 subjects studied scenes (N1 = 30 and N2 = 60) for 12 s each in preparation for a scene-recognition task. Half of the time, subjects engaged in a secondary articulatory suppression task concurrent with scene viewing. Meaning and saliency maps were quantified for each of the experimental scenes. In both experiments, we found that meaning explained more of the variance in visual attention than image salience did, particularly when we controlled for the overlap between meaning and salience, with and without the suppression task. Based on these results, verbal encoding processes do not appear to modulate the relationship between scene meaning and visual attention. Our findings suggest that semantic information in the scene steers the attentional ship, consistent with cognitive guidance theory.

Visual Search: How Do We Find What We Are Looking For?

In visual search tasks, observers look for targets among distractors. In the lab, this often takes the form of multiple searches for a simple shape that may or may not be present among other items scattered at random on a computer screen (e.g., Find a red T among other letters that are either black or red.). In the real world, observers may search for multiple classes of target in complex scenes that occur only once (e.g., As I emerge from the subway, can I find lunch, my friend, and a street sign in the scene before me?). This article reviews work on how search is guided intelligently. I ask how serial and parallel processes collaborate in visual search, describe the distinction between search templates in working memory and target templates in long-term memory, and consider how searches are terminated.

Where the eyes wander: The relationship between mind wandering and fixation allocation to visually salient and semantically informative static scene content

Vision is crucial for many everyday activities, but the mind is not always focused on what the eyes see. Mind wandering occurs frequently and is associated with attenuated visual and cognitive processing of external information. Corresponding changes in gaze behavior—namely, fewer, longer, and more dispersed fixations—suggest a shift in how the visual system samples external information. Using three computational models of visual salience and two innovative approaches for measuring semantic informativeness, the current work assessed whether these changes reflect how the visual system prioritizes visually salient and semantically informative scene content, two major determinants in most theoretical frameworks and computational models of gaze control. Findings showed that, in a static scene viewing task, fixations were allocated to scene content that was more visually salient 10 seconds prior to probe-caught, self-reported mind wandering compared to self-reported attentive viewing. The relationship between mind wandering and semantic content was more equivocal, with weaker evidence that fixations are more likely to fall on locally informative scene regions. This indicates that the visual system is still able to discriminate visually salient and semantically informative scene content during mind wandering and may fixate on such information more frequently than during attentive viewing. Theoretical implications are discussed in light of these findings.

Where the action could be: Speakers look at graspable objects and meaningful scene regions when describing potential actions

The world is visually complex, yet we can efficiently describe it by extracting the information that is most relevant to convey. How do the properties of real-world scenes help us decide where to look and what to say? Image salience has been the dominant explanation for what drives visual attention and production as we describe displays, but new evidence shows scene meaning predicts attention better than image salience. Here we investigated the relevance of one aspect of meaning, graspability (the grasping interactions objects in the scene afford), given that affordances have been implicated in both visual and linguistic processing. We quantified image salience, meaning, and graspability for real-world scenes. In 3 eyetracking experiments, native English speakers described possible actions that could be carried out in a scene. We hypothesized that graspability would preferentially guide attention due to its task-relevance. In 2 experiments using stimuli from a previous study, meaning explained visual attention better than graspability or salience did, and graspability explained attention better than salience. In a third experiment we quantified image salience, meaning, graspability, and reach-weighted graspability for scenes that depicted reachable spaces containing graspable objects. Graspability and meaning explained attention equally well in the third experiment, and both explained attention better than salience. We conclude that speakers use object graspability to allocate attention to plan descriptions when scenes depict graspable objects within reach, and otherwise rely more on general meaning. The results shed light on what aspects of meaning guide attention during scene viewing in language production tasks. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Active vision in immersive, 360° real-world environments

How do we construct a sense of place in a real-world environment? Real-world environments are actively explored via saccades, head turns, and body movements. Yet, little is known about how humans process real-world scene information during active viewing conditions. Here, we exploited recent developments in virtual reality (VR) and in-headset eye-tracking to test the impact of active vs. passive viewing conditions on gaze behavior while participants explored novel, real-world, 360° scenes. In one condition, participants actively explored 360° photospheres from a first-person perspective via self-directed motion (saccades and head turns). In another condition, photospheres were passively displayed to participants while they were head-restricted. We found that, relative to passive viewers, active viewers displayed increased attention to semantically meaningful scene regions, suggesting more exploratory, information-seeking gaze behavior. We also observed signatures of exploratory behavior in eye movements, such as quicker, more entropic fixations during active as compared with passive viewing conditions. These results show that active viewing influences every aspect of gaze behavior, from the way we move our eyes to what we choose to attend to. Moreover, these results offer key benchmark measurements of gaze behavior in 360°, naturalistic environments.

Eye spy a liar: assessing the utility of eye fixations and confidence judgments for detecting concealed recognition of faces, scenes and objects

BACKGROUND

In criminal investigations, uncooperative witnesses might deny knowing a perpetrator, the location of a murder scene or knowledge of a weapon. We sought to identify markers of recognition in eye fixations and confidence judgments whilst participants told the truth and lied about recognising faces (Experiment 1) and scenes and objects (Experiment 2) that varied in familiarity. To detect recognition we calculated effect size differences in markers of recognition between familiar and unfamiliar items that varied in familiarity (personally familiar, newly learned).

RESULTS

In Experiment 1, recognition of personally familiar faces was reliably detected across multiple fixation markers (e.g. fewer fixations, fewer interest areas viewed, fewer return fixations) during honest and concealed recognition. In Experiment 2, recognition of personally familiar non-face items (scenes and objects) was detected solely by fewer fixations during honest and concealed recognition; differences in other fixation measures were not consistent. In both experiments, fewer fixations exposed concealed recognition of newly learned faces, scenes and objects, but the same pattern was not observed during honest recognition. Confidence ratings were higher for recognition of personally familiar faces than for unfamiliar faces.

CONCLUSIONS

Robust memories of personally familiar faces were detected in patterns of fixations and confidence ratings, irrespective of task demands required to conceal recognition. Crucially, we demonstrate that newly learned faces should not be used as a proxy for real-world familiarity, and that conclusions should not be generalised across different types of familiarity or stimulus class.

Center Bias Does Not Account for the Advantage of Meaning Over Salience in Attentional Guidance During Scene Viewing

Studies assessing the relationship between high-level meaning and low-level image salience on real-world attention have shown that meaning better predicts eye movements than image salience. However, it is not yet clear whether the advantage of meaning over salience is a general phenomenon or whether it is related to center bias: the tendency for viewers to fixate scene centers. Previous meaning mapping studies have shown meaning predicts eye movements beyond center bias whereas saliency does not. However, these past findings were correlational or post hoc in nature. Therefore, to causally test whether meaning predicts eye movements beyond center bias, we used an established paradigm to reduce center bias in free viewing: moving the initial fixation position away from the center and delaying the first saccade. We compared the ability of meaning maps and image salience maps to account for the spatial distribution of fixations with reduced center bias. We found that meaning continued to explain both overall and early attention significantly better than image salience even when center bias was reduced by manipulation. In addition, although both meaning and image salience capture scene-specific information, image salience is driven by significantly greater scene-independent center bias in viewing than meaning. In total, the present findings indicate that the strong association of attention with meaning is not due to center bias.

Why do we retrace our visual steps? Semantic and episodic memory in gaze reinstatement

When we look at repeated scenes, we tend to visit similar regions each time—a phenomenon known as resampling. Resampling has long been attributed to episodic memory, but the relationship between resampling and episodic memory has recently been found to be less consistent than assumed. A possibility that has yet to be fully considered is that factors unrelated to episodic memory may generate resampling: for example, other factors such as semantic memory and visual salience that are consistently present each time an image is viewed and are independent of specific prior viewing instances. We addressed this possibility by tracking participants’ eyes during scene viewing to examine how semantic memory, indexed by the semantic informativeness of scene regions (i.e., meaning), is involved in resampling. We found that viewing more meaningful regions predicted resampling, as did episodic familiarity strength. Furthermore, we found that meaning interacted with familiarity strength to predict resampling. Specifically, the effect of meaning on resampling was attenuated in the presence of strong episodic memory, and vice versa. These results suggest that episodic and semantic memory are each involved in resampling behavior and are in competition rather than synergistically increasing resampling. More generally, this suggests that episodic and semantic memory may compete to guide attention.

Implicitly and explicitly encoded features can guide attention in free viewing

It is well known that priming, probably by the contents of working memory, can influence subsequent visual task performance. How ubiquitous is this effect? Can incidental exposure to visual stimuli influence the deployment of attention when there is no explicit visual task? Results of two experiments show that a preceding stimulus can influence free-viewing eye movements. A simple change detection task was used as the cover task. The initial memory display was the priming display, while subsequent filler display constituted the free-viewing display of our interest. In Experiment 1, subjects were asked to memorize the number of items in the priming display. Subjects were not explicitly instructed to attend to features, but these might still be implicitly encoded. In Experiment 2, a more complex change detection task required subjects to memorize the number, color, and shape of priming items. Here, prime features were attended and, presumably, explicitly encoded. We were interested to know whether incidentally or explicitly encoded features of prime items would influence attention distribution in the filler display. In both experiments, items sharing color and shape with the prime were attended more often than predicted by chance. Items sharing neither color nor shape were attended less often. Items sharing either color or shape (not both) could also attract attention showing that the priming need not be based on a bound representation of the primed item. Effects were stronger in Experiment 2. No intention or top-down control appears to be needed to produce this priming.

Eye Movements in Real-World Scene Photographs: General Characteristics and Effects of Viewing Task

The present study examines eye movement behavior in real-world scenes with a large (N = 100) sample. We report baseline measures of eye movement behavior in our sample, including mean fixation duration, saccade amplitude, and initial saccade latency. We also characterize how eye movement behaviors change over the course of a 12 s trial. These baseline measures will be of use to future work studying eye movement behavior in scenes in a variety of literatures. We also examine effects of viewing task on when and where the eyes move in real-world scenes: participants engaged in a memorization and an aesthetic judgment task while viewing 100 scenes. While we find no difference at the mean-level between the two tasks, temporal- and distribution-level analyses reveal significant task-driven differences in eye movement behavior.

Fixation-pattern similarity analysis reveals adaptive changes in face-viewing strategies following aversive learning

Animals can effortlessly adapt their behavior by generalizing from past aversive experiences, allowing to avoid harm in novel situations. We studied how visual information was sampled by eye-movements during this process called fear generalization, using faces organized along a circular two-dimensional perceptual continuum. During learning, one face was conditioned to predict a harmful event, whereas the most dissimilar face stayed neutral. This introduced an adversity gradient along one specific dimension, while the other, unspecific dimension was defined solely by perceptual similarity. Aversive learning changed scanning patterns selectively along the adversity-related dimension, but not the orthogonal dimension. This effect was mainly located within the eye region of faces. Our results provide evidence for adaptive changes in viewing strategies of faces following aversive learning. This is compatible with the view that these changes serve to sample information in a way that allows discriminating between safe and adverse for a better threat prediction.

What is a preattentive feature?

The concept of a preattentive feature has been central to vision and attention research for about half a century. A preattentive feature is a feature that guides attention in visual search and that cannot be decomposed into simpler features. While that definition seems straightforward, there is no simple diagnostic test that infallibly identifies a preattentive feature. This paper briefly reviews the criteria that have been proposed and illustrates some of the difficulties of definition.