Spatial Contextual Cueing Research Articles

The effect of task-irrelevant objects in spatial contextual cueing

During visual search, the spatial configuration of the stimuli can be learned when the same displays are presented repeatedly, thereby guiding attention more efficiently to the target location (contextual cueing effect). This study investigated how the presence of a task-irrelevant object influences the contextual cueing effect. Experiment 1 used a standard T/L search task with “old” display configurations presented repeatedly among “new” displays. A green-filled square appeared at unoccupied locations within the search display. The results showed that the typical contextual cueing effect was strongly reduced when a square was added to the display. In Experiment 2, the contextual cueing effect was reinstated by simply including trials where the square could appear at an occupied location (i.e., underneath the search stimuli). Experiment 3 replicated the previous experiment, showing that the restored contextual cueing effect did not depend on whether the square was actually overlapping with a stimulus or not. The final two experiments introduced a display change in the last epoch. The results showed that the square does not only hinder the acquisition of contextual information but also its manifestation. These findings are discussed in terms of an account where effective contextual learning depends on whether the square is perceived as part of the search display or as part of the display background.

Spatial contextual cues that help predict how a target will accelerate can be used to guide interception.

Objects in one's environment do not always move at a constant velocity but often accelerate or decelerate. People are very poor at visually judging acceleration and normally make systematic errors when trying to intercept accelerating objects. If the acceleration is perpendicular to the direction of motion, it gives rise to a curved path. Can spatial contextual cues help one predict such accelerations and thereby help interception? To answer this question, we asked participants to hit a target that moved as if it were attached to a rolling disk, like a valve (target) on a bicycle wheel (disk) moves when cycling: constantly accelerating toward the wheel's center. On half the trials, the disk was visible such that participants could use the spatial relations between the target and the rolling disk to guide their interception. On the other half, the disk was not visible, so participants had no help in predicting the target's complicated pattern of accelerations and decelerations. Importantly, the target's path was the same in both cases. Participants hit more targets when the disk was visible than when it was invisible, even when using a strategy that can compensate for neglecting acceleration. We conclude that spatial contextual cues that help predict the target's accelerations can help intercept it.

Mechanisms of spatial contextual cueing in younger and older adults.

The contextual cueing effect is the phenomenon observed when response time (RT) becomes faster in visual search in repeated context compared with a new one. In the present study, we explored whether the mechanisms involved in the effect are age dependent. We investigated it in younger (N = 20, 12 women, 21.2 ± 1.75 years) and older (N = 19, nine women, 67.05 ± 3.94 years) adults. We found a faster target identification in the repeated configurations with similar magnitude in the two age groups, which indicates that this contextual cueing effect remained intact even in the older participants. To shed light on the underlying mechanisms, we measured and compared the amplitude of three event-related potentials: N2pc, P3, and response-locked LRP. In the younger group, the larger contextual cueing effect (novel-minus-repeated RT difference) correlated positively with a larger difference in amplitude for repeated compared with novel configurations for both the N2pc and the P3 components, but there was no correlation with the response-locked lateralized readiness potential (rLRP) amplitude difference. However, in the older group, only the rLRP amplitude difference between novel and repeated configurations showed an enhancement with larger contextual cueing. These results suggest that different mechanisms are responsible for the contextual effect in the two age groups. It has both an early and an intermediate locus in younger adults: effective attentional allocation and successful stimulus categorization, or decision-making confidence are involved; while in older adults, a late locus was identified: a more efficient response organization led to a faster reaction.

Incorporating multi-stage spatial visual cues and active localization offset for pancreas segmentation

Accurately segmenting pancreas or pancreatic tumor from limited computed tomography (CT) scans plays an essential role in making a precise diagnosis and planning the surgical procedure for clinicians. Although deep convolutional neural networks (DCNNs) have greatly advanced in automatic organ segmentation, there are still many challenges in solving the pancreas segmentation problem with small region and complex background. Many researchers have developed a coarse-to-fine scheme, which employ prediction from the coarse stage as a smaller input region for the fine stage. Despite this scheme effectiveness, most existing approaches handle two stages individually, and fail to identify the reliability of coarse stage predictions. In this work, we present a novel coarse-to-fine framework based on spatial contextual cues and active localization offset. The novelty lies in carefully designed two modules: Spacial Visual Cues Fusion (SVCF) and Active Localization OffseT (ALOT). The SVCF combines the correlations between all pixels in an image to optimize the rough and uncertain pixel prediction at the coarse stage, while ALOT dynamically adjusts the localization as the coarse stage iteration. These two modules work together to optimize the coarse stage results and provide high-quality input for the fine stage, thereby achieving inspiring target segmentation. Empirical results on NIH pancreas segmentation and MSD pancreatic tumor segmentation dataset show that our framework yields state-of-the-art results. The code will make available at https://github.com/PinkGhost0812/SANet.

Cascaded acquisition of spatial contextual cueing

Spatial contextual cueing refers to the facilitation of visual search when invariant spatial configurations of the target and distractors are learned. Using the instance theory of automatization and the reverse hierarchy theory of visual perceptual learning, this study explores the acquisition of spatial contextual cueing. The findings support the reverse hierarchy theory, which predicts that the acquisition of spatial contextual cueing progresses in an easy-to-difficult cascading manner. However, these findings are inconsistent with instance theory, which predicts that the acquisition of spatial contextual cueing in easy-half-repeated trials would keep pace with that in difficult-half-repeated trials. This study concludes that compared with instance theory, reverse hierarchy theory more plausibly explains the acquisition of spatial contextual cueing.

Boosting Night-Time Scene Parsing With Learnable Frequency.

Night-Time Scene Parsing (NTSP) is essential to many vision applications, especially for autonomous driving. Most of the existing methods are proposed for day-time scene parsing. They rely on modeling pixel intensity-based spatial contextual cues under even illumination. Hence, these methods do not perform well in night-time scenes as such spatial contextual cues are buried in the over-/under-exposed regions in night-time scenes. In this paper, we first conduct an image frequency-based statistical experiment to interpret the day-time and night-time scene discrepancies. We find that image frequency distributions differ significantly between day-time and night-time scenes, and understanding such frequency distributions is critical to NTSP problem. Based on this, we propose to exploit the image frequency distributions for night-time scene parsing. First, we propose a Learnable Frequency Encoder (LFE) to model the relationship between different frequency coefficients to measure all frequency components dynamically. Second, we propose a Spatial Frequency Fusion module (SFF) that fuses both spatial and frequency information to guide the extraction of spatial context features. Extensive experiments show that our method performs favorably against the state-of-the-art methods on the NightCity, NightCity+ and BDD100K-night datasets. In addition, we demonstrate that our method can be applied to existing day-time scene parsing methods and boost their performance on night-time scenes. The code is available at https://github.com/wangsen99/FDLNet.

Effects of tDCS on visual statistical learning

Visual statistical learning describes the encoding of structure in sensory input, and it has important consequences for cognition and behaviour. Higher-order brain regions in the prefrontal and posterior parietal cortices have been associated with statistical learning behaviours. Yet causal evidence of a cortical contribution remains limited. In a recent study, the modulation of cortical activity by transcranial direct current stimulation (tDCS) disrupted statistical learning in a spatial contextual cueing phenomenon; supporting a cortical role. Here, we examined whether the same tDCS protocol would influence statistical learning assessed by the Visual Statistical Learning phenomenon (i.e., Fiser and Aslin, 2001), which uses identity-based regularities while controlling for spatial location. In Experiment 1, we employed the popular exposure-test design to tap the learning of structure after passive viewing. Using a large sample (N = 150), we found no effect of the tDCS protocol when compared to a sham control nor to an active control region. In Experiment 2 (N = 80), we developed an online task that was sensitive to the timecourse of learning. Under these task conditions, we did observe a stimulation effect on learning, consistent with the previous work. The way tDCS affected learning appeared to be task-specific; expediting statistical learning in this case. Together with the existing evidence, these findings support the hypothesis that cortical areas are involved in the visual statistical learning process, and suggest the mechanisms of cortical involvement may be task-dependent and dynamic across time.

The Effect of Visual Features of Search Stimuli on Learning of Spatial Contextual Cueing

The Effect of Visual Features of Search Stimuli on Learning of Spatial Contextual Cueing

Not scene learning, but attentional processing is superior in team sport athletes and action video game players.

We tested if high-level athletes or action video game players have superior context learning skills. Incidental context learning was tested in a spatial contextual cueing paradigm. We found comparable contextual cueing of visual search in repeated displays in high-level amateur handball players, dedicated action video game players and normal controls. In contrast, both handball players and action video game players showed faster search than controls, measured as search time per display item, independent of display repetition. Thus, our data do not indicate superior context learning skills in athletes or action video game players. Rather, both groups showed more efficient visual search in abstract displays that were not related to sport-specific situations.

Spatial Contextual Cueing, Assessed in a Computerized Task, Is Not a Limiting Factor for Expert Performance in the Domain of Team Sports or Action Video Game Playing

In two reaction time experiments, we investigated if handball and action video game players show improved implicit learning of repeated spatial configurations for efficient search guidance in comparison to a control group without sport or video game proficiency. To this end, we used both a sport-specific pseudo 3-D contextual cueing task and the original contextual cueing paradigm (Chun and Jiang 36, 28-71, 1998). In this visual search paradigm, a target element has to be searched in a distractor-filled display. A typical block of trials consisted of one half of displays that were repeatedly presented in subsequent blocks, while the other half of displays was always randomly generated. In numerous studies with this paradigm, it has been found that search becomes more efficient in repeated displays, even though participants are often unaware of these repetitions (Chun 4, 170-178, 2000). Contextual cueing was present in all groups. Thus, all groups showed incidental learning of repeated displays. Contrary to our hypothesis, handball and action video game players did not differ in the strength of contextual cueing from the control group, although these groups had overall faster search times in the sport-specific displays of experiment 1. To conclude, our data yield no evidence for superior context-learning skills in athletes or action video game players.

An individual difference examination of the relationship between spatial working memory abilities and contextual cueing.

An individual difference examination of the relationship between spatial working memory abilities and contextual cueing.

High-Resolution Image Classification Integrating Spectral-Spatial-Location Cues by Conditional Random Fields

With the increase in the availability of high-resolution remote sensing imagery, classification is becoming an increasingly useful technique for providing a large area of detailed land-cover information by the use of these high-resolution images. High-resolution images have the characteristics of abundant geometric and detail information, which are beneficial to detailed classification. In order to make full use of these characteristics, a classification algorithm based on conditional random fields (CRFs) is presented in this paper. The proposed algorithm integrates spectral, spatial contextual, and spatial location cues by modeling the probabilistic potentials. The spectral cues modeled by the unary potentials can provide basic information for discriminating the various land-cover classes. The pairwise potentials consider the spatial contextual information by establishing the neighboring interactions between pixels to favor spatial smoothing. The spatial location cues are explicitly encoded in the higher order potentials. The higher order potentials consider the nonlocal range of the spatial location interactions between the target pixel and its nearest training samples. This can provide useful information for the classes that are easily confused with other land-cover types in the spectral appearance. The proposed algorithm integrates spectral, spatial contextual, and spatial location cues within a CRF framework to provide complementary information from varying perspectives, so that it can address the common problem of spectral variability in remote sensing images, which is directly reflected in the accuracy of each class and the average accuracy. The experimental results with three high-resolution images show the validity of the algorithm, compared with the other state-of-the-art classification algorithms.

Automatic non-parametric image parsing via hierarchical semantic voting based on sparse–dense reconstruction and spatial–contextual cues

Image parsing is vital for many high-level image understanding tasks. Although both parametric and non-parametric approaches have achieved remarkable success, many technical challenges still prevail for images containing things/objects with broad-coverage and high-variability, because it still lacks versatile and effective strategies to seamlessly integrate local–global features selection, contextual cues exploitation, spatial layout encoding, data-driven coherency exploration, and flexible accommodation of newly annotated labels. To ameliorate, this paper develops a novel automatic non-parametric image parsing method with advantages of both parametric and non-parametric methodologies by resorting to new modeling and inferring strategies. The originality of our new approach is to employ sparse–dense reconstruction as a latent learning model to conduct candidate-label probability analysis over multi-level local regions, and synchronously leverage context-specific local–global label confidence propagation and global semantic spatial–contextual cues to guide holistic scene parsing. Towards this goal, we devise several novel technical components to comprise a lightweight parsing framework, including local region representation integrating complementary features, anisotropic consistency propagation based on bi-harmonic distance metric, bottom-up label voting, semantic string generation of image-level spatial–contextual cues based on Hilbert space-filling curve, and co-occurrence priors analysis based on relaxed string matching algorithm, which collectively enable us to effectively combat the aforementioned obstinate problems. Moreover, we conduct comprehensive experiments on public benchmarks, and make extensive and quantitative evaluations with state-of-the-art methods, which demonstrate the advantages of our method in accuracy, versatility, flexibility, and efficiency.

Neural structures involved in visual search guidance by reward-enhanced contextual cueing of the target location

Spatial contextual cueing reflects an incidental form of learning that occurs when spatial distractor configurations are repeated in visual search displays. Recently, it was reported that the efficiency of contextual cueing can be modulated by reward. We replicated this behavioral finding and investigated its neural basis with fMRI. Reward value was associated with repeated displays in a learning session. The effect of reward value on context-guided visual search was assessed in a subsequent fMRI session without reward. Structures known to support explicit reward valuation, such as ventral frontomedial cortex and posterior cingulate cortex, were modulated by incidental reward learning. Contextual cueing, leading to more efficient search, went along with decreased activation in the visual search network. Retrosplenial cortex played a special role in that it showed both a main effect of reward and a reward×configuration interaction and may thereby be a central structure for the reward modulation of context-guided visual search.

Relationship of contextual cueing and hippocampal volume in amnestic mild cognitive impairment patients and cognitively normal older adults.

There is currently some debate as to whether hippocampus mediates contextual cueing. In the present study, we examined contextual cueing in patients diagnosed with mild cognitive impairment (MCI) and healthy older adults, with the main goal of investigating the role of hippocampus in this form of learning. Amnestic MCI (aMCI) patients and healthy controls completed the contextual cueing task, in which they were asked to search for a target (a horizontal T) in an array of distractors (rotated L's). Unbeknownst to them, the spatial arrangement of elements on some displays was repeated thus making the configuration a contextual cue to the location of the target. In contrast, the configuration for novel displays was generated randomly on each trial. The difference in response times between repeated and novel configurations served as a measure of contextual learning. aMCI patients, as a group, were able to learn spatial contextual cues as well as healthy older adults. However, better learning on this task was associated with higher hippocampal volume, particularly in right hemisphere. Furthermore, contextual cueing performance was significantly associated with hippocampal volume, even after controlling for age and MCI status. These findings support the role of the hippocampus in learning of spatial contexts, and also suggest that the contextual cueing paradigm can be useful in detecting neuropathological changes associated with the hippocampus.

Hierarchical acquisition of visual specificity in spatial contextual cueing.

Spatial contextual cueing refers to visual search performance's being improved when invariant associations between target locations and distractor spatial configurations are learned incidentally. Using the instance theory of automatization and the reverse hierarchy theory of visual perceptual learning, this study explores the acquisition of visual specificity in spatial contextual cueing. Two experiments in which detailed visual features were irrelevant for distinguishing between spatial contexts found that spatial contextual cueing was visually generic in difficult trials when the trials were not preceded by easy trials (Experiment 1) but that spatial contextual cueing progressed to visual specificity when difficult trials were preceded by easy trials (Experiment 2). These findings support reverse hierarchy theory, which predicts that even when detailed visual features are irrelevant for distinguishing between spatial contexts, spatial contextual cueing can progress to visual specificity if the stimuli remain constant, the task is difficult, and difficult trials are preceded by easy trials. However, these findings are inconsistent with instance theory, which predicts that when detailed visual features are irrelevant for distinguishing between spatial contexts, spatial contextual cueing will not progress to visual specificity. This study concludes that the acquisition of visual specificity in spatial contextual cueing is more plausibly hierarchical, rather than instance-based.

The effects of spatial contextual familiarity on remembered scenes, episodic memories, and imagined future events.

Several recent studies have explored the effect of contextual familiarity on remembered and imagined events. The aim of this study was to examine the extent of this effect by comparing the effect of cuing spatial memories, episodic memories, and imagined future events with spatial contextual cues of varying levels of familiarity. We used real-world landmark cues that had all been previously visited by the participants, and we measured the retrieval time, detail-richness, and vividness of remembered scenes, events, and imagined future events based on these cues. Participants consistently rated scenes and events based on more familiar cues as more detailed and more vivid, and they took less time to retrieve them. When the types of details were examined, it was revealed that the effects of increased contextual familiarity carry over to non-spatial details in the case of remembered events but possibly not in imagined events. This study provides evidence regarding how episodic memory and imagination are reliant on spatial context and possibly the process of scene construction.

Spatial Contextual Cueing Effect and Its Mechanisms

Invariant spatial configuration of the visual environment can guide observer's attention to specific location and facilitates recognition of the target in it, which is called spatial contextual cueing effect. Based on the systematic review on the previous studies, the present article introduced the classical studies and experimental paradigms of spatial contextual cueing effect, characteristics, content and process of spatial contextual learning, analyzed the mechanisms and neural bases of this effect. Finally, the article carried on the summary of five controversial issues in the previous studies and pointed out that future research could manipulate some key variables, such as materials and task difficulties, to solve these problems.

Acute stress differentially affects spatial configuration learning in high and low cortisol-responding healthy adults

BackgroundStress and stress hormones modulate memory formation in various ways that are relevant to our understanding of stress-related psychopathology, such as posttraumatic stress disorder (PTSD). Particular relevance is attributed to efficient memory formation sustained by the hippocampus and parahippocampus. This process is thought to reduce the occurrence of intrusions and flashbacks following trauma, but may be negatively affected by acute stress. Moreover, recent evidence suggests that the efficiency of visuo-spatial processing and learning based on the hippocampal area is related to PTSD symptoms.ObjectiveThe current study investigated the effect of acute stress on spatial configuration learning using a spatial contextual cueing task (SCCT) known to heavily rely on structures in the parahippocampus.MethodAcute stress was induced by subjecting participants (N = 34) to the Maastricht Acute Stress Test (MAST). Following a counterbalanced within-subject approach, the effects of stress and the ensuing hormonal (i.e., cortisol) activity on subsequent SCCT performance were compared to SCCT performance following a no-stress control condition.ResultsAcute stress did not impact SCCT learning overall, but opposing effects emerged for high versus low cortisol responders to the MAST. Learning scores following stress were reduced in low cortisol responders, while high cortisol-responding participants showed improved learning.ConclusionsThe effects of stress on spatial configuration learning were moderated by the magnitude of endogenous cortisol secretion. These findings suggest a possible mechanism by which cortisol responses serve an adaptive function during stress and trauma, and this may prove to be a promising route for future research in this area.

Learning of spatial statistics in nonhuman primates: Contextual cueing in baboons (Papio papio)

A growing number of theories of cognition suggest that many of our behaviors result from the ability to implicitly extract and use statistical redundancies present in complex environments. In an attempt to develop an animal model of statistical learning mechanisms in humans, the current study investigated spatial contextual cueing (CC) in nonhuman primates. Twenty-five baboons (Papio papio) were trained to search for a target (T) embedded within configurations of distrators (L) that were either predictive or non-predictive of the target location. Baboons exhibited an early CC effect, which remained intact after a 6-week delay and stable across extensive training of 20,000 trials. These results demonstrate the baboons’ ability to learn spatial contingencies, as well as the robustness of CC as a cognitive phenomenon across species. Nevertheless, in both the youngest and oldest baboons, CC required many more trials to emerge than in baboons of intermediate age. As a whole, these results reveal strong similarities between CC in humans and baboons, suggesting similar statistical learning mechanisms in these two species. Therefore, baboons provide a valid model to investigate how statistical learning mechanisms develop and/or age during the life span, as well as how these mechanisms are implemented in neural networks, and how they have evolved throughout the phylogeny.