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In previous studies, it was established that individuals can implicitly learn spatiotemporal regularities related to how the distribution of target locations unfolds across the time course of a single trial. However, these regularities were tied to the appearance of salient targets that are known to capture attention in a bottom-up way. The current study investigated whether the saliency of target is necessary for this type of learning to occur. In a visual search task, participants were instructed to search for a unique circle with a gap (Landolt C) among two other circles and indicate the location of the gap. Unbeknownst to them, the onset timing of search displays predicted the target location. Specifically, the target appeared more frequently at one peripheral location with an early onset of the search display and at the opposite peripheral location with a late onset of the search display. Additionally, we manipulated the gap size of the Landolt C to create either nonsalient (small gap) or salient (big gap) target events. Results showed that, regardless of prior exposure to salient targets (Experiment 1) or nonsalient targets (Experiment 2), visual search efficiency increased when the target appeared at the temporally valid location compared with the temporally invalid location. In conclusion, the saliency of targets and the associated bottom-up capture is not a prerequisite for learning dynamic distributional regularities of target locations during visual search. [ABSTRACT FROM AUTHOR]

Understanding the interplay between top–down and bottom–up attention in visual working memory (VWM) is crucial, although the specific challenges arising from this interaction remain ambiguous. In this study, we address this complexity by examining how cue informativeness and probe status of the salient items influence this interaction. Through three experiments, we manipulated top–down attention by varying probe frequencies using pre-cues and bottom–up attention by varying the visual salience of memory items. Experiment 1 explored cue informativeness at 100% and 50%, while Experiments 2 and 3 maintained cue informativeness at 80% and 50%. Additionally, Experiment 1 tested a few of the salient items, Experiment 2 excluded them, and Experiment 3 tested half of them in each cue condition. Across all experiments, we consistently observed cueing benefits for cue-directed items, albeit with costs to non-cued items. Furthermore, cue informativeness and the probe status of salient items emerged as critical factors influencing the interaction between top–down and bottom–up attention in VWM. These findings underscore the pivotal roles of cue informativeness and salient item relevance in shaping the dynamics of top–down and bottom–up attention within VWM. [ABSTRACT FROM AUTHOR]

Within the framework of the theory of visual attention (TVA), the visual attention span (VAS) deficit among individuals with developmental dyslexia has been ascribed to the problems entailed by bottom–up (BotU) and top–down (TopD) attentional processes. The former involves two VAS subcomponents: the visual short-term memory storage and perceptual processing speed; the latter consists of the spatial bias of attentional weight and the inhibitory control. Then, what about the influences of the BotU and TopD components on reading? Are there differences in the roles of the two types of attentional processes in reading? This study addresses these issues by using two types of training tasks separately, corresponding to the BotU and TopD attentional components. Three groups of Chinese children with dyslexia—15 children each in the BotU training, TopD training, and non-trained active control groups were recruited here. Participants completed reading measures and a CombiTVA task which was used to estimate VAS subcomponents, before and after the training procedure. Results showed that BotU training improved both the within-category and between-category VAS subcomponents and sentence reading performance; meanwhile, TopD training enhanced character reading fluency through improving spatial attention capacity. Moreover, benefits on attentional capacities and reading skills in the two training groups were generally maintained three months after the intervention. The present findings revealed diverse patterns in the influences of VAS on reading within the TVA framework, which contributes to enriching the understanding of VAS-reading relation. [ABSTRACT FROM AUTHOR]

Does the strength of representations in long-term memory (LTM) depend on which type of attention is engaged? We tested participants' memory for objects seen during visual search. We compared implicit memory for two types of objects—related-context nontargets that grabbed attention because they matched the target defining feature (i.e., color; top-down attention) and salient distractors that captured attention only because they were perceptually distracting (bottom-up attention). In Experiment 1, the salient distractor flickered, while in Experiment 2, the luminance of the salient distractor was alternated. Critically, salient and related-context nontargets produced equivalent attentional capture, yet related-context nontargets were remembered far better than salient distractors (and salient distractors were not remembered better than unrelated distractors). These results suggest that LTM depends not only on the amount of attention but also on the type of attention. Specifically, top-down attention is more effective in promoting the formation of memory traces than bottom-up attention. [ABSTRACT FROM AUTHOR]

Since our environment typically contains more information than can be processed at any one time due to the limited capacity of our visual system, we are bound to differentiate between relevant and irrelevant information. This process, termed attentional selection, is usually categorized into bottom-up and top-down processes. However, recent research suggests reward might also be an important factor in guiding attention. Monetary reward can bias attentional selection in favor of task-relevant targets and reduce the efficiency of visual search when a reward-associated, but task-irrelevant distractor is present. This study is the first to investigate reward-related target and distractor processing in an additional singleton task using neurophysiological measures and source space analysis. Based on previous studies, we hypothesized that source space analysis would find enhanced neural activity in regions of the value-based attention network, such as the visual cortex and the anterior cingulate. Additionally, we went further and explored the time courses of the underlying attentional mechanisms. Our neurophysiological results showed that rewarding distractors led to a stronger attentional capture. In line with this, we found that reward-associated distractors (compared with reward-associated targets) enhanced activation in frontal regions, indicating the involvement of top-down control processes. As hypothesized, source space analysis demonstrated that reward-related targets and reward-related distractors elicited activation in regions of the value-based attention network. However, these activations showed time-dependent differences, indicating that the neural mechanisms underlying reward biasing might be different for task-relevant and task-irrelevant stimuli. [ABSTRACT FROM AUTHOR]

Background: An emerging trend in visual information processing is toward incorporating some interesting properties of the ventral stream in order to account for some limitations of machine learning algorithms. Selective attention and cortical magnification are two such important phenomena that have been the subject of a large body of research in recent years. In this paper, we focus on designing a new model for visual acquisition that takes these important properties into account. Methods: We propose a new framework for visual information acquisition and representation that emulates the architecture of the primate visual system by integrating features such as retinal sampling and cortical magnification while avoiding spatial deformations and other side effects produced by models that tried to implement these two features. It also explicitly integrates the notion of visual angle, which is rarely taken into account by vision models. We argue that this framework can provide the infrastructure for implementing vision tasks such as object recognition and computational visual attention algorithms. Results: To demonstrate the utility of the proposed vision framework, we propose an algorithm for bottom-up saliency prediction implemented using the proposed architecture. We evaluate the performance of the proposed model on the MIT saliency benchmark and show that it attains state-of-the-art performance, while providing some advantages over other models. Conclusion: Here is a summary of the main contributions of this paper: (1) Introducing a new bio-inspired framework for visual information acquisition and representation that offers the following properties: (a) Providing a method for taking the distance between an image and the viewer into account. This is done by incorporating a visual angle parameter which is ignored by most visual acquisition models. (b) Reducing the amount of visual information acquired by introducing a new scheme for emulating retinal sampling and cortical magnification effects observed in the ventral stream. (2) Providing a concrete application of the proposed framework by using it as a substrate for building a new saliency-based visual attention model, which is shown to attain state-of-the-art performance on the MIT saliency benchmark. (3) Providing an online Git repository that implements the introduced framework that is meant to be developed as a scalable, collaborative project. [ABSTRACT FROM AUTHOR]

The gap effect refers to a reduction in saccadic reaction time ( SRT) to an eccentric target, when the fixation point is removed before the target onset. Though it is known that the gap effect peaks when the fixation point is offset about 200 ms before the onset of the eccentric target, it is unknown how this effect is modulated by stimulus variations. In this paper, we propose and investigate a model of saccadic reaction time as a function of the fixation point brightness gain. The brightness gain is defined as the ratio of the final and initial intensities of the stimulus. We have conducted a typical gap effect experiment with 15 participants, where the brightness of the fixation point was manipulated under four conditions and two gap intervals, at the same time and 200 ms before the onset of the eccentric target. The conditions included removing the fixation point (offset), leaving it with constant brightness (overlap), reducing, and increasing its brightness (lower and higher brightness conditions). Experimental data showed a significant gap effect in the offset and lower brightness conditions when compared to the overlap condition. On the other hand, the SRT was significantly longer for the higher brightness condition than the SRT for the overlap condition. Linear regression analysis using ten values of brightness gain shows that our model fits the data well for the 0- and 200-ms gap, with a coefficient of determination of .89 and .94, respectively. [ABSTRACT FROM AUTHOR]

This paper presents a new attention model for detecting visual saliency in news video. In the proposed model, bottom-up (low level) features and top-down (high level) factors are used to compute bottom-up saliency and top-down saliency respectively. Then, the two saliency maps are fused after a normalization operation. In the bottom-up attention model, we use quaternion discrete cosine transform in multi-scale and multiple color spaces to detect static saliency. Meanwhile, multi-scale local motion and global motion conspicuity maps are computed and integrated into motion saliency map. To effectively suppress the background motion noise, a simple histogram of average optical flow is adopted to calculate motion contrast. Then, the bottom-up saliency map is obtained by combining the static and motion saliency maps. In the top-down attention model, we utilize high level stimulus in news video, such as face, person, car, speaker, and flash, to generate the top-down saliency map. The proposed method has been extensively tested by using three popular evaluation metrics over two widely used eye-tracking datasets. Experimental results demonstrate the effectiveness of our method in saliency detection of news videos compared to several state-of-the-art methods. [ABSTRACT FROM AUTHOR]

We examined the impact of simultaneous bottom-up visual influences and meaningful social stimuli on attention orienting in young children with autism spectrum disorders (ASDs). Relative to typically-developing age and sex matched participants, children with ASDs were more influenced by bottom-up visual scene information regardless of whether social stimuli and bottom-up scene properties were congruent or competing. This initial reliance on bottom-up strategies correlated with severity of social impairment as well as receptive language impairments. These data provide support for the idea that there is enhanced reliance on bottom-up attention strategies in ASDs, and that this may have a negative impact on social and language development. [ABSTRACT FROM AUTHOR]

In biological vision systems, attention mechanisms are responsible for selecting the relevant information from the sensed field of view, so that the complete scene can be analyzed using a sequence of rapid eye saccades. In recent years, efforts have been made to imitate such attention behavior in artificial vision systems, because it allows optimizing the computational resources as they can be focused on the processing of a set of selected regions. In the framework of mobile robotics navigation, this work proposes an artificial model where attention is deployed at the level of objects (visual landmarks) and where new processes for estimating bottom-up and top-down (target-based) saliency maps are employed. Bottom-up attention is implemented through a hierarchical process, whose final result is the perceptual grouping of the image content. The hierarchical grouping is applied using a Combinatorial Pyramid that represents each level of the hierarchy by a combinatorial map. The process takes into account both image regions (faces in the map) and edges (arcs in the map). Top-down attention searches for previously detected landmarks, enabling their re-detection when the robot presumes that it is revisiting a known location. Landmarks are described by a combinatorial submap; thus, this search is conducted through an error-tolerant submap isomorphism procedure. [ABSTRACT FROM AUTHOR]

biologically-inspired model of visual attention known as basic saliency model is biased for object detection. It is possible to make this model faster by inhibiting computation of features or scales, which are less important for detection of an object. To this end, we revise this model by implementing a new scale-wise surround inhibition. Each feature channel and scale is associated with a weight and a processing cost. Then a global optimization algorithm is used to find a weight vector with maximum detection rate and minimum processing cost. This allows achieving maximum object detection rate for real time tasks when maximum processing time is limited. A heuristic is also proposed for learning top-down spatial attention control to further limit the saliency computation. Comparing over five objects, our approach has 85.4 and 92.2% average detection rates with and without cost, respectively, which are above 80% of the basic saliency model. Our approach has 33.3 average processing cost compared with 52 processing cost of the basic model. We achieved lower average hit numbers compared with NVT but slightly higher than VOCUS attentional systems. [ABSTRACT FROM AUTHOR]

Recent neuroimaging studies suggest that the superior parietal lobule (SPL) of the human cortex mediates goal-directed attentional orienting, while the temporo-parietal junction (TPJ) mediates stimulus-driven attentional orienting. Here, we investigated these brain-behavior correspondences by examining the performance of patients with an attentional deficit following a right hemisphere lesion. Patients completed two tasks, one sensitive to stimulus-driven attentional orienting and the other to goal-directed attentional orienting. Based on the behavioral profiles obtained on each task, patients were assigned to different groups and their lesion overlap explored. Patients who exhibited difficulties with goal-directed attentional orienting and showed concurrent 'hyper-capture' presented with lesion overlap centered over superior portions of the parietal lobule with spared inferior portions of the parietal lobule. Patients who performed normally on the goal-directed orienting task, while remaining abnormally immune to attentional capture, presented with lesion overlap centered over the inferior portions of the parietal lobule but spared superior parietal lobule. The findings from this study clearly suggest that (a) SPL and TPJ are anatomical regions that are recruited for the purposes of top-down and bottom-up orienting, respectively, and that damage to SPL and TPJ leads to disorders of top-down and bottom-up orienting, and (b) albeit dissociable, top-down and bottom-up orienting (and, by extension, SPL and TPJ) are not entirely independent mechanisms. [ABSTRACT FROM AUTHOR]