A critical review of selective attention: an interdisciplinary perspective

Design guidelines for limiting and eliminating virtual reality-induced symptoms and effects at work: a comprehensive, factor-oriented review

Virtual reality (VR) can induce side effects known as virtual reality-induced symptoms and effects (VRISE). To address this concern, we identify a literature-based listing of these factors thought to influence VRISE with a focus on office work use. Using those, we recommend guidelines for VRISE amelioration intended for virtual environment creators and users. We identify five VRISE risks, focusing on short-term symptoms with their short-term effects. Three overall factor categories are considered: individual, hardware, and software. Over 90 factors may influence VRISE frequency and severity. We identify guidelines for each factor to help reduce VR side effects. To better reflect our confidence in those guidelines, we graded each with a level of evidence rating. Common factors occasionally influence different forms of VRISE. This can lead to confusion in the literature. General guidelines for using VR at work involve worker adaptation, such as limiting immersion times to between 20 and 30 min. These regimens involve taking regular breaks. Extra care is required for workers with special needs, neurodiversity, and gerontechnological concerns. In addition to following our guidelines, stakeholders should be aware that current head-mounted displays and virtual environments can continue to induce VRISE. While no single existing method fully alleviates VRISE, workers' health and safety must be monitored and safeguarded when VR is used at work.

Gender composition of pairs influences joint action effect

Research on joint action has demonstrated that individuals are sensitive to a coactor's attentional relation to jointly attend stimuli. It has also been suggested that some features are necessary to resolve the discrimination problem (i.e., self-own and other-own actions). In the present study, we aimed to test whether the gender composition of interacting pairs modulated the joint action effect. Same- (female-female or male-male) and mixed- (female-male) gender pairs performed a joint version of flanker tasks in Experiment 1 (90 participants, 50% males), while in Experiment 2 (154 participants, 50% males) Navon tasks were performed. In Experiment 1, a higher joint flanker effect in same-gender pairs than in mixed-gender pairs, and this joint effect was similar to the classical flanker effect reported by males and females in a classical procedure of the task (70 participants, 50% males). In Experiment 2, the same-gender pairs reported a joint Navon effect, which was reversed in mixed-gender pairs. In conclusion, our findings support how the gender composition of interacting pairs plays a role in joint attentional tasks.

Changes in the components of visual attention following traumatic brain injury: A systematic review and meta-analysis

Purpose

We conducted a systematic review and meta-analysis to understand the impact of traumatic brain injury (TBI) on visual attention and whether different components and processes of visual attention (such as selective, sustained, divided, and covert orientation of visual attention) are affected following brain injury.

Methods

A literature search between January 1980 to May 2021 was conducted using Medline, Scopus, PubMed, and Google Scholar databases was undertaken for studies that assessed visual attention using different tasks that target specific or multiple components of visual attention. Three hundred twenty-nine potentially relevant articles were identified, and 20 studies met our inclusion criteria.

Results

A total of 123 effect sizes (ES) were estimated from 20 studies that included 519 patients with TBI and 530 normal participants. The overall combined ES was statistically significant and large (ES = 0.92), but with high heterogeneity (Q = 614.83, p < 0.0001, I² = 80.32%). Subgroup analysis showed that the impact of TBI severity, with the ES for moderate-severe TBI significantly higher than mild TBI (t (112) = 3.11, p = 0.002). Additionally, the component of visual attention was differentially affected by TBI (F (2, 120) = 10.25, p<0.0001); the ES for selective attention (ES = 1.13) and covert orientation of visual attention (ES = 1.14) were large, whilst for sustained attention, the ES was medium at 0.43. A subgroup analysis comparing outcome measures showed that reaction time (ES = 1.12) was significantly more affected compared to performance accuracy (ES = 0.43), F (1, 96) = 25.98, p<0.0001).

Conclusion

Large and significant deficits in visual attention was found following TBI which can last for years after the initial injury. However, different components of visual attention were not affected to the same extent, with selective visual attention and orientation of visual attention most affected following TBI.

What Can Computational Models Learn From Human Selective Attention? A Review From an Audiovisual Unimodal and Crossmodal Perspective

Selective attention plays an essential role in information acquisition and utilization from the environment. In the past 50 years, research on selective attention has been a central topic in cognitive science. Compared with unimodal studies, crossmodal studies are more complex but necessary to solve real-world challenges in both human experiments and computational modeling. Although an increasing number of findings on crossmodal selective attention have shed light on humans' behavioral patterns and neural underpinnings, a much better understanding is still necessary to yield the same benefit for intelligent computational agents. This article reviews studies of selective attention in unimodal visual and auditory and crossmodal audiovisual setups from the multidisciplinary perspectives of psychology and cognitive neuroscience, and evaluates different ways to simulate analogous mechanisms in computational models and robotics. We discuss the gaps between these fields in this interdisciplinary review and provide insights about how to use psychological findings and theories in artificial intelligence from different perspectives.

Feature Map Quality Score Estimation Through Regression

Understanding the visual quality of a feature map plays a significant role in many active vision applications. Previous works mostly rely on object-level features, such as compactness, to estimate the quality score of a feature map. However, the compactness is leveraged on feature maps produced by salient object detection techniques where the maps tend to be compact. As a result, the compactness feature fails when the feature maps are blurry (e.g., fixation maps). In this paper, we regard the process of estimating the quality score of feature maps, specifically fixation maps, as a regression problem. After extracting several local, global, geometric, and positional characteristic features from a feature map, a model is learned using a random forest regressor to estimate the quality score of any unseen feature map. Our model is specifically tailored to estimate the quality of three types of maps: bottom-up, target, and contextual feature maps. These maps are produced for a large benchmark fixation data set of more than 900 challenging outdoor images. We demonstrate that our approach provides an accurate estimate of the quality of the abovementioned feature maps compared to the groundtruth data. In addition, we show that our proposed approach is useful in feature map integration for predicting human fixation. Instead of naively integrating all three feature maps when predicting human fixation, our proposed approach dynamically selects the best feature map with the highest estimated quality score on an individual image basis, thereby improving the fixation prediction accuracy.

Sex and menstrual cycle influences on three aspects of attention

Sex differences and menstrual cycle influences have been investigated in a variety of cognitive abilities, but results regarding attention are comparably sparse. In the present study, 35 men and 32 naturally cycling women completed three attention tasks, which are commonly used in neuropsychological assessment situations. All participants completed two sessions, which were time-locked to the follicular (low progesterone) and luteal cycle phase (high progesterone) in women. The results reveal higher operation speed during sustained attention in men, but no sex differences in selected and divided attention. Menstrual cycle influences were observed on accuracy in all three tasks. During divided and sustained attention, for which a male advantage was previously reported, accuracy was higher during the early follicular compared to the mid-luteal cycle phase. Furthermore, during selected and sustained attention the learning effect from the first to the second test session was higher in women who started the experiment in their luteal cycle phase. These results suggest a possible role of progesterone in modulating the ability to focus on certain stimulus aspects, while inhibiting others and to sustain attention over a longer period of time.

Sex differences in the Simon task help to interpret sex differences in selective attention

In the last decade, a number of studies have reported sex differences in selective attention, but a unified explanation for these effects is still missing. This study aims to better understand these differences and put them in an evolutionary psychological context. 418 adult participants performed a computer-based Simon task, in which they responded to the direction of a left or right pointing arrow appearing left or right from a fixation point. Women were more strongly influenced by task-irrelevant spatial information than men (i.e., the Simon effect was larger in women, Cohen's d = 0.39). Further, the analysis of sex differences in behavioral adjustment to errors revealed that women slow down more than men following mistakes (d = 0.53). Based on the combined results of previous studies and the current data, it is proposed that sex differences in selective attention are caused by underlying sex differences in core abilities, such as spatial or verbal cognition.

Modality-specificity of Selective Attention Networks

Objective: To establish the modality specificity and generality of selective attention networks.

Method: Forty-eight young adults completed a battery of four auditory and visual selective attention tests based upon the Attention Network framework: the visual and auditory Attention Network Tests (vANT, aANT), the Test of Everyday Attention (TEA), and the Test of Attention in Listening (TAiL). These provided independent measures for auditory and visual alerting, orienting, and conflict resolution networks. The measures were subjected to an exploratory factor analysis to assess underlying attention constructs.

Results: The analysis yielded a four-component solution. The first component comprised of a range of measures from the TEA and was labeled “general attention.” The third component was labeled “auditory attention,” as it only contained measures from the TAiL using pitch as the attended stimulus feature. The second and fourth components were labeled as “spatial orienting” and “spatial conflict,” respectively—they were comprised of orienting and conflict resolution measures from the vANT, aANT, and TAiL attend-location task—all tasks based upon spatial judgments (e.g., the direction of a target arrow or sound location).

Conclusions: These results do not support our a-priori hypothesis that attention networks are either modality specific or supramodal. Auditory attention separated into selectively attending to spatial and non-spatial features, with the auditory spatial attention loading onto the same factor as visual spatial attention, suggesting spatial attention is supramodal. However, since our study did not include a non-spatial measure of visual attention, further research will be required to ascertain whether non-spatial attention is modality-specific.

Attentional spreading to task-irrelevant object features: experimental support and a 3-step model of attention for object-based selection and feature-based processing modulation

Directing attention to a specific feature of an object has been linked to different forms of attentional modulation. Object-based attention theory founds on the finding that even task-irrelevant features at the selected object are subject to attentional modulation, while feature-based attention theory proposes a global processing benefit for the selected feature even at other objects. Most studies investigated either the one or the other form of attention, leaving open the possibility that both object- and feature-specific attentional effects do occur at the same time and may just represent two sides of a single attention system. We here investigate this issue by testing attentional spreading within and across objects, using reaction time (RT) measurements to changes of attended and unattended features on both attended and unattended objects. We asked subjects to report color and speed changes occurring on one of two overlapping random dot patterns (RDPs), presented at the center of gaze. The key property of the stimulation was that only one of the features (e.g., motion direction) was unique for each object, whereas the other feature (e.g., color) was shared by both. The results of two experiments show that co-selection of unattended features even occurs when those features have no means for selecting the object. At the same time, they demonstrate that this processing benefit is not restricted to the selected object but spreads to the task-irrelevant one. We conceptualize these findings by a 3-step model of attention that assumes a task-dependent top-down gain, object-specific feature selection based on task- and binding characteristics, and a global feature-specific processing enhancement. The model allows for the unification of a vast amount of experimental results into a single model, and makes various experimentally testable predictions for the interaction of object- and feature-specific processes.