Distractor Objects Research Articles

Integrating neural and ocular attention reorienting signals in virtual reality

Objective. Reorienting is central to how humans direct attention to different stimuli in their environment. Previous studies typically employ well-controlled paradigms with limited eye and head movements to study the neural and physiological processes underlying attention reorienting. Here, we aim to better understand the relationship between gaze and attention reorienting using a naturalistic virtual reality (VR)-based target detection paradigm. Approach. Subjects were navigated through a city and instructed to count the number of targets that appeared on the street. Subjects performed the task in a fixed condition with no head movement and in a free condition where head movements were allowed. Electroencephalography (EEG), gaze and pupil data were collected. To investigate how neural and physiological reorienting signals are distributed across different gaze events, we used hierarchical discriminant component analysis (HDCA) to identify EEG and pupil-based discriminating components. Mixed-effects general linear models (GLM) were used to determine the correlation between these discriminating components and the different gaze events time. HDCA was also used to combine EEG, pupil and dwell time signals to classify reorienting events. Main results. In both EEG and pupil, dwell time contributes most significantly to the reorienting signals. However, when dwell times were orthogonalized against other gaze events, the distributions of the reorienting signals were different across the two modalities, with EEG reorienting signals leading that of the pupil reorienting signals. We also found that the hybrid classifier that integrates EEG, pupil and dwell time features detects the reorienting signals in both the fixed (AUC = 0.79) and the free (AUC = 0.77) condition. Significance. We show that the neural and ocular reorienting signals are distributed differently across gaze events when a subject is immersed in VR, but nevertheless can be captured and integrated to classify target vs. distractor objects to which the human subject orients.

Gaze Behavior During Navigation and Visual Search of an Open-World Virtual Environment.

Eye tracking has been an essential tool within the vision science community for many years. However, the majority of studies involving eye-tracking technology employ a relatively passive approach through the use of static imagery, prescribed motion, or video stimuli. This is in contrast to our everyday interaction with the natural world where we navigate our environment while actively seeking and using task-relevant visual information. For this reason, an increasing number of vision researchers are employing virtual environment platforms, which offer interactive, realistic visual environments while maintaining a substantial level of experimental control. Here, we recorded eye movement behavior while subjects freely navigated through a rich, open-world virtual environment. Within this environment, subjects completed a visual search task where they were asked to find and count occurrence of specific targets among numerous distractor items. We assigned each participant into one of four target conditions: Humvees, motorcycles, aircraft, or furniture. Our results show a statistically significant relationship between gaze behavior and target objects across Target Conditions with increased visual attention toward assigned targets. Specifically, we see an increase in the number of fixations and an increase in dwell time on target relative to distractor objects. In addition, we included a divided attention task to investigate how search changed with the addition of a secondary task. With increased cognitive load, subjects slowed their speed, decreased gaze on objects, and increased the number of objects scanned in the environment. Overall, our results confirm previous findings and support that complex virtual environments can be used for active visual search experimentation, maintaining a high level of precision in the quantification of gaze information and visual attention. This study contributes to our understanding of how individuals search for information in a naturalistic (open-world) virtual environment. Likewise, our paradigm provides an intriguing look into the heterogeneity of individual behaviors when completing an un-timed visual search task while actively navigating.

Memory precision for salient distractors decreases with learned suppression

Attention operates as a cognitive gate that selects sensory information for entry into memory and awareness (Driver, 2001, British Journal of Psychology, 92, 53–78). Under many circumstances, the selected information is task-relevant and important to remember, but sometimes perceptually salient nontarget objects will capture attention and enter into awareness despite their irrelevance (Adams & Gaspelin, 2020, Attention, Perception, & Psychophysics, 82[4], 1586–1598). Recent studies have shown that repeated exposures with salient distractor will diminish their ability to capture attention, but the relationship between suppression and later cognitive processes such as memory and awareness remains unclear. If learned attentional suppression (indicated by reduced capture costs) occurs at the sensory level and prevents readout to other cognitive processes, one would expect memory and awareness to dimmish commensurate with improved suppression. Here, we test this hypothesis by measuring memory precision and awareness of salient nontargets over repeated exposures as capture costs decreased. Our results show that stronger learned suppression is accompanied by reductions in memory precision and confidence in having seen a color singleton at all, suggesting that such suppression operates at the sensory level to prevent further processing of the distractor object.

Visual working memory load plays limited, to no role in encoding distractor objects during visual search

ABSTRACT Previous research raised the counterintuitive hypothesis that searching for multiple potential targets leads to increased incidental encoding of distractors. Are these previously reported findings due to increased visual working memory (VWM) engagement, or less precise target templates? In four experiments, we examined the effect of VWM load during visual search on incidental encoding of distractors. Consecutive target repetitions indirectly reduce template-related VWM demands but failed to reduce recognition for distractors relative to conditions where the targets were novel. Distractors that were subsequently recognized attracted longer cumulative dwell time, regardless of search condition. When placed in a dual-task situation where search was performed while holding a working memory load, recognition for distractors was marginally improved relative to a search task without additional VWM demands. We ruled out the possibility that the dual-task was not sufficiently difficult to trigger the scrutiny of distractors required for significant encoding benefits by showing a decrement to encoding when search time was limited. This suggests that widening the attentional set is the crucial factor in improved incidental encoding given that observers can assign differential status to various contents of VWM. Thus, utilizing VWM resources in general appears insufficient to meaningfully improve incidental memory.

Drone vs. Bird Detection: Deep Learning Algorithms and Results from a Grand Challenge.

Adopting effective techniques to automatically detect and identify small drones is a very compelling need for a number of different stakeholders in both the public and private sectors. This work presents three different original approaches that competed in a grand challenge on the “Drone vs. Bird” detection problem. The goal is to detect one or more drones appearing at some time point in video sequences where birds and other distractor objects may be also present, together with motion in background or foreground. Algorithms should raise an alarm and provide a position estimate only when a drone is present, while not issuing alarms on birds, nor being confused by the rest of the scene. In particular, three original approaches based on different deep learning strategies are proposed and compared on a real-world dataset provided by a consortium of universities and research centers, under the 2020 edition of the Drone vs. Bird Detection Challenge. Results show that there is a range in difficulty among different test sequences, depending on the size and the shape visibility of the drone in the sequence, while sequences recorded by a moving camera and very distant drones are the most challenging ones. The performance comparison reveals that the different approaches perform somewhat complementary, in terms of correct detection rate, false alarm rate, and average precision.

Handgrip Based Action Information Modulates Attentional Selection: An ERP Study.

Prior work shows that the possibility of action to an object (visual affordance) facilitates attentional deployment. We sought to investigate the neural mechanisms underlying this modulation of attention by examining ERPs to target objects that were either congruently or incongruently gripped for their use in the presence of a congruently or incongruently gripped distractor. Participants responded to the presence or absence of a target object matching a preceding action word with a distractor object presented in the opposite location. Participants were faster in responding to congruently gripped targets compared to incongruently gripped targets. There was a reduced N2pc potential when the target was congruently gripped, and the distractor was incongruently gripped compared to the conditions where targets were incongruently gripped or when the distractor, as well as target, was congruently gripped. The N2pc results indicate that target selection is easier when action information is congruent with an object’s use.

Learning Diverse Models for End-to-End Ensemble Tracking.

In visual tracking, how to effectively model the target appearance using limited prior information remains an open problem. In this paper, we leverage an ensemble of diverse models to learn manifold representations for robust object tracking. The proposed ensemble framework includes a shared backbone network for efficient feature extraction and multiple head networks for independent predictions. Trained by the shared data within an identical structure, the mutually correlated head models heavily hinder the potential of ensemble learning. To shrink the representational overlaps among multiple models while encouraging the diversity of individual predictions, we propose the model diversity and response diversity regularization terms during training. By fusing these distinctive prediction results via a fusion module, the tracking variance caused by the distractor objects can be largely restrained. Our whole framework is end-to-end trained in a data-driven manner, avoiding the heuristic designs of multiple base models and fusion strategies. The proposed method achieves state-of-the-art results on seven challenging benchmarks while operating in real-time.

L1 activation during L2 processing is modulated by both age of acquisition and proficiency

It is well established that access to the bilingual lexicon is non-selective: even in an entirely monolingual context, elements of the non-target language are active. Research has also shown that activation of the non-target language is greater at higher proficiency levels, suggesting that it may be proficiency that drives cross-language lexical activation. At the same time, the potential role of age of acquisition (AoA) in cross-language activation has gone largely unexplored, as most studies have either focused on adult L2 learners or have conflated AoA with L2 proficiency. The present study examines the roles of AoA and L2 proficiency in L2 lexical processing using the visual world paradigm. Participants were a group of early L1 Afrikaans–L2 English bilinguals (AoA 1–9 years) and a control group of L1 English speakers. Importantly, in the bilingual group, AoA and proficiency were not correlated. In the task, participants viewed a screen with four objects on it: a target object, a competitor object whose Afrikaans translation overlapped phonetically with the target object, and two unrelated distractor objects. The results show that the L2 English group was significantly more likely to look at the cross-language competitor than the L1 English group, thus providing evidence of cross-language activation. Importantly, the extent to which this activation occurred was modulated by both L2 proficiency and AoA. These findings suggest that while these two variables may have been confounded in previous research, they actually both exert effects on cross-language activation. The locus of this parallel activation effect is discussed in terms of connectionist models of bilingualism.

Cross-Situational Word Learning in Two Foreign Languages: Effects of Native Language and Perceptual Difficulty

Cross-situational word learning (CSWL) paradigms have gained traction in recent years as a way to examine word learning in ambiguous scenarios in infancy, childhood, and adulthood. However, no study thus far has examined how CSWL paradigms may provide viable learning pathways for second language (L2) word learning. Here, we used a CSWL paradigm to examine how native Australian English (AusE) speakers learned novel Dutch (Experiment 1) and Brazilian Portuguese (Experiment 2) word-object pairings. During each learning phase trial, two words and objects were presented without indication as to which auditory word belonged to which visual referent. The two auditory words formed a non-minimal or vowel minimal pair. Minimal pairs were classified as “perceptually easy” or “perceptually difficult” based on the acoustic-phonetic relationship between AusE and each L2. At test, participants again saw two visual referents but heard one auditory label and were asked to select the corresponding referent. We predicted that accuracy would be highest for non-minimal pair trials (in which the auditory words associated with the target and distractor object formed a non-minimal pair), followed by perceptually easy minimal pairs, with lowest accuracy for perceptually difficult minimal pair trials. Our results support these hypotheses: While accuracy was above chance for all pair types, in both experiments accuracy was highest for non-minimal pair trials, followed by perceptually easy and then perceptually difficult minimal pair trials. These results are the first to demonstrate the effectiveness of CSWL in adult L2 word learning. Furthermore, the difference between perceptually easy and perceptually difficult minimal pairs in both language groups suggests that the acoustic-phonetic relationship between the L1-L2 is an important factor in novel L2 word learning in ambiguous learning scenarios. We discuss the implications of our findings for L2 acquisition, cross-situational learning and encoding of phonetic detail in a foreign language.

Do we predict upcoming speech content in naturalistic environments?

ABSTRACT The ability to predict upcoming actions is a hallmark of cognition. It remains unclear, however, whether the predictive behaviour observed in controlled lab environments generalises to rich, everyday settings. In four virtual reality experiments, we tested whether a well-established marker of linguistic prediction (anticipatory eye movements) replicated when increasing the naturalness of the paradigm by means of immersing participants in naturalistic scenes (Experiment 1), increasing the number of distractor objects (Experiment 2), modifying the proportion of predictable noun-referents (Experiment 3), and manipulating the location of referents relative to the joint attentional space (Experiment 4). Robust anticipatory eye movements were observed for Experiments 1–3. The anticipatory effect disappeared, however, in Experiment 4. Our findings suggest that predictive processing occurs in everyday communication if the referents are situated in the joint attentional space. Methodologically, our study confirms that ecological validity and experimental control may go hand-in-hand in the study of human predictive behaviour.

Visual Attention to Sexual Stimuli in Women With Clinical, Subclinical, and Normal Sexual Functioning: An Eye-Tracking Study

BackgroundVisual attention to sexual stimuli is an important means to facilitate sexual arousal and is thereby relevant for healthy sexual functioning. Experimental studies suggest that sexual dysfunction is associated with less attention toward sexual stimuli. AimThe goal of this study was to use an eye-tracking-based free-viewing paradigm to investigate whether women in the clinical range of sexual function attend to a genital area in visual sexual stimuli differently than women with subclinical sexual function or those with normal sexual functioning. MethodsToward this goal, 69 women (Mage = 27.77, SD = 8.00, range = 19–54) with clinical (n = 30), subclinical (n = 23), and normal (n = 16) levels of sexual functioning watched a series of 10 pictures depicting heterosexual couples during vaginal intercourse while their eye movements were recorded. Each picture was presented twice—once with a distracting object (eg, a to-do list or household appliance) present in the picture and once without—for 8 seconds, each. Outcomes5 eye-tracking measures indicative of different aspects of initial and sustained attention were analyzed. ResultsAs hypothesized, 3 out of 5 eye-tracking measures (ie, first fixation duration, number of first fixations, and total fixation duration) indicated that women in the clinical group attended less to the genital area in the pictures than women with normal sexual functioning. For 2 indices (ie, first fixation duration and total fixation duration), women with subclinical (vs normal) sexual functioning also attended less to the genital area. In contrast to our hypothesis, the presence of a distracting object did not influence attention to the genital area in either of the sexual function groups. Clinical ImplicationsThis study provides further evidence of the role of attentional biases in sexual dysfunction in women. Strengths and LimitationsEye-tracking methodology allows for a continuous measurement of visual attention; this is one of the first studies using this methodology to assess differences in visual attention in women with and without sexual dysfunction. However, the cross-sectional nature of this study prevents causal interpretation of findings. ConclusionFuture studies should use experimental paradigms to determine the causal role of visual attention for the development or maintenance of sexual dysfunction.Velten J, Milani S, Margraf J, et al. Visual Attention to Sexual Stimuli in Women With Clinical, Subclinical, and Normal Sexual Functioning: An Eye-Tracking Study. J Sex Med 2021;18:144–155.

Subitizing object parts reveals a second stage of individuation

Humans can efficiently individuate a small number of objects. This subitizing ability is thought to be a consequence of limited attentional resources. However, how and what is selected during the individuation process remain outstanding questions. We investigated these in four experiments by examining if parts of objects are enumerated as efficiently as distinct objects in the presence and absence of distractor objects. We found that distractor presence reduced subitizing efficiency. Crucially, parts connected to multiple objects were enumerated less efficiently than independent objects or parts connected to a single object. These results argue against direct individuation of parts and show that objecthood plays a fundamental role in individuation. Objects are selected first and their components are selected in subsequent steps. This reveals that individuation operates sequentially over multiple levels.

Selective attention to real-world objects drives their emotional appraisal.

Attentional manipulations have been shown to influence subsequent evaluations of objects and images. For example, images used as distractors in a visual search task are subsequently rated more negatively than are target images. One powerful manipulation of attention occurs when we plan and execute movements toward objects in our environment. Here, in two experiments, we show that selective attention to real-world objects subsequently improves emotional appraisal of those objects-an effect we term "target appreciation." Participants were presented with abstract images on three-dimensional objects, and were cued to either reach and grasp one of the two objects, or to respond to the cued object with a keyboard. Images presented on target objects were appraised more positively when compared with novel images. In contrast, images associated with obstacles or distractor objects were not appraised differently than novel images, despite the attentional suppression thought to be required to successfully avoid or ignore these objects. We speculate that this automatic appreciation of the objects of selective attention may be adaptive for organisms acting in complex environments.

Surface color under environmental illumination

Objects in real three-dimensional environments receive illumination from all directions, characterized in computer graphics by an environmental illumination map. The spectral content of this illumination can vary widely with direction [1], which means that the computational task of recovering surface color under environmental illumination cannot be reduced to correction for a single illuminant. We report the performance of human observers in selecting a target surface color from three distractors, one rendered under the same environmental illumination as the target, and two rendered under a different environmental illumination. Surface colors were selected such that, in the vast majority of trials, observers could identify the environment that contained non-identical surface colors, and color constancy performance was analyzed as the percentage of correct choices between the remaining two surfaces. The target and distractor objects were either matte or glossy and presented either with surrounding context or in a dark void. Mean performance ranged from 70% to 80%. There was a significant improvement in the presence of context, but no difference for matte and glossy stimuli, and no interaction between gloss and context. Analysis of trial-by-trial responses showed a dependence on the statistical properties of previously viewed images. Such analyses provide a means of investigating mechanisms that depend on environmental features, and not only on the properties of the instantaneous proximal image.

Age Differences in the Efficiency of Filtering and Ignoring Distraction in Visual Working Memory.

Healthy aging is associated with decline in the ability to maintain visual information in working memory (WM). We examined whether this decline can be explained by decreases in the ability to filter distraction during encoding or to ignore distraction during memory maintenance. Distraction consisted of irrelevant objects (Exp. 1) or irrelevant features of an object (Exp. 2). In Experiment 1, participants completed a spatial WM task requiring remembering locations on a grid. During encoding or during maintenance, irrelevant distractor positions were presented. In Experiment 2, participants encoded either single-feature (colors or orientations) or multifeature objects (colored triangles) and later reproduced one of these features using a continuous scale. In multifeature blocks, a precue appeared before encoding or a retrocue appeared during memory maintenance indicating with 100% certainty to the to-be-tested feature, thereby enabling filtering and ignoring of the irrelevant (not-cued) feature, respectively. There were no age-related deficits in the efficiency of filtering and ignoring distractor objects (Exp. 1) and of filtering irrelevant features (Exp. 2). Both younger and older adults could not ignore irrelevant features when cued with a retrocue. Overall, our results provide no evidence for an aging deficit in using attention to manage visual WM.

Collaboration improves unspeeded search in the absence of precise target information.

Two-person teams outperform individuals in search tasks, and even exceed expectations based on statistical limitations. Here, we aimed to replicate and extend this result. We used Bayesian hierarchical modelling of receiver operating characteristics to examine collaborative performance in a visual search task wherein top-down target information was constrained. Participants (N = 16 teams per experiment in Experiments 1 and 2; N = 24 teams in Experiment 3), working independently or collaboratively, performed a search task framed as a medical image reading task. Stimuli were polygons generated by randomly distorting a prototype shape. Observers judged whether an extreme distortion was present among a set of low-distortion distractor objects. Team members' individual sensitivity levels were used to predict collaborative sensitivity using two versions of a uniform judgment-weighting (UW) model, one that assumed stochastically independent judgments and one that accounted for correlations in the team members' judgments. Collaborative search was better than that from single observers in all three experiments, and consistently trended higher than predictions of the correlated UW model. Results imply that collaborative search can be highly efficient even when target foreknowledge is limited.

When slowing down processing helps learning: Lexico‐semantic structure supports retention, but interferes with disambiguation of novel object‐label mappings

This project explores how children disambiguate and retain novel object-label mappings in the face of semantic similarity. Burgeoning evidence suggests that semantic structure in the developing lexicon promotes word learning in ostensive contexts, whereas other findings indicate that semantic similarity interferes with and temporarily slows familiar word recognition. This project explores how these distinct processes interact when mapping and retaining labels for novel objects (i.e., low-frequency objects that are unfamiliar to toddlers) via disambiguation from a semantically similar familiar referent in 24-month-olds (N=65). Toddlers' log-adjusted looking to labeled target objects (relative to distractor objects) was measured in three conditions: Familiar trials (familiar label spoken while viewing semantically related familiar and novel objects), Disambiguation trials (unfamiliar label spoken while viewing semantically similar familiar and unfamiliar object), and Retention trials (unfamiliar label spoken while viewing novel object pairs). Toddlers' individual vocabulary structure was then compared to performance on each condition. Vocabulary structure was measured at two levels: category-level structure (semantic density) for experimental items, and lexicon-level structure (global clustering coefficient). The findings suggest, consistent with prior results, that semantic density interfered with known word recognition, and facilitated unfamiliar word retention. Children did not show a significant novel word preference during disambiguation, and disambiguation behavior was not impacted by semantic structure. These findings connect seemingly disparate mechanisms of semantic interference in processing and semantic leveraging in word learning. Semantic interference momentarily slows word recognition and resolution of referential uncertainty for novel label-object mappings. Nevertheless, this slowing might support retention by enabling comparison between related objects.

Domain Randomization Using Deep Neural Networks for Estimating Positions of Bolts

Abstract Current manual practices of replacing bolts on structures are time-consuming and costly, especially because of numerous bolts. Thus, an automated method that can visually detect and localize bolt positions would be highly beneficial. We demonstrate the use of deep neural networks using domain randomization for detecting and localizing bolts on a workpiece. In contrast to previous approaches that require training on real images, the use of domain randomization enables all training in simulation. The key idea is to create a wide variety of computer-generated synthetic images by varying the texture, color, camera position and orientation, distractor objects, and noise, and train the neural network on these images such that the neural network is robust to scene variability and hence provides accurate results when deployed on real images. Using domain randomization, we train two neural networks, a faster regional convolutional neural network for detecting the bolt and placing a bounding box, and a regression convolutional neural network for estimating the x- and y-position of the bolts relative to the coordinates fixed to the workpiece. Our results indicate that in the best case, we can detect bolts with 85% accuracy and can predict 75% of bolts within 1.27 cm accuracy. The novelty of this work is in using domain randomization to detect and localize: (1) multiples of a single object and (2) small-sized objects (0.6 cm × 2.5 cm).

When and how did you go wrong? Characterizing mild functional difficulties in older adults during an everyday task

ABSTRACT Mild functional difficulties associated with cognitive aging may be reliably measured by coding “micro-errors” during everyday tasks, like meal preparation. Micro-errors made by 25 older adult and 48 younger adults were coded on four dimensions to evaluate the influence of: 1) poor error monitoring; 2) goal decay; 3) competition for response selection when switching to a new subtask; and 4) interference from distractor objects. Micro-errors made by young adults under a dual task load also were analyzed to determine the influence of overall performance level. Older adults’ micro-errors were observed when switching to a new subtask and to unrelated distractors. Slowed error monitoring and goal decay also influenced micro-errors in older adults, but not significantly more so than younger adults under the dual task. Interventions to reduce interference from distractors and to increase attention at critical choice points during tasks may optimize everyday functioning and preclude decline in older adults.

The Table-top Visual Search Ability Test for children and young people: Normative response time data from typically developing children

Five table-top tasks were developed to test the visual search ability of children and young people in a real-world context, and to assess the transfer of training-related improvements in visual search on computerised tasks to real-world activities. Each task involved searching for a set of target objects among distracting objects on a table-top. Performance on the Table-top Visual Search Ability Test for Children (TVSAT-C) was measured as the time spent searching for targets divided by the number of targets found. A total of 108 typically developing children (3–11 years old) and eight children with vision impairment (7–12 years old) participated in the study. A significant correlation was found between log-transformed age and log-transformed performance ( R2 = .65, p = 4 × 10−26) in our normative sample, indicating a monomial power law relationship between age and performance with an exponent of [Formula: see text], [Formula: see text] We calculated age-dependent percentiles and receiver operating characteristic curve analysis indicated the third percentile as the optimal cut-off for detecting a visual search deficit, giving a specificity of [Formula: see text], [Formula: see text] and sensitivity of [Formula: see text], [Formula: see text] for the test. Further studies are required to calculate measures of reliability and external validity, to confirm sensitivity for visual search deficits, and to investigate the most appropriate response modes for participants with conditions that affect manual dexterity. In addition, more work is needed to assess construct validity where semantic knowledge is required that younger children may not have experience with. We have made the protocol and age-dependent normative data available for those interested in using the test in research or practice, and to illustrate the smooth developmental trajectory of visual search ability during childhood.