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The giant mottled eel Anguilla marmorata Quoy & Gaimard is an important aquaculture candidate in eel farming industry. The high economic value of the species leads to intensive cultivation affecting its welfare under farm condition. Since colour environment affects the welfare of confined fishes, basic information on colour vision is necessary. By means of a behavioural experiment of A. marmorata elvers in the laboratory, we determined colour vision under natural daylight. The elvers were subjected to classical conditioning to associate a reward feed with a blue or a green stimulus placed amid seven shades of grey. The elvers learned this visual task after 30 or 36 trials and thus the ability of colour discrimination was confirmed. Since the elvers have the retinal tapetum, it may be suggested that colour vision in dim light enables crepuscular feeding by the A. marmorata elvers, clearly an advantage in aquaculture.

The purpose of this study was to investigate the effects of sport participation, concussion history, and age of first exposure to football on preseason cerebrovascular function in adolescent athletes. Athletes (n = 53, age = 15.8 ± 1.2 years) were examined based on three exposure groupings: (1) sport participation (football vs. non-collision), (2) concussion history (none vs. ≥ 1), and (3) age of first exposure (football participants only). Transcranial Doppler assessed cerebrovascular reactivity (CVR) and neurovascular coupling (NVC), and separate independent samples t-tests evaluated group differences in CVR and NVC outcomes. Separate univariate linear regressions determined how age of first exposure related to CVR and NVC outcomes. Linear mixed effects models assessed group differences in CVR and NVC relative response curves. Differential response to NVC visual task response was significantly greater in non-collision sport athletes (F1,2946 = 38.69, p < 0.0001) and athletes without a concussion history (F1,2946 = 25.23, p < 0.0001). Older age of first exposure significantly predicted reduced breath-holding CVR response (F1,1560 = 2.92, p = 0.03). Healthy adolescent athletes have similar pre-season cerebrovascular function despite different sport participation and concussion history. However, age of first exposure may predict CVR in adolescent football athletes. Developmental literature identifies cerebrovascular function as dynamically changing throughout adolescence. Our study provides fundamental data informing the clinical meaningfulness of short- and long-term physiological function changes.

Dynamic accommodation under natural viewings, such as driving, could be affected by the lighting condition. This study aimed to investigate the accommodation rock after the visual display unit (VDU) activity with and without ambient lighting. It was measured in cycle minute (cpm) with Hart Chart before and after each lighting condition's VDU activity. The VDU activity involved a one-hour visual task in 30 young adults. There was significant different [c2(3) = 23.42, p

Humans are living in the age of big data, advanced analytics, and human information interaction. The tremendous growth of ‘the data' presents enormous challenges to information-seeking. A naïve user adapts several strategies (e.g., analytical search, search by analogy, etc.) to aggregate the knowledge. Augmented visualization plays a pivotal role via visual cognitive support in user searches (i.e., simple visual search, visual exploration, etc.). Though it is hard for a user to look for specific tasks or visual metaphors, as evaluation of visual task is rarely undertaken, it is unclear what role, if any, information visualizations play in the user search. In this paper, a visual taxonomy is adopted to systematically review key visualization tools to understand the visual tasks and inherent functions and viability. The key contribution is to trace the current trends and advancements on the dimensions (i.e., visual accomplishments and visual implications) and to assert that annotations will provide a vision on the state of exploratory visual analytics, evolving frameworks, and tools.

Objective. Retinal prostheses are a promising strategy to restore sight to patients with retinal degenerative diseases. These devices compensate for the loss of photoreceptors by electrically stimulating neurons in the retina. Currently, the visual function that can be recovered with such devices is very limited. This is due, in part, to current spread, unintended axonal activation, and the limited resolution of existing devices. Here we show, using a recent model of prosthetic vision, that optimizing how visual stimuli are encoded by the device can help overcome some of these limitations, leading to dramatic improvements in visual perception. Approach. We propose a strategy to do this in practice, using patients’ feedback in a visual task. The main challenge of our approach comes from the fact that, typically, one only has access to a limited number of noisy responses from patients. We propose two ways to deal with this: first, we use a model of prosthetic vision to constrain and simplify the optimization. We show that, if one knew the parameters of this model for a given patient, it would be possible to greatly improve their perceptual performance. Second we propose a preferential Bayesian optimization to efficiently learn these model parameters for each patient, using minimal trials. Main results. To test our approach, we presented healthy subjects with visual stimuli generated by a recent model of prosthetic vision, to replicate the perceptual experience of patients fitted with an implant. Our optimization procedure led to significant and robust improvements in perceived image quality, that transferred to increased performance in other tasks. Significance. Importantly, our strategy is agnostic to the type of prosthesis and thus could readily be implemented in existing implants.

The study focused on low light intensity spaces. The research helps to find strategies for the reduction of energy consumption. It aims to highlight the role of colour temperature in the lighting design of historic buildings. The case study corresponds to a Roman archaeological site of the Badalona Museum in Barcelona. The lighting design uses three different colour temperatures to differentiate groups of surfaces which play a different role in the visual field. The information panels are lit with white light, the old Roman city has warm white colour light, and the new walkway over the ruins is lit with cool white light. This study evaluates colour temperature value, luminance value and visual task. The present work reveals that the colour temperature allows setting apart and classifying the visual information from low luminance values. The research presented addresses the importance of the colour temperature, as a significant visual perception component, in the inherent low light intensity design proposal to energy conservation.

We developed an artificial neural network (ANN) classifier to analyze the cortical activity signals during visual information processing. We tested several ANN architectures and chose a convolutional neural network (CNN) with the Resnet50 topology. As a result, the trained CNN classifier achieved an accuracy of 74% on the data of newly recruited subjects.

This study presents a novel approach for familiar and unfamiliar face classification based on electroencephalography (EEG). Firstly, the raw EEG epoch is temporally split into three overlapped segments, and each segment is decomposed into multiple sub-bands by band-pass filters. Then, differential entropy is employed to extract discriminative EEG features. Finally, the obtained features are concatenated and classified with the support vector machine (SVM). The results yielded on our database indicate that the proposed method can achieve a mean accuracy of 76.2% over five participants. This work primarily demonstrates that differential entropy is an effective feature for EEG-based familiar and unfamiliar face classification, and has the potential to be applied to other EEG-based visual task analyses.

Simulation-based training utilising visual displays are common in many defence and civil domains. The performance of individuals in these tasks depends on their ability to employ effective visual strategies. Quantifying the performance of the trainees is vitally important when assessing training effectiveness and developing future training requirements. The approach, attitudes and processes of an individual’s learning varies from one to another. In this light, some visual strategies may be better suited to the dynamics of a task environment than others, the result of which could be observed in the superior performance outcomes of some individuals. In this study, eye gaze data is used to investigate the relationship between performance outcomes and visual strategies. In an attempt to emulate real operational settings, a challenging task environment using multiple targets that had minimal salient features was selected for the study. Eye gaze of participants performing a simulation-based unmanned aerial vehicle (UAV) refuelling task was used to facilitate the investigation. Cross recurrence quantification analysis (CRQA) and Epistemic network analysis (ENA) were employed on eye gaze data to provide spatial-temporal mapping of visual strategies. A CRQA measure of recurrence rate was used to observe participants’ fixation interest on various regions of the task environment. The recurrence behaviours were categorised into cases of visual strategies using an unsupervised clustering algorithm. This article discusses the relationship between the visual strategy cases and performance outcomes to observe which are the most effective. Using the relationship between recurrence rates and performance outcomes, we demonstrate and discuss a gaze-based measure that could objectively quantify performance.

Human eye is a special kind of optical system, and its imaging quality and fatigue level seem susceptible to the illumination. In this study we were sought to develop a novel method to quantify ocular fatigue more accurately, and to assess the influence of light environment on ocular fatigue. Human factor experiments were performed on a total of 1249 participants. Among all physiological parameters, only accommodation and the 12th aberration presented significant variations during visual tasks. We deducted the ocular fatigue equation based on these two parameters together with other structural data. Regression equation and neural network were also constructed as complements. As a test, we predicted the ocular fatigue accumulations in various visual tasks. It was implied the predicted fatigue accumulations fell in separate ranges. It seems the novel method developed in this study could predict ocular fatigue accurately, and provide guidance to luminaire design.

Developmental dyscalculia (DD) is characterized by lower numerical and finger-related skills. Studies of enumeration among those DD that suggested core deficiency in pattern recognition, working memory or/and attention were mostly carried out in the visual modality. In our study, we examined visual (dots) enumeration of 1–10 stimuli and tactile (vibration) enumeration of 1–10 fingers among DD and matched-control adults. We used 800-ms stimuli exposure time of either random/non-neighboring or canonical/neighboring stimuli arrangements (visual/tactile). Compared to controls, those with DD responded faster in visual random enumeration and did not differ in reaction time (RT) of canonical stimuli arrangements. However, while the control group had near perfect accuracy in random stimuli arrangements of up to five stimuli, DD participants performed accurately for only up to four stimuli, and they were less accurate in the canonical stimuli arrangements in the counting range. In the tactile task, DD participants showed less accurate tactile enumeration only for neighboring arrangements, more profoundly for finger counting (FC) patterns. The longer exposure time in the visual task enabled us to explore pattern recognition effects when working memory and attention loads were low. We discuss possible modal-independent deficits in pattern recognition and working memory on enumeration performance among those with DD and the unique role of fingers in ordinal and cardinal representation of numbers.

The auditory cortex has been shown to participate in visual processing in individuals with complete auditory deprivation. However, it remains unclear whether partial hearing deprivation like single-sided deafness (SSD) leads to similar cross-modal plasticity. To investigate this, we enrolled individuals with long-term SSD, into functional MRI scans under resting-state and a visuo-spatial working memory task. Contrary to previous findings in bilateral deafness, our study revealed decreased activation in the auditory cortex in both left (LSSD) and right (RSSD) single-sided deafness compared to normal hearing controls, with statistical significance in RSSD. The degree of involvement was correlated with residual hearing ability in RSSD. These observations suggest that SSD can lead to a downward cross-modal plasticity: the more hearing ability lost, the fewer brain resources in the auditory cortex can be applied to visual tasks. In addition, the fronto-parietal cortex was observed to be less activated during the visual task in RSSD while the resting-state fMRI revealed increased functional connectivity between the fronto-parietal cortex and the auditory cortex, suggesting fronto-parietal resources may be recruited less by vision but more by hearing. The LSSD showed a similar alteration trend with RSSD, but without statistical significance. Together these findings may indicate that when hearing is partially deprived in SSD, there may be redistribution for brain resources between hearing and vision, and vision tends to allocate less resources. Our findings in this pilot study of unilateral auditory-deprived individuals enrich the understanding of cross-modal plasticity in the brain.

Evidence from recent studies on attention and consciousness has raised many questions about their inherent natures and the existence of a possible relationship between them. The main goal of this study is to investigate the significant difference among different states of attention and consciousness, through the connectivity method. These two cognitive phenomena have been studied in recent years with different approaches, but none of them has employed connectivity methods to study the attention and consciousness relationship. Therefore, the connectivity approach is a novel effort in this field. The 8-channel Electroencephalogram signal (EEGs) was used from 45 participants performing a psychophysical visual task. To track the variation of connectivity during time, the EEG recorded data were organized in a particular way, providing 9 1 s signals, including four stimuli classes: attention-consciousness class, attention-unconsciousness class, inattention-consciousness class, and inattention-unconsciousness class. In order to reduce the volume conduction effect, source signals were extracted with the ICA method. The effective connectivity network was computed using the Granger causality method. For the statistical analysis, connectivity indices were presented. This approach suggests that attention-consciousness and attention-unconsciousness classes, and attention-unconsciousness and inattention-unconsciousness classes are the most and least distinctive combinations, respectively. In a more general view provided by averaging the connectivity matrices, all the presented connectivity indices showed significant differences with p-value

In this paper, illumination coverage is proposed to optimize the illumination performance of the visual task. The coverage of illumination is considered on the basis of traditional visual coverage task. A detailed illumination model is proposed to describe the parameters of the spot illumination sensor. Three criteria called Illumination Attenuation, Field of Illumination, and Shading are introduced and combined with other visual criteria to define the illumination coverage strength. The illumination coverage performance of a single-camera coverage task with multi-illumination sensor is optimized by maximizing the constructed cost function. The simulation and experiment verify the effectiveness of the proposed optimization method of illumination coverage.

International audience; Patients with Parkinson’s disease (PD patients) have been shown to exhibit abnormally low levels of synergy in their posture control. The goal of this study is to determine how synergic interactions between vision and posture are affected in PD patients. These synergic interactions were expected to be impaired because PD affects the basal ganglia, which are involved in the modulation of both types of movement. Twenty patients (mean age: 60) on levodopa and 20 age-matched-controls (mean age: 61) performed a precise visual task (searching for targets in an image) and an unprecise control task (randomly looking at an image) in which images were projected onto a large panoramic display. Lower back, upper back, head and eye movements were recorded simultaneously. To test behavioural synergies, Pearson correlations between eye and postural movements were analysed. The relationships between eye movements and upper and lower back movements were impaired in the patients. The age-matched controls did not show any significant correlations between eye and postural movements. Overall, our results showed that the PD patients failed to adjust and control their postural stability for success in the visual task. The impaired synergy between eye and postural movements was not related to clinical variables - probably because our patients had early-stage PD. Our results showed that impairments in synergy can occur very early in PD. Hence, the analysis of this synergy might provide a better understanding of postural instability, visual task performance in the upright stance, and perhaps the risk of falls in PD patients.

Directed information flow between brain regions might be disrupted in children with Attention Deficit Hyperactivity Disorder (ADHD) which is related to the behavioral characteristics of ADHD. This paper aims to investigate the different information pathways of brain networks in children with ADHD in comparison with healthy subjects. EEG recordings were obtained from 61 children with ADHD and 60 healthy children without neurological disorders during attentional visual task. Effective connectivity among all scalp channels was calculated using directed phase transfer entropy (dPTE) for delta, theta, alpha, beta, and lower-gamma frequency bands. Group differences were evaluated using permutation tests in connectivity between regions. Significant posterior to anterior patterns of information flow in theta frequency bands were found in healthy subjects (p-value

We show how a simple autoencoder based deep network with a contrastive loss can effectively learn representations in a continual/incremental manner with limited labelling. This is of particular interest to the biomedical imaging research community, for whom the visual task is often a binary decision (healthy vs. disease) with limited quantity data and costly labelling. For such applications, the proposed method provides a light-weight option of 1) representing patterns with relatively few training samples using a novel collaborative contrastive loss function 2) update the autoencoder based deep network in an unsupervised fashion for continual learning for new incoming data. We overcome the drawbacks of existing methods through planned technical design, and demonstrate the efficacy of the proposed method on three histology image classification tasks (lung, colon, breast cancer) with SOTA results.

A fundamental natural visual task is the identification of specific target objects in the environments that surround us. It has long been known that some properties of the background have strong effects on target visibility. The most well-known properties are the luminance, contrast, and similarity of the background to the target. In previous studies, we found that these properties have highly lawful effects on detection in natural backgrounds. However, there is another important factor affecting detection in natural backgrounds that has received little or no attention in the masking literature, which has been concerned with detection in simpler backgrounds. Namely, in natural backgrounds the properties of the background often vary under the target, and hence some parts of the target are masked more than others. We began studying this factor, which we call the “partial masking factor,” by measuring detection thresholds in backgrounds of contrast-modulated white noise that was constructed so that the standard template-matching (TM) observer performs equally well whether or not the noise contrast modulates in the target region. If noise contrast is uniform in the target region, then this TM observer is the Bayesian optimal observer. However, when the noise contrast modulates then the Bayesian optimal observer weights the template at each pixel location by the estimated reliability at that location. We find that human performance for modulated noise backgrounds is predicted by this reliability-weighted TM (RTM) observer. More surprisingly, we find that human performance for natural backgrounds is also predicted by the RTM observer.

Background: Electrocardiogram (ECG) is a low-cost, inexpensive, non-invasive, and ubiquitous test to detect structural or electrical cardiac abnormalities. The ECG interpretation is a visual task to correlate specific patterns with diseases. Subtle ECG patterns that are invisible to the human eyes may be useful for patient risk stratification. We aimed to develop a deep neural network to predict mortality using standard 12-lead ECG. Methods: We obtained the entire clinical MUSE database of Chang Gung Memorial Hospital for standard resting 12-lead 10-sec ECG voltage-time traces, which were linked to the National Death Registry for all-cause and cause-specific mortality. Ten thousand patients remained alive at one year from the ECG examination date, and 10000 patients died within one year were randomly selected to train a one-dimensional deep neural network to predict mortality risk. Data was split into 16,000 patients for the training and 4,000 patients for the validation sets. We prepared a separate held-out dataset of 19,737 randomly selected patients whose ECG traces were fed to the model to predict their mortality risk. Results: The mean age of the held-out dataset was 60.0±16.7 years, and 50.0% were female. Among them, 3,807 died during a mean follow-up period of 6.0 years (maximum period, 14 years). The model achieved an area under the receiver operator curve of 0.85 on the held-out dataset. The age- and sex-weighted Kaplan-Meier curve for the mortality was shown in figure 1, which stratified by the model prediction for survival status (log-rank test, p < 0.001). Using a Cox proportional hazards model, the ECG algorithm predicted death is associated with an age- and sex-adjusted hazard ratio of 3.2 (95% confidence interval, 3.0-3.4) for all-cause mortality and 2.9 (95% CI, 2.4-3.5) for cardiovascular mortality. Conclusion: The deep learning model could extract prognostic information from standard 12-lead ECG and predict mortality with reasonable precision.

Eye blinks are vital components of human gaze which are used for assessing human behaviour. We have analyzed the variability of the inter-blink durations, termed as blink rate variability (BRV), for analysing sustained attention for visual tasks. Uniformly sampled BRV series is reconstructed from the gaze data recorded using an eye tracker. A number of features are extracted from this series. We proposed a new feature based on pareto principle. Results show that skewness, kurtosis, mean frequency and pareto frequency are good indicators of sustained attention. We observed that with increase in attention level, the power of BRV series tends to have a normal distribution whereas the mean and pareto frequency decreases. Results were generated on a small dataset as a proof of concept of our hypothesis that BRV is a potential bio-marker of sustained attention in a visual task.

Objective: The current investigation examined how a bout of soccer heading may impact brain function. Design: Semi-randomized crossover cohort. Setting: Controlled soccer heading. Participants: Seven male soccer players (24.1 ± 1.5 years). Intervention: 40 successful soccer headers were performed in 20 min (25 m, launch velocity ~80 km/h). X2 xPatch recorded linear and rotational head accelerations during each impact. A contact control “sham” condition – ball made body contact, but not by the head; and a no activity time “control” condition were also completed. Main Outcome Measures: Posterior and middle cerebral artery (PCA and MCA, respectively), cerebral blood velocity (CBV) was recorded during a visual task (neurovascular coupling: NVC) alongside SCAT3 symptoms scores pre/post a controlled bout of soccer heading. Results: Cumulative linear and rotational accelerations were 1,574 ± 97.9 g and 313,761 ± 23,966 rads/s2, respectively, during heading and changes in SCAT3 symptom number (pre: 2.6 ± 3.0; post: 6.7 ± 6.2, p = 0.13) and severity (pre: 3.7 ± 3.6, post: 9.4 ± 7.6, p = 0.11) were unchanged. In the PCA, no NVC differences were observed, including: relative CBV increase (28.0 ± 7.6%, p = 0.71) and total activation (188.7 ± 68.1 cm, p = 0.93). However, MCA-derived NVC metrics were blunted following heading, demonstrating decreased relative CBV increase (7.8 ± 3.1%, p = 0.03) and decreased total activation (26.7 ± 45.3 cm, p = 0.04). Conclusion: Although an acute bout of soccer heading did not result in an increase of concussion-like symptoms, there were alterations in NVC responses within the MCA during a visual task. This suggests an acute bout of repetitive soccer heading can alter CBV regulation within the region of the brain associated with the header impacts.

Medical images are acquired at different resolutions based on clinical goals or available technology. In general, however, high-resolution images with fine structural details are preferred for visual task analysis. Recognizing this significance, several deep learning networks have been proposed to enhance medical images for reliable automated interpretation. These deep networks are often computationally complex and require a massive number of parameters, which restrict them to highly capable computing platforms with large memory banks. In this paper, we propose an efficient deep learning approach, called Hydra, which simultaneously reduces computational complexity and improves performance. The Hydra consists of a trunk and several computing heads. The trunk is a super-resolution model that learns the mapping from low-resolution to high-resolution images. It has a simple architecture that is trained using multiple scales at once to minimize a proposed learning-loss function. We also propose to append multiple task-specific heads to the trained Hydra trunk for simultaneous learning of multiple visual tasks in medical images. The Hydra is evaluated on publicly available chest X-ray image collections to perform image enhancement, lung segmentation, and abnormality classification. Our experimental results support our claims and demonstrate that the proposed approach can improve the performance of super-resolution and visual task analysis in medical images at a remarkably reduced computational cost.

Patients with alcohol use disorder (AUD) have difficulties controlling alcohol cravings and thus exhibit increased use and earlier relapse. Although patients tend to respond more strongly to alcohol-related images compared with non-alcohol-related images, few researchers examined the factors that modulate cravings. Here, we examined whole-brain blood oxygen level-dependent (BOLD) responses to behavioural cues in individuals with AUD and healthy controls (HCs). The participants included 24 patients with severe AUD and 15 HCs. We presented four beverage images (juice, drinking juice, sake, and drinking sake) and compared participant BOLD responses between the two groups. Multiple comparisons revealed that the AUD group had lower BOLD responses compared with the HC group to images of drinking juice in the left precuneus (p = 0.036) and the left posterior cingulate cortex (PCC) (p = 0.044) and higher BOLD responses to images of drinking sake in the left PCC (p = 0.044). Furthermore, compared to the HCs, the AUD patients had decreased BOLD responses associated with cue reactivity to drinking juice in the left precuneus during the period from 15 to 18 s (p = 0.004, df = 37) and 18 to 21 s (p = 0.002, df = 37). Using the Spearman correlation, we found a significant negative correlation between BOLD responses in the left PCC of the AUD patients and Mini–Mental State Examination (MMSE) scores (r = −0.619, p = 0.001). Our findings suggest that HCs and severe AUD patients differ in their responses not to images of alcoholic beverages but those related to alcohol drinking behavior. Thus, these patients appear to have different patterns of brain activity. This information may aid clinicians in developing treatments for patients with AUD.

This paper presents an approach for saliency detection able to emulate the integration of the top-down (task-controlled) and bottom-up (sensory information) processes involved in human visual attention. In particular, we first learn how to generate saliency when a specific visual task has to be accomplished. Afterwards, we investigate if and to what extent the learned saliency maps can support visual classification in nontrivial cases. To achieve this, we propose SalClassNet, a CNN framework consisting of two networks jointly trained: a) the first one computing top-down saliency maps from input images, and b) the second one exploiting the computed saliency maps for visual classification. To test our approach, we collected a dataset of eye-gaze maps, using a Tobii T60 eye tracker, by asking several subjects to look at images from the Stanford Dogs dataset, with the objective of distinguishing dog breeds. Performance analysis on our dataset and other saliency benchmarking datasets, such as POET, showed that SalClassNet outperforms state-of-the-art saliency detectors, such as SalNet and SALICON. Finally, we also analyzed the performance of SalClassNet in a fine-grained recognition task and found out that it yields enhanced classification accuracy compared to Inception and VGG-19 classifiers. The achieved results, thus, demonstrate that 1) conditioning saliency detectors with object classes reaches state-of-the-art performance, and 2) explicitly providing top-down saliency maps to visual classifiers enhances accuracy.

Object detection is one of the most significant visual tasks in a road. So, artificial, lighting used in a road have a greater importance in visual task performance. In this, paper an attempt is made to simulate the road lighting situation for measuring the, ability of road users to detect object under different color temperature (CCT) of the light, source. The effect of color temperature of peripheral source on object detection is, investigated in this work with 20 neurologically and physiologically healthy subjects., The experiment was repeated with two types of lighting situations under four different, colour temperature (CCT) of the light source. The reaction/response time data along, with object colour perception under different lighting condition are recorded for further, analysis. Finally, it has been found that the colour temperature of light source has an, influence on the response time of the user

Background Objective measures have been shown to be equally sensitive in different cultures. However, these measures need special devices that are relatively expensive and need expertise to analyze the result. In Indonesia, there is a need for a sensitive and affordable mental workload measure. Objective To evaluate the sensitivity of Galvanic Skin Response (GSR) in assessing mental workload in Indonesia. Participants A total of 72 Indonesian students with normal visual capability. Method Participants were asked to work on visual memory search task with a secondary task of counting with three different levels of difficulty. GSR, Heart Rate Variability (HRV), and the NASA-TLX were administered prior to, during, and after the tasks. Results GSR measure was compared to NASA-TLX and HRV measures. Like the HRV, GSR showed to be sensitive in distinguishing rest and task condition significantly but not sensitive in distinguishing different levels of mental workload. In contrast, both the NASA-TLX and performance measure were sensitive in differentiating different levels of mental workload. Conclusions GSR has potential as a simple, cost-effective tool for measuring mental workload in Indonesia.

In Viticulture, visual inspection of the plant is a necessary task for measuring relevant variables. In many cases, these visual inspections are susceptible to automation through computer vision methods. Bud detection is one such visual task, central for the measurement of important variables such as: measurement of bud sunlight exposure, autonomous pruning, bud counting, type-of-bud classification, bud geometric characterization, internode length, bud area, and bud development stage, among others. This paper presents a computer method for grapevine bud detection based on a Fully Convolutional Networks MobileNet architecture (FCN-MN). To validate its performance, this architecture was compared in the detection task with a strong method for bud detection, Scanning Windows (SW) based on a patch classifier, showing improvements over three aspects of detection: segmentation, correspondence identification and localization. The best version of FCN-MN showed a detection F1-measure of $88.6\%$ (for true positives defined as detected components whose intersection-over-union with the true bud is above $0.5$), and false positives that are small and near the true bud. Splits -- false positives overlapping the true bud -- showed a mean segmentation precision of $89.3\% (21.7)$, while false alarms -- false positives not overlapping the true bud -- showed a mean pixel area of only $8\%$ the area of a true bud, and a distance (between mass centers) of $1.1$ true bud diameters. The paper concludes by discussing how these results for FCN-MN would produce sufficiently accurate measurements of bud variables such as bud number, bud area, and internode length, suggesting a good performance in a practical setup., Comment: Revised version submitted to Journal of Computers and Electronics in Agriculture November 13, 2020

Purpose. To investigate the effects of chewing gum and tablet candy to reduce eyestrain in healthy individuals. Materials and Methods. A double-blinded crossover trial was conducted. Forty-six healthy individuals (23 men, 23 women) between 20 and 59 years old, feeling eyestrain, were enrolled. Each 10-year age group included 12 individuals except the 30s group, which included 10 individuals. A visual task was performed on reading material displayed on a computer screen at a fixed distance for 60 min. Gum or tablet candy of two pieces were chewed for two 15-min periods starting 15 and 45 min after starting to read. Subjects chewed gum on Day 1 and tablet candy on Day 2, and vice versa. Primary outcome is as follows: subjective eye fatigue (eye tiredness, eye heaviness, blurred vision, double vision, and eye dryness) using a visual analog scale (VAS). Secondary outcomes are as follows: subjective accommodation from near and far points of accommodation measured with a D’ACOMO, spherical equivalent refraction, and eye dryness by analyzing ring break-up time (RBUT) measured with the RT-7000 Auto Ref-Topographer. Results. The VAS scores of subjective eye fatigue were not significantly changed between chewing gum and tablet candy ( P = 0.397 - P = 0.909 ). Those scores of eye tiredness and eye heaviness were significantly longer before and after the visual task with tablet candy ( P = 0.013 and P = 0.025 , respectively) but not with chewing gum. The changes of subjective accommodation were significantly lower after the visual task between chewing gum and candy ( P = 0.043 ). There were significant differences among each age group (20 s vs. 30 s, P = 0.594 ; 20 s vs. 40 s, P = 0.002 ; 20 s vs. 50 s, P = 0.002 ). After reading, the changes of spherical equivalent refraction did not indicate a shift toward myopia ( P = 0.267 ). In the RBUT, there were no significant differences between the samples ( P = 0.680 ). Conclusions. Chewing gum helps improve the ability of the eye to focus, especially in young adults.

Background: To maximize the effect of intravenous (IV) thrombolysis and/or endovascular therapy (EVT) for acute ischemic stroke (AIS), stroke centers need to establish a parallel workflow on the basis of a code stroke (CS) protocol. At Kokura Memorial Hospital (KMH), we implemented a CS system in January 2014; however, the process of information sharing within the team has occasionally been burdensome. Objective: To solve this problem using information communication technology (ICT), we developed a novel application for smart devices, named “Task Calc. Stroke” (TCS), and aimed to investigate the impact of TCS on AIS care. Methods: TCS can visualize the real-time progress of crucial tasks for AIS on a dashboard by changing color indicators. From August 2015 to March 2017, we installed TCS at KMH and recommended its use during normal business hours (NBH). We compared the door-to-computed tomography time, the door-to-complete blood count (door-to-CBC) time, the door-to-needle for IV thrombolysis time, and the door-to-puncture for EVT time among three treatment groups, one using TCS (“TCS-based CS”), one not using TCS (“phone-based CS”), and one not based on CS (“non-CS”). A questionnaire survey regarding communication problems was conducted among the CS teams at 3 months after the implementation of TCS. Results: During the study period, 74 patients with AIS were transported to KMH within 4.5 h from onset during NBH, and 53 were treated using a CS approach (phone-based CS: 26, TSC-based CS: 27). The door-to-CBC time was significantly reduced in the TCS-based CS group compared to the phone-based CS group, from 31 to 19 min (p = 0.043). Other processing times were also reduced, albeit not significantly. The rate of IV thrombosis was higher in the TCS-based CS group (78% vs. 46%, p = 0.037). The questionnaire was correctly filled in by 34/38 (89%) respondents, and 82% of the respondents felt a reduction in communication burden by using the TCS application. Conclusions: TCS is a novel approach that uses ICT to support information sharing in a parallel CS workflow in AIS care. It shortens the processing times of critical tasks and lessens the communication burden among team members.

Previous studies have shown that liquid crystal display (LCD) can cause visual fatigue to the human eye, but the effect of quantum dot (QD) display has not been explored yet. This study conducted a human factor experiment on the QD display and LCD. The parameters ACC, HOAs and MTF were selected as objective physiological indicators for visual quantification of visual fatigue. 39 participants performed a 45-minute video viewing task. While before and after the visual task, measured the physiological parameters of the participants' eyes. Analysis the effects of QD display and LCD on human physiological characteristics under the same conditions. The results show that: (1) The QD display and LCD have an influence on the physiological characteristics of the human eye during continuous visual task duration. These effects can be quantified by changes in human eye physiological parameters; (2) The effect of QD display on human eye physiological parameters is less than LCD: the VICO index (visual comfort index) is lower, and the participants' color feedback accuracy is higher. This study provides theoretical basis and data support for the subsequent development of quantum dot display.

The illumination environment is extremely important to the visual-related operation/interface design, due to its great effect on visual operation. Therefore, the influence of illumination environment factors, such as illumination and color temperature, on visual operation needs to be investigated deeply. In this study, five illumination environment levels, combined by illumination and color temperature, were selected to carry out ergonomic experiments. The screen brightness of high, medium and low was set, and the internal experiment of two-factor subjects was conducted based on the visual search task. Behavioral performance data and subjective evaluation data of 16 subjects were collected and analyzed. The results show that, in terms of response time, correct rate, and subjective evaluation, the main effects of illumination and screen brightness are significant.

BACKGROUND: Binocular amblyopia treatments promote visual acuity recovery and binocularity by rebalancing the signal strength of dichoptic images. Most require active participation by the amblyopic child to play a game or perform a repetitive visual task. The purpose of this study was to investigate a passive form of binocular treatment with contrast-rebalanced dichoptic movies. METHODS: A total of 27 amblyopic children, 4–10 years of age, wore polarized glasses to watch 6 contrast-rebalanced dichoptic movies on a passive 3D display during a 2-week period. Amblyopic eye contrast was 100%; fellow eye contrast was initially set to a lower level (20%−60%), which allowed the child to overcome suppression and use binocular vision. Fellow eye contrast was incremented by 10% for each subsequent movie. Best-corrected visual acuity, random dot stereoacuity, and interocular suppression were measured at baseline and at 2 weeks. RESULTS: Amblyopic eye best-corrected visual acuity improved from 0.57 ± 0.22 at baseline to 0.42 ± 0.23 logMAR (t(26) = 8.09; P < 0.0001; 95% CI for improvement, 0.11–0.19 logMAR). Children aged 3–6 years had more improvement (0.21 ± 0.11 logMAR) than children aged 7–10 years (0.11 ± 0.06 logMAR; t(25) = 3.05; P = 0.005). Children with severe amblyopia (≥0.7 logMAR) at baseline experienced greater improvement (0.24 ± 0.12 logMAR) than children with moderate amblyopia at baseline (0.12 ± 0.06 logMAR; t(25) = 3.49; P = 0.002). CONCLUSIONS: In this cohort, passive viewing of contrast-rebalanced dichoptic movies effectively improved visual acuity in amblyopic subjects. The degree of improvement observed was similar to that previously reported for 2 weeks of binocular games treatment and with 3–4 months of occlusion therapy.

This study aimed to evaluate objective and subjective visual fatigue experienced before and after performing a visual task while using a head-mounted display for virtual reality (VR-HMD) and two-dimensional (2D) display. Binocular fusion maintenance (BFM) was measured using a binocular open-view Shack-Hartmann wavefront aberrometer equipped with liquid crystal shutters. Twelve healthy subjects performed the BFM test and completed a questionnaire regarding subjective symptoms before and after performing a visual task that induces low visually induced motion sickness (VIMS). BFM (p = .87) and total subjective eye symptom scores (p = .38) were not significantly different between both groups, although these values were significantly lower after the visual task than before the task within both groups (p < .05). These findings suggest that visual fatigue after using a VR-HMD is not significantly different from that after using a 2D display in the presence of low-VIMS VR content. Practitioner summary: Objective and subjective evaluation of visual fatigue were not significantly different with the use of a head-mounted display for virtual reality (VR-HMD) and two-dimensional display. These results should be valuable not only to engineers developing VR content but also to researchers involved in the evaluation of visual fatigue using VR-HMD. Abbreviations: VR: virtual reality; VR-HMD: head-mounted display for virtual reality; BFM: binocular fusion maintenance; BWFA: binocular open-view Shack-Hartmann wavefront aberrometer.

Objective: A set of 4 driving related tasks were used to evaluate the potential for a modified Detection Response Task (DRT) to simultaneously measure visual and cognitive task demands. Background: The accurate assessment of cognitive and visual tasks demands in driving has become increasingly important. As of yet, no simple, cost effective approach has been found to measure visual demands in complex, multimodal tasks. Methods: Two experiments are presented which evaluate an extension of the standard DRT methodology. The discriminate sensitivity of the experiments is tested using an integrated testing configuration, which systematically increased visual demand across four conditions. Results: Results suggest that the standard DRT configurations are highly tuned to selectively evaluate cognitive demand but that a variant of the system may be able to simultaneously evaluate changes in both visual and cognitive task demands. Conclusions: These data suggest that the simple, rapid, and reliable assessment of both visual and cognitive task demands is possible, even in highly fluid systems with non-constant visual task requirements.

This study explores the patterns of activation in brain regions toward classifying decision making voxels from among four major Brodmann areas (BAs) upon stimulus of visual tasks. Toward this goal, a well-known clustering analysis has been performed on real-time data of the human brain obtained using functional magnetic resonance imaging (fMRI). The functional connectivity among various brain regions was detected by leveraging a distance correlation graph. Graphical methods have been employed to visualize the clusters elicited in the process. The analysis of the results sheds new light on how four significantly activated BAs of the brain exhibit effective connectively to perform a visual task in the context of decision making.

Purpose: The aim of this study was to create vision standards for various tasks performed by hairdressers and to assess the spectacle compliance and its impact at work. Methods: The observational cross-sectional study enrolled hairdressers in and around Chennai, Tamil Nadu. It was done in three phases: (i) Job profiling from visual task analysis, creating vision standards for various hairdressing tasks and arriving at test protocols; (ii) Comprehensive eye examination, and (iii) Assessment of spectacle compliance and its impact on work. Descriptive analysis using Microsoft Excel and SPSS (IBM SPSS Statistics Version 21.0) was performed. Results: There were 305 participants with a mean age of 48 (SD ± 12) years. The visual acuity demand was found to be 6/18 and N15, for distance and near, respectively. Appropriate spectacles were prescribed for 203 (67%) hairdressers. Even with the best possible refractive correction, a few hairdressers did not meet the distance (13) and near (11) visual acuity standard. In all, 54 hairdressers were referred for further examination to a tertiary eye care center for lenticular changes, retinal abnormalities, and glaucoma screening. Among the subjects who were dispensed with spectacles, 181 (86%) were available for telephonic spectacle compliance assessment, and 164 (90%) were compliant with spectacle usage at work. Improved visual ability was reported by 133 (81%) hairdressers at work. Conclusion: This study provides vision standards for hairdressers. From the visual task analysis, hairdressing tasks were found to be visually demanding and hazardous. The study emphasizes that providing appropriate spectacle correction showed a clinically evident positive impact at work.

Phonological short-term memory (STM) and working memory (WM) capacity, which is temporal storage of phonological information, facilitates language development. This capacity is often impaired in cochlear implant (CI) users who have congenital hearing loss. Functional near-infrared spectroscopy (fNIRS) is potentially useful to reveal underlying mechanisms of this impairment due to its tolerance to magnetic and electrical artifacts generated by CIs. The spatial resolution of the standard fNIRS, however, seems inadequate to evaluate cortical activity associated with the maintenance of phonological information in the STM/WM tasks. In the present study recruiting 14 normal hearing adults, we applied a double density alignment of fNIRS optodes to improve spatial resolution in the generalized linear model (GLM)-based statistical analysis using NIRS-SPM, in which cortical activities were estimated during each of three stages (encoding, maintenance, and retrieval) in pseudoword STM tasks with auditory or visual presentation. Since the double density alignment of fNIRS optodes contains two sets of standard density arrays, in the off-line analysis the measured cortical hemodynamic responses can be analyzed as data from two independent standard density arrays as well as those from one double density array (DD-array) which has two times higher density of channels. The two standard arrays demonstrated a similar pattern of cortical activation at each stage of the auditory and visual tasks, which proved the reliability of our fNIRS analysis, but failed to detect significant cortical activation in 2 of 12 conditions including the maintenance stage in the visual task. On the other hand, DD-array revealed significant cortical activation in all conditions. These differences were observed when estimated cortical activation was localized in small regions, which suggests higher spatial resolution in DD-array than the standard arrays. In our knowledge, this is the first clinical study supporting the previous experimental phantom study which demonstrated improvement of spatial resolution in the double density arrangement of fNIRS optodes. These findings imply that the double density alignment of fNIRS optodes improves reliability and spatial resolution in fNIRS-based estimation of cortical activity in the STM/WM studies, although further studies are required to determine usefulness of this method in the CI population.

A common way of interacting with conversational agents is through voice commands. Finding appropriate voice commands can be a challenge for developers and often require empirical methods where participants come up with voice commands for specific tasks. Textual and visual task representations were compared in an online study to assess the influence of semantic priming on spontaneous, user-generated voice commands. Our results indicate that visual representations of tasks lead to a different distribution of used phrases, compared to the textual representation, within the target population. Furthermore, the results suggest that text stimuli can be used to influence user utterances.

We present a computational observer model of the human spatial contrast sensitivity (CSF) function based on the Image Systems EngineeringTools for Biology (ISETBio) simulation framework. We demonstrate that ISETBio-derived CSFs agree well with CSFs derived using traditional ideal observer approaches, when the mosaic, optics, and inference engine are matched. Further simulations extend earlier work by considering more realistic cone mosaics, more recent measurements of human physiological optics, and the effect of varying the inference engine used to link visual representations to psy-chohysical performance. Relative to earlier calculations, our simulations show that the spatial structure of realistic cone mosaics reduces upper bounds on performance at low spatial frequencies, whereas realistic optics derived from modern wavefront measurements lead to increased upper bounds high spatial frequencies. Finally, we demonstrate that the type of inference engine used has a substantial effect on the absolute level of predicted performance. Indeed, the performance gap between an ideal observer with exact knowledge of the relevant signals and human observers is greatly reduced when the inference engine has to learn aspects of the visual task. ISETBio-derived estimates of stimulus representations at different stages along the visual pathway provide a powerful tool for computing the limits of human performance.

High-throughput behavioral training of rodents has been a transformative development for systems neuroscience. Water or food restriction is typically required to motivate task engagement. We hypothesized a gap between physiological water need and hedonic water satiety that could be leveraged to train rats for water rewards without water restriction. We show that when Citric Acid (CA) is added to water, female rats drink less, yet consume enough to maintain long term health. With 24 h/day access to a visual task with water rewards, rats with ad lib CA water performed 84% ± 18% as many trials as in the same task under water restriction. In 2-h daily sessions, rats with ad lib CA water performed 68% ± 13% as many trials as under water restriction. Using reward sizes

Purpose To investigate visual performance during reading under different illumination sources. Methods This experimental quantitative study included 40 (20 females and 20 males) emmetropic participants with no history of ocular pathology. The participants were randomly assigned to read a near visual task under four different illuminations (400-lux constant): compact fluorescent light (CFL), tungsten light (TUNG), fluorescent tube light (FLUO), and light emitting diode (LED). Subsequently, we evaluated the participants' experiences of eight symptoms of visual comfort. Results The mean age of the participants was 19.86 ± 1.09 (range: 18-21) years. There was no statistically significant difference between the reading rates of males and females under the different illuminations (P = 0.99); however, the reading rate was fastest among males under CFL, and among females under FLUO. One way analysis of variance (ANOVA) revealed a strong significant difference (P = 0.001) between males and females (P = 0.002) regarding the visual performance and illuminations. Conclusion This study demonstrates the influence of illumination on reading rate; there were no significant differences between males and females under different illuminations, however, males preferred CFL and females preferred FLUO for faster reading and visual comfort. Interestingly, neither preferred LED or TUNG. Although energy-efficient, visual performance under LED is poor; it is uncomfortable for prolonged reading and causes early symptoms of fatigue.

Introduction: Visual search is a task that humans perform in everyday life. Whether it involves looking for a pen on a desk or a mass in a mammogram, the cognitive and perceptual processes that underpin these tasks are identical. Radiologists are experts in visual search of medical images and studies on their visual search behaviours have revealed some interesting findings with regard to diagnostic errors. In Australia, within the modality of ultrasound, sonographers perform the diagnostic scan, select images and present to the radiologist for reporting. Therefore the visual task and potential for errors is similar to a radiologist. Our aim was to explore and understand the detection, localisation and eye‐gaze behaviours of a group of qualified sonographers. Method: We measured clinical performance and analysed diagnostic errors by presenting fifty sonographic breast images that varied on cancer present and degree of difficulty to a group of sonographers in their clinical workplace. For a sub‐set of sonographers we obtained eye‐tracking metrics such as time‐to‐first fixation, total visit duration and cumulative dwell time heat maps. Results: The results indicate that the sonographers' clinical performance was high and the eye‐tracking metrics showed diagnostic error types similar to those found in studies on radiologist visual search. Conclusion: This study informs us about sonographer visual search patterns and highlights possible ways to improve diagnostic performance via targeted education.

1.AbstractThere is increasing interest in understanding how the phase and amplitude of distinct neural oscillations might interact to support dynamic communication within the brain. In particular, previous work has demonstrated a coupling between the phase of low frequency oscillations and the amplitude (or power) of high frequency oscillations during certain tasks, termed phase amplitude coupling (PAC). For instance, during visual processing in humans, PAC has been reliably observed between ongoing alpha (8-13Hz) and gamma-band (>40Hz) activity. However, the application of PAC metrics to electrophysiological data can be challenging due to numerous methodological issues and lack of coherent approaches within the field. Therefore, in this article we outline the various analysis steps involved in detecting PAC, using an openly available MEG dataset from 16 participants performing an interactive visual task. Firstly, we localised gamma and alpha-band power using the Fieldtrip toolbox, and extracted time courses from area V1, defined using a multimodal parcellation scheme. These V1 responses were analysed for changes in alpha-gamma PAC, using four common algorithms. Results showed an increase in gamma (40-100Hz) - alpha (7-13Hz) PAC in response to the visual grating stimulus, though specific patterns of coupling were somewhat dependent upon the algorithm employed. Additionally, post-hoc analyses showed that these results were not driven by the presence of non-sinusoidal oscillations, and that trial length was sufficient to obtain reliable PAC estimates. Finally, throughout the article, methodological issues and practical guidelines for ongoing PAC research will be discussed.

The new version of Diagnostic and Statistical Manual of Mental Disorders (DSM-5th) proposed the Internet Gaming Disorder for the diagnosis of Internet addiction (IA) considering the neurobiological evidence of the craving.The aim was to test the neural correlate in response to the Internet cue in patients with IA.Sixteen males with IA diagnosis (clinical group) and 14 healthy male (control group) were recruited for an experimental visual task composed of Internet images and emotional images. During the visual presentation of Internet cue, electroencefalographic data were recorded using Net Station 4.5.1 with a 256-channels HydroCel Geodesic Sensor Net. Event-related potential (ERP) components and low-resolution electromagnetic tomography (sLoreta) were analysed.sLoreta analyses showed that patients from the clinical group presented a higher primary somatosensorial cortex and lower paralimbic, temporal and orbito-frontal activation in response to both Internet and emotional images compared to those of the control group.These results suggest that clinically recognized pathological use of Internet could be linked to dissociative symptoms.

Background Visual demands of school children tend to vary with diverse classroom environments. The study aimed to evaluate the distance and near Visual Acuity (VA) demand in Indian school classrooms and their comparison with the recommended vision standards. Materials and methods The distance and near VA demands were assessed in 33 classrooms (grades 4 to 12) of eight schools. The VA threshold demand relied on the smallest size of distance and near visual task material and viewing distance. The logMAR equivalents of minimum VA demand at specific seating positions (desk) and among different grades were evaluated. The near threshold was converted into actual near VA demand by including the acuity reserve. The existing dimensions of chalkboard and classroom, gross area in a classroom per student and class size in all the measured classrooms were compared to the government recommended standards. Results In 33 classrooms assessed (35±10 students per room), the average distance and near logMAR VA threshold demand was 0.31±0.17 and 0.44±0.14 respectively. The mean distance VA demand (minimum) in front desk position was 0.56±0.18 logMAR. Increased distance threshold demand (logMAR range -0.06, 0.19) was noted in 7 classrooms (21%). The mean VA demand in grades 4 to 8 and grades 9 to 12 was 0.35±0.16 and 0.24±0.16 logMAR respectively and the difference was not statistically significant (p = 0.055). The distance from board to front desk was greater than the recommended standard of 2.2m in 27 classrooms (82%). The other measured parameters were noted to be different from the proposed standards in majority of the classrooms. Conclusion The study suggests the inclusion of task demand assessment in school vision screening protocol to provide relevant guidance to school authorities. These findings can serve as evidence to accommodate children with mild to moderate visual impairment in the regular classrooms.

Octopuses (Octopus vulgaris) are generally considered to possess extraordinary cognitive abilities including the ability to successfully perform in a serial reversal learning task. During reversal learning, an animal is presented with a discrimination problem and, after reaching a learning criterion, the signs of the stimuli are reversed: the former positive becomes the negative stimulus and vice versa. If an animal improves its performance over reversals, it is ascribed advanced cognitive abilities. Reversal learning has been tested in octopus in a number of studies. However, the experimental procedures adopted in these studies involved pre-training on the new positive stimulus after a reversal, strong negative reinforcement or might have enabled secondary cueing by the experimenter. These procedures could have all affected the outcome of reversal learning. Thus in this study, serial visual reversal learning was revisited in octopus. We trained four common octopuses (Octopus vulgaris) to discriminate between 2-dimensional stimuli presented on a monitor in a simultaneous visual discrimination task and reversed the signs of the stimuli each time the animals reached the learning criterion of ≥80% in two consecutive daily sessions. The animals were trained using operant conditioning techniques including a secondary reinforcer, a rod that was pushed up and down the feeding tube, which signaled the correctness of a response and preceded the subsequent primary reinforcement of food. The experimental protocol did not involve negative reinforcement. One animal completed four reversals and showed progressive improvement, i.e. it decreased its errors to criterion the more reversals it experienced. This animal developed a generalized response strategy. In contrast, another animal completed only one reversal, whereas two animals did not learn to reverse during the first reversal. In conclusion, some octopus individuals can learn to reverse in a visual task demonstrating behavioral flexibility even with a refined methodology.

Large screens have become more popular in recent years. Because of the increasing size of displays, the amount of information presented in the peripheral visual field has gained importance in many tasks on visual display units. Users of displays are often exposed to some change or difference in luminance in or between different areas of a display, which in turn may produce a phenomenon known as discomfort glare. Discomfort glare is likely to affect cognitive performance. The performance in the visual periphery is more susceptible to disturbances as is the case for the performance in the central visual field. This study explored the effects of discomfort glare on detecting and processing peripheral visual information in a complex visual task. The task consisted of comparing the orientation of arrows presented in the central visual field and at 18° in the periphery. The arrows were superimposed on a background video and presented by a projection system in virtual reality. 50% of the presentations were preceded by a mild glare scene with a luminance of 25 cd/m2 flashed prior to the stimulus. Experimental results of 56 participants were analyzed using the theory of signal detection. A significant difference (two-tailed t-test p = 0.01) in detectability of stimuli (d′glare = 1.87; d′no glare = 2.11; Δd′ = 0.24) was obtained when comparing the performance in the two situations of glare. Results show that discomfort glare impairs peripheral visual performance in attending stimuli in a virtual reality environment. We therefore propose to consider discomfort glare as a factor affecting performance in detecting peripheral visual information. Discomfort glare should be included as a quality criterion in rating visual information, as is done in present standards of displays and lighting.