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Mental effort (intensity of attention) in elite sports has remained a debated topic and a challenging phenomenon to measure. Thus, a quasi-ecological laboratory study was conducted to investigate mental effort in elite rowers as compared with a group of nonelites. Findings suggest that eye-tracking measures—specifically, blink rates and pupil size—can serve as valid indicators of mental effort in physically demanding sport tasks. Furthermore, findings contradict the notion that elite athletes spend less cognitive effort than their lower-level peers. Specifically, elites displayed similar levels of self-reported effort and performance decrement with increasing mental load and significantly more mental effort overall as measured by pupil-size increase (relative to baseline) during rowing trials as compared with the nonelites in the sample. Future studies on eye tracking in sports may include investigations of mental effort in addition to selective attention during physically demanding tasks. [ABSTRACT FROM AUTHOR]

Eye tracking is prevalent in scientific and commercial applications. Recent computer vision and deep learning methods enable eye tracking with off-the-shelf webcams and reduce dependence on expensive, restrictive hardware. However, such deep learning methods have not yet been applied and evaluated for remote, online psychological experiments. In this study, we tackle critical challenges faced in remote eye tracking setups and systematically evaluate appearance-based deep learning methods of gaze tracking and blink detection. From their own homes and laptops, 65 participants performed a battery of eye tracking tasks including (i) fixation, (ii) zone classification, (iii) free viewing, (iv) smooth pursuit, and (v) blink detection. Webcam recordings of the participants performing these tasks were processed offline through appearance-based models of gaze and blink detection. The task battery required different eye movements that characterized gaze and blink prediction accuracy over a comprehensive list of measures. We find the best gaze accuracy to be 2.4° and precision of 0.47°, which outperforms previous online eye tracking studies and reduces the gap between laboratory-based and online eye tracking performance. We release the experiment template, recorded data, and analysis code with the motivation to escalate affordable, accessible, and scalable eye tracking that has the potential to accelerate research in the fields of psychological science, cognitive neuroscience, user experience design, and human–computer interfaces. [ABSTRACT FROM AUTHOR]

A hand passing in front of a camera produces a large and obvious disruption of a video. Yet the closure of the eyelid during a blink, which lasts for hundreds of milliseconds and occurs thousands of times per day, typically goes unnoticed. What are the neural mechanisms that mediate our uninterrupted visual experience despite frequent occlusion of the eyes? Here, we review the existing literature on the neurophysiology, perceptual consequences, and behavioral dynamics of blinks. We begin by detailing the kinematics of the eyelid that define a blink. We next discuss the ways in which blinks alter visual function by occluding the pupil, decreasing visual sensitivity, and moving the eyes. Then, to anchor our understanding, we review the similarities between blinks and other actions that lead to reductions in visual sensitivity, such as saccadic eye movements. The similarity between these two actions has led to suggestions that they share a common neural substrate. We consider the extent of overlap in their neural circuits and go on to explain how recent findings regarding saccade suppression cast doubt on the strong version of the shared mechanism hypothesis. We also evaluate alternative explanations of how blink-related processes modulate neural activity to maintain visual stability: a reverberating corticothalamic loop to maintain information in the face of lid closure; and a suppression of visual transients related to lid closure. Next, we survey the many areas throughout the brain that contribute to the execution of, regulation of, or response to blinks. Regardless of the underlying mechanisms, blinks drastically attenuate our visual abilities, yet these perturbations fail to reach awareness. We conclude by outlining opportunities for future work to better understand how the brain maintains visual perception in the face of eye blinks. Future work will likely benefit from incorporating theories of perceptual stability, neurophysiology, and novel behavior paradigms to address issues central to our understanding of natural visual behavior and for the clinical rehabilitation of active vision. [ABSTRACT FROM AUTHOR]

A hand passing in front of a camera produces a large and obvious disruption of a video. Yet the closure of the eyelid during a blink, which lasts for hundreds of milliseconds and occurs thousands of times per day, typically goes unnoticed. What are the neural mechanisms that mediate our uninterrupted visual experience despite frequent occlusion of the eyes? Here, we review the existing literature on the neurophysiology, perceptual consequences, and behavioral dynamics of blinks. We begin by detailing the kinematics of the eyelid that define a blink. We next discuss the ways in which blinks alter visual function by occluding the pupil, decreasing visual sensitivity, and moving the eyes. Then, to anchor our understanding, we review the similarities between blinks and other actions that lead to reductions in visual sensitivity, such as saccadic eye movements. The similarity between these two actions has led to suggestions that they share a common neural substrate. We consider the extent of overlap in their neural circuits and go on to explain how recent findings regarding saccade suppression cast doubt on the strong version of the shared mechanism hypothesis. We also evaluate alternative explanations of how blink-related processes modulate neural activity to maintain visual stability: a reverberating corticothalamic loop to maintain information in the face of lid closure; and a suppression of visual transients related to lid closure. Next, we survey the many areas throughout the brain that contribute to the execution of, regulation of, or response to blinks. Regardless of the underlying mechanisms, blinks drastically attenuate our visual abilities, yet these perturbations fail to reach awareness. We conclude by outlining opportunities for future work to better understand how the brain maintains visual perception in the face of eye blinks. Future work will likely benefit from incorporating theories of perceptual stability, neurophysiology, and novel behavior paradigms to address issues central to our understanding of natural visual behavior and for the clinical rehabilitation of active vision.

• RELAX is a fully automated free EEG cleaning pipeline with capability to clean data using 0.25 Hz high-pass filter settings for analysis of event-related potentials. • RELAX provided high artifact reduction performance on data with filter settings appropriate for event-related potential research. • ERP data cleaned with RELAX provided high reliability scores, and high variance explained by ERPs comparisons from a commonly used task. Electroencephalography (EEG) is often used to examine neural activity time-locked to stimuli presentation, referred to as Event-Related Potentials (ERP). However, EEG is influenced by non-neural artifacts, which can confound ERP comparisons. Artifact cleaning reduces artifacts, but often requires time-consuming manual decisions. Most automated methods filter frequencies <1 Hz out of the data, so are not recommended for ERPs (which contain frequencies <1 Hz). Our aim was to test the RELAX (Reduction of Electroencephalographic Artifacts) pre-processing pipeline for use on ERP data. The cleaning performance of multiple versions of RELAX were compared to four commonly used EEG cleaning pipelines across both artifact cleaning metrics and the amount of variance in ERPs explained by different conditions in a Go-Nogo task. Results RELAX with Multi-channel Wiener Filtering (MWF) and wavelet-enhanced independent component analysis applied to artifacts identified with ICLabel (wICA_ICLabel) cleaned data most effectively and produced amongst the most dependable ERP estimates. RELAX with wICA_ICLabel only or MWF_only may detect effects better for some ERPs. RELAX shows high artifact cleaning performance even when data is high-pass filtered at 0.25 Hz (applicable to ERP analyses). RELAX is easy to implement via EEGLAB in MATLAB and freely available on GitHub. Given its performance and objectivity we recommend RELAX to improve artifact cleaning and consistency across ERP research. [ABSTRACT FROM AUTHOR]

• RELAX is a fully automated EEG cleaning pipeline, freely available on GitHub, and easy to use through a graphical user interface. • RELAX provided amongst the best performance out of a range of common EEG pre-processing pipelines at cleaning all artifact types. • RELAX provided high values for the variance explained by the difference between outcomes in common experimental manipulations. Electroencephalographic (EEG) data are often contaminated with non-neural artifacts which can confound experimental results. Current artifact cleaning approaches often require costly manual input. Our aim was to provide a fully automated EEG cleaning pipeline that addresses all artifact types and improves measurement of EEG outcomes We developed RELAX (the Reduction of Electroencephalographic Artifacts). RELAX cleans continuous data using Multi-channel Wiener filtering [MWF] and/or wavelet enhanced independent component analysis [wICA] applied to artifacts identified by ICLabel [wICA_ICLabel]). Several versions of RELAX were compared using three datasets (N = 213, 60 and 23 respectively) against six commonly used pipelines across a range of artifact cleaning metrics, including measures of remaining blink and muscle activity, and the variance explained by experimental manipulations after cleaning. RELAX with MWF and wICA_ICLabel showed amongst the best performance at cleaning blink and muscle artifacts while preserving neural signal. RELAX with wICA_ICLabel only may perform better at differentiating alpha oscillations between working memory conditions. RELAX provides automated, objective and high-performing EEG cleaning, is easy to use, and freely available on GitHub. We recommend RELAX for data cleaning across EEG studies to reduce artifact confounds, improve outcome measurement and improve inter-study consistency. [ABSTRACT FROM AUTHOR]

Purpose: To assess optical and motor changes associated with near vision reading under different controlled lighting conditions performed with two different types of electronic screens. Methods: Twenty-four healthy subjects with a mean age of 22.9±2.3 years (18-33) participated in this study. An iPad and an e-ink reader were chosen to present calibrated text, and each task lasted 5 minutes evaluating both ambient illuminance level and luminance of the screens. Results: Eye-tracker data revealed a higher number of saccadic eye movements under minimum luminance than under maximum luminance. The results showed statistically significant differences between the iPad (p=0.016) and the e-ink reader (p=0.002). The length of saccades was also higher for the minimum luminance level for both devices: 6.2±2.8 mm and 8.2±4.2 mm (e-ink max vs min), 6.8±2.9 mm and 7.6±3.6 mm (iPad max vs min), and blinking rate increased significantly for lower lighting conditions. Conclusions: Performing reading tasks on electronic devices is highly influenced by both the configuration of the screens and the ambient lighting, meanwhile, low differences in visual quality that are transient in healthy young people, were found. [ABSTRACT FROM AUTHOR]

The ear-EEG has emerged as a promising candidate for real-world wearable brain monitoring. While experimental studies have validated several applications of ear-EEG, the source-sensor relationship for neural sources from across the brain surface has not yet been established. In addition, modeling of the ear-EEG sensitivity to sources of artifacts is still missing. Through volume conductor modeling, the sensitivity of various configurations of ear-EEG is established for a range of neural sources, in addition to ocular artifact sources for the blink, vertical saccade, and horizontal saccade eye movements. Results conclusively support the introduction of ear-EEG into conventional EEG paradigms for monitoring neural activity that originates from within the temporal lobes, while also revealing the extent to which ear- EEG can be used for sources further away from these regions. The use of ear-EEG in scenarios prone to ocular artifacts is also supported, through the demonstration of proportional scaling of artifacts and neural signals in various configurations of ear-EEG. The results from this study can be used to support both existing and prospective experimental ear-EEG studies and applications in the context of sensitivity to both neural sources and ocular artifacts. [ABSTRACT FROM AUTHOR]

Eye behaviour provides valuable information revealing one’s higher cognitive functions and state of affect. Although eye tracking is gaining ground in the research community, it is not yet a popular approach for the detection of emotional and cognitive states. In this paper, we present a review of eye and pupil tracking related metrics (such as gaze, fixations, saccades, blinks, pupil size variation, etc.) utilized towards the detection of emotional and cognitive processes, focusing on visual attention, emotional arousal and cognitive workload. Besides, we investigate their involvement as well as the computational recognition methods employed for the reliable emotional and cognitive assessment. The publicly available datasets employed in relevant research efforts were collected and their specifications and other pertinent details are described. The multimodal approaches which combine eye-tracking features with other modalities (e.g. biosignals), along with artificial intelligence and machine learning techniques were also surveyed in terms of their recognition/classification accuracy. The limitations, current open research problems and prospective future research directions were discussed for the usage of eye-tracking as the primary sensor modality. This study aims to comprehensively present the most robust and significant eye/pupil metrics based on available literature towards the development of a robust emotional or cognitive computational model. [ABSTRACT FROM AUTHOR]

The ear-EEG has emerged as a promising candidate for real-world wearable brain monitoring. While experimental studies have validated several applications of ear-EEG, the source-sensor relationship for neural sources from across the brain surface has not yet been established. In addition, modeling of the ear-EEG sensitivity to sources of artifacts is still missing. Through volume conductor modeling, the sensitivity of various configurations of ear-EEG is established for a range of neural sources, in addition to ocular artifact sources for the blink, vertical saccade, and horizontal saccade eye movements. Results conclusively support the introduction of ear-EEG into conventional EEG paradigms for monitoring neural activity that originates from within the temporal lobes, while also revealing the extent to which ear-EEG can be used for sources further away from these regions. The use of ear-EEG in scenarios prone to ocular artifacts is also supported, through the demonstration of proportional scaling of artifacts and neural signals in various configurations of ear-EEG. The results from this study can be used to support both existing and prospective experimental ear-EEG studies and applications in the context of sensitivity to both neural sources and ocular artifacts.

Introduction. This paper analyzes the problem of formation of educational Internet resources. Despite numerous works concerning the importance of using information technologies in the education, the issue of its rational organization remains understudied. The purpose of the article is to analyze what patterns are observed when students read educational information from the screen, and how these patterns can be used to create educational Internet resources. Materials and Methods. To study the interaction of students with educational information on the screen, the authors used the method of oculography. The results were processed using the BeGaze and IBM SPSS Statistics 22 programs. In total 100 respondents participated in the experiment, 50 of which were trained in the natural sciences, 50 – in the humanities. Results. It is determined that the presence of media text influences the oculomotor activity of students: students commit fewer fixations and saccades, the average duration of saccades increases, the value of the Scanpath Length indicator decreases. It was revealed that the orientation of training forms strategies for working with information on the screen: students of natural sciences read texts longer, blink less often; they have a higher Scanpath Length value. When forming educational Internet resources, the developer should take into account the students’ specialisms with reference to e-material. It should also be borne in mind that the presence of images on educational Internet pages is perceived by students as a simplifying factor for completing the cognitive task of reading, but students practically do not pay attention to the images themselves. This may be attributed to the specificity of the learning process, when their main focus is on written texts acquisition. Discussion and Conclusion. The results of the study open a new direction in the study of the problem of rational organization of the student's learning process using technical devices and may be of interest to developers of educational Internet resources, as well as practicing teachers.

Purpose: Although blink rate is considered important for digital eye strain and dry eye conditions, its assessment has been mostly manual. This study aimed at quantifying blink rate automatically using the Eyelink 1000 Plus eye tracker and comparing it with manual counting. Additionally, blink rate was correlated with reading eye movements and reading speed., Methods: Thirty participants (mean age 26.8 ± 3.5 years; 19 females) were enrolled. An on-screen reading task for 3 min duration, was repeated 3 times with a 2-min break between the repetitions. During this task, eye movements and blinks were measured through the Eyelink 1000 Plus eye tracker. The blink was also counted manually by the examiner in real time from a video feed., Results: The blink rate obtained by the eye tracker (median [Q1, Q3]:11.7 [6.8,15.5] blinks/min) and manual counting (11.6 [7.1, 15.4] blinks/min) were comparable (p > 0.5). No significant correlations were observed between the blink rate and any of the reading eye movement parameters except saccadic amplitude (Spearman's rho, r s  = 0.506). No statistically significant correlation was found between the blink rate and reading speed., Conclusion: The Eyelink 1000 Plus eye tracker gives a comparable blink rate compared to that obtained through manual counting. A positive correlation between the blink rate and saccade amplitude could indicate a coupled interaction between the two mechanisms to minimize visual loss during reading. The option of using this tracker to investigate blinks in dry eye and binocular vision disorders can be further explored., Competing Interests: Declaration of competing interest None for all authors., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Increasing workload is a central notion in human factors research that can decrease the performance and yield accidents. Thus, it is crucial to understand the impact of different internal operator's factors including eye movements, memory and audio-visual integration. Here, we explored the relationship between cognitive workload (low vs. high) and eye movements (saccades, fixations and smooth pursuit). The task difficulty was induced by auditory noise, arithmetical count and working memory load. We estimated cognitive workload using EOG and EEG-based mental state monitoring. One novelty consists in recording the EOG around the ears (alternative EOG) and around the eyes (conventional EOG). The number of blinks and saccades amplitude increased along with the difficulty increase (p ≤ 0.05). We found significant correlations between EOG and EEG (theta/alpha ratio) and between conventional and alternative EOG signal. The increase in cognitive load may disturb the coding and maintenance of related visual information. Alternative EOG metrics could be a valuable tool for detecting workload. [ABSTRACT FROM AUTHOR]

Experiments in animal models have shown that running increases neuronal activity in early visual areas in light as well as in darkness. This suggests that visual processing is influenced by locomotion independent of visual input. Combining mobile electroencephalography, motion- and eye-tracking, we investigated the influence of overground free walking on cortical alpha activity (~10 Hz) and eye movements in healthy humans. Alpha activity has been considered a valuable marker of inhibition of sensory processing and shown to negatively correlate with neuronal firing rates. We found that walking led to a decrease in alpha activity over occipital cortex compared to standing. This decrease was present during walking in darkness as well as during light. Importantly, eye movements could not explain the change in alpha activity. Nevertheless, we found that walking and eye related movements were linked. While the blink rate increased with increasing walking speed independent of light or darkness, saccade rate was only significantly linked to walking speed in the light. Pupil size, on the other hand, was larger during darkness than during light, but only showed a modulation by walking in darkness. Analyzing the effect of walking with respect to the stride cycle, we further found that blinks and saccades preferentially occurred during the double support phase of walking. Alpha power, as shown previously, was lower during the swing phase than during the double support phase. We however could exclude the possibility that the alpha modulation was introduced by a walking movement induced change in electrode impedance. Overall, our work indicates that the human visual system is influenced by the current locomotion state of the body. This influence affects eye movement pattern as well as neuronal activity in sensory areas and might form part of an implicit strategy to optimally extract sensory information during locomotion.

Some people with severe disabilities are confined in a state in which communication is virtually impossible, being reduced to communicating with their eyes or using sophisticated systems that translate thoughts into words. The EyeTrackers and Brain-Computer Interfaces (BCIs) are suitable systems for those people but their main drawback is their cost. More affordable devices are capable of detecting voluntary blinks and translating them into a binary signal that allows the selection, for example, of an ideogram on a communication board. We tested four different systems based on infrared, bioelectrical signals (Electro-Oculography (EOG) and Electro-Encephalography (EEG)), and video processing. The experiments were performed by people with/without disabilities and analyzed the systems' performances, usability, and method of voluntary blinking (long blinks or sequence of two short blinks). The best accuracy (99.3%) was obtained using Infrared-Oculography (IR-OG) and the worst with the EEG headset (85.9%) and there was a statistical influence of the technology on accuracy. Regarding the method of voluntary blinking, the use of long or double blinks had no statistical influence on accuracy, excluding EOG, and the time taken to perform double blinks was shorter, resulting in a potentially much faster interface. People with disabilities obtained similar values but with greater variability. The preferred technology and blinking methods were Video-Oculography (VOG) and long blinks, respectively. The several Open-Source Hardware (OSHW) devices have been developed and a new algorithm for detecting voluntary blinks has also been proposed, which outperforms most of the published papers in the reviewed literature.

Experiments in animal models have shown that running increases neuronal activity in early visual areas in light as well as in darkness. This suggests that visual processing is influenced by locomotion independent of visual input. Combining mobile electroencephalography, motion- and eye-tracking, we investigated the influence of overground free walking on cortical alpha activity (~10 Hz) and eye movements in healthy humans. Alpha activity has been considered a valuable marker of inhibition of sensory processing and shown to negatively correlate with neuronal firing rates. We found that walking led to a decrease in alpha activity over occipital cortex compared to standing. This decrease was present during walking in darkness as well as during light. Importantly, eye movements could not explain the change in alpha activity. Nevertheless, we found that walking and eye related movements were linked. While the blink rate increased with increasing walking speed independent of light or darkness, saccade rate was only significantly linked to walking speed in the light. Pupil size, on the other hand, was larger during darkness than during light, but only showed a modulation by walking in darkness. Analyzing the effect of walking with respect to the stride cycle, we further found that blinks and saccades preferentially occurred during the double support phase of walking. Alpha power, as shown previously, was lower during the swing phase than during the double support phase. We however could exclude the possibility that the alpha modulation was introduced by a walking movement induced change in electrode impedance. Overall, our work indicates that the human visual system is influenced by the current locomotion state of the body. This influence affects eye movement pattern as well as neuronal activity in sensory areas and might form part of an implicit strategy to optimally extract sensory information during locomotion. [ABSTRACT FROM AUTHOR]

Eye-tracking experiments rely heavily on good data quality of eye-trackers. Unfortunately, it is often the case that only the spatial accuracy and precision values are available from the manufacturers. These two values alone are not sufficient to serve as a benchmark for an eye-tracker: Eye-tracking quality deteriorates during an experimental session due to head movements, changing illumination or calibration decay. Additionally, different experimental paradigms require the analysis of different types of eye movements; for instance, smooth pursuit movements, blinks or microsaccades, which themselves cannot readily be evaluated by using spatial accuracy or precision alone. To obtain a more comprehensive description of properties, we developed an extensive eye-tracking test battery. In 10 different tasks, we evaluated eye-tracking related measures such as: the decay of accuracy, fixation durations, pupil dilation, smooth pursuit movement, microsaccade classification, blink classification, or the influence of head motion. For some measures, true theoretical values exist. For others, a relative comparison to a reference eye-tracker is needed. Therefore, we collected our gaze data simultaneously from a remote EyeLink 1000 eye-tracker as the reference and compared it with the mobile Pupil Labs glasses. As expected, the average spatial accuracy of 0.57° for the EyeLink 1000 eye-tracker was better than the 0.82° for the Pupil Labs glasses (N = 15). Furthermore, we classified less fixations and shorter saccade durations for the Pupil Labs glasses. Similarly, we found fewer microsaccades using the Pupil Labs glasses. The accuracy over time decayed only slightly for the EyeLink 1000, but strongly for the Pupil Labs glasses. Finally, we observed that the measured pupil diameters differed between eye-trackers on the individual subject level but not on the group level. To conclude, our eye-tracking test battery offers 10 tasks that allow us to benchmark the many parameters of interest in stereotypical eye-tracking situations and addresses a common source of confounds in measurement errors (e.g., yaw and roll head movements). All recorded eye-tracking data (including Pupil Labs’ eye videos), the stimulus code for the test battery, and the modular analysis pipeline are freely available (https://github.com/behinger/etcomp).

(1) Goals: The purpose of this study was to analyze the feasibility of using the information obtained from a one-channel electro-encephalography (EEG) signal to control a mouse pointer. We used a low-cost headset, with one dry sensor placed at the FP1 position, to steer a mouse pointer and make selections through a combination of the user’s attention level with the detection of voluntary blinks. There are two types of cursor movements: spinning and linear displacement. A sequence of blinks allows for switching between these movement types, while the attention level modulates the cursor’s speed. The influence of the attention level on performance was studied. Additionally, Fitts’ model and the evolution of the emotional states of participants, among other trajectory indicators, were analyzed. (2) Methods: Twenty participants distributed into two groups (Attention and No-Attention) performed three runs, on different days, in which 40 targets had to be reached and selected. Target positions and distances from the cursor’s initial position were chosen, providing eight different indices of difficulty (IDs). A self-assessment manikin (SAM) test and a final survey provided information about the system’s usability and the emotions of participants during the experiment. (3) Results: The performance was similar to some brain–computer interface (BCI) solutions found in the literature, with an averaged information transfer rate (ITR) of 7 bits/min. Concerning the cursor navigation, some trajectory indicators showed our proposed approach to be as good as common pointing devices, such as joysticks, trackballs, and so on. Only one of the 20 participants reported difficulty in managing the cursor and, according to the tests, most of them assessed the experience positively. Movement times and hit rates were significantly better for participants belonging to the attention group. (4) Conclusions: The proposed approach is a feasible low-cost solution to manage a mouse pointer.

This study investigated the effects of music and playback speed on arousal and visual perception in slow-motion scenes taken from commercial films. Slow-motion scenes are a ubiquitous film technique and highly popular. Yet the psychological effects of mediated time-stretching compared to real-time motion have not been empirically investigated. We hypothesised that music affects arousal and attentional processes. Furthermore, we assumed that playback speed influences viewers’ visual perception, resulting in a higher number of eye movements and larger gaze dispersion. Thirty-nine participants watched three film excerpts in a repeated-measures design in conditions with or without music and in slow motion vs. adapted real-time motion (both visual-only). Results show that music in slow-motion film scenes leads to higher arousal compared to no music as indicated by larger pupil diameters in the former. There was no systematic effect of music on visual perception in terms of eye movements. Playback speed influenced visual perception in eye movement parameters such that slow motion resulted in more and shorter fixations as well as more saccades compared to adapted real-time motion. Furthermore, in slow motion there was a higher gaze dispersion and a smaller centre bias, indicating that individuals attended to more detail in slow motion scenes.

Abstract The accurate extraction of signals out of noisy environments is a major challenge of the perceptual system. Forming temporal expectations and continuously matching them with perceptual input can facilitate this process. In humans, temporal expectations are typically assessed using behavioral measures, which provide only retrospective but no real-time estimates during target anticipation, or by using electrophysiological measures, which require extensive preprocessing and are difficult to interpret. Here we show a new correlate of temporal expectations based on oculomotor behavior. Observers performed an orientation-discrimination task on a central grating target, while their gaze position and EEG were monitored. In each trial, a cue preceded the target by a varying interval ("foreperiod"). In separate blocks, the cue was either predictive or non-predictive regarding the timing of the target. Results showed that saccades and blinks were inhibited more prior to an anticipated regular target than a less-anticipated irregular one. This consistent oculomotor inhibition effect enabled a trial-by-trial classification according to interval-regularity. Additionally, in the regular condition the slope of saccade-rate and drift were shallower for longer than shorter foreperiods, indicating their adjustment according to temporal expectations. Comparing the sensitivity of this oculomotor marker with those of other common predictability markers (e.g. alpha-suppression) showed that it is a sensitive marker for cue-related anticipation. In contrast, temporal changes in conditional probabilities (hazard-rate) modulated alpha-suppression more than cue-related anticipation. We conclude that pre-target oculomotor inhibition is a correlate of temporal predictions induced by cue-target associations, whereas alpha-suppression is more sensitive to conditional probabilities across time. Highlights • Saccades and blinks are inhibited prior to predictable targets. • Pre-target oculomotor inhibition can be used as an index of temporal expectations. • This index is sensitive and direct, and is measured while predictions are made, unlike retrospective behavioral measures. • EEG Alpha amplitude is correlated with the hazard rate and reflects conditional probabilities. • There is no evidence that the oculomotor index reflects conditional probabilities. [ABSTRACT FROM AUTHOR]

Highlights • EOG-based gaze displacement estimation using a two-channel input regression model. • Real-time blink and saccade discrimination using EOG peak and gradient features. • Using unconstrained gaze movements to interact with an EOG-based virtual keyboard. • A writing speed of 11.89 ± 4.42 characters per minute was achieved across 9 subjects. Abstract This work aims to develop a novel electrooculography (EOG)-based virtual keyboard with a standard QWERTY layout which, unlike similar state-of-the-art systems, allows users to reach any icon from any location directly and asynchronously. The saccadic EOG potential displacement is mapped to angular gaze displacement using a novel two-channel input linear regression model, which considers features extracted from both the horizontal and vertical EOG signal components jointly. Using this technique, a gaze displacement estimation error of 1.32 ± 0.26° and 1.67 ± 0.26° in the horizontal and vertical directions respectively was achieved, a performance which was also found to be generally statistically significantly better than the performance obtained using one model for each EOG component to model the relationship in the horizontal and vertical directions separately, as typically used in the literature. Furthermore, this work also proposes a threshold-based method to detect eye movements from EOG signals in real-time, which are then classified as saccades or blinks using a novel cascade of a parametric and a signal-morphological classifier based on the EOG peak and gradient features. This resulted in an average saccade and blink labelling accuracy of 99.92% and 100.00% respectively, demonstrating that these two eye movements could be reliably detected and discriminated in real-time using the proposed algorithms. When these techniques were used to interface with the proposed asynchronous EOG-based virtual keyboard, an average writing speed across subjects of 11.89 ± 4.42 characters per minute was achieved, a performance which has been shown to improve substantially with user experience. [ABSTRACT FROM AUTHOR]

This study investigated the effects of music and playback speed on arousal and visual perception in slow-motion scenes taken from commercial films. Slow-motion scenes are a ubiquitous film technique and highly popular. Yet the psychological effects of mediated time-stretching compared to real-time motion have not been empirically investigated. We hypothesised that music affects arousal and attentional processes. Furthermore, we assumed that playback speed influences viewers' visual perception, resulting in a higher number of eye movements and larger gaze dispersion. Thirty-nine participants watched three film excerpts in a repeated-measures design in conditions with or without music and in slow motion vs. adapted real-time motion (both visual-only). Results show that music in slow-motion film scenes leads to higher arousal compared to no music as indicated by larger pupil diameters in the former. There was no systematic effect of music on visual perception in terms of eye movements. Playback speed influenced visual perception in eye movement parameters such that slow motion resulted in more and shorter fixations as well as more saccades compared to adapted real-time motion. Furthermore, in slow motion there was a higher gaze dispersion and a smaller centre bias, indicating that individuals attended to more detail in slow motion scenes. [ABSTRACT FROM AUTHOR]

We present a computationally light real-time algorithm which automatically detects blinks, saccades, and fixations from electro-oculography (EOG) data and calculates their temporal parameters. The method is probabilistic which allows to consider the uncertainties in the detected events. The method is real-time in the sense that it processes the data sample-by-sample, without a need to process the whole data as a batch. Prior to the actual measurements, a short, unsupervised training period is required. The parameters of the Gaussian likelihoods are learnt using an expectation maximization algorithm. The results show the promise of the method in detecting blinks, saccades, and fixations, with detection rates close to 100 %. The presented method is published as an open source tool.

The Concealed Information Test (CIT) is a psychophysiological technique that allows for detecting crime-related knowledge. Usually, autonomic response measures are used for this purpose, but ocular measures have also been proposed recently. Prior studies reported heterogeneous results for the usage of countermeasures (CM) to corrupt the CIT's validity, depending on the CM technique and the dependent measure. The current study systematically compared the application of physical and mental CM on autonomic and ocular measures during the CIT. Sixty participants committed a mock crime and were assigned to one of three guilty conditions: standard guilty (without CM), physical CM, or mental CM. An additional group of 20 innocents was investigated with the same CIT to calculate validity estimates. Electrodermal responses were more vulnerable for CM usage compared to heart rate and respiration, and physical CM were more effective than mental CM. Independent of CM usage, a combined score of autonomic responses enabled a valid differentiation between guilty and innocent examinees. Fixations and blinks also allowed for detecting crime-related knowledge, but these measures were more affected by CM application than autonomic responses. The current study delivered further evidence that CM differentially impact physiological and ocular responses in the CIT. Whereas individual data channels were strongly affected by CM usage, a combination of different response measures yielded a relatively stable differentiation of guilty and innocent examinees when mental CM were used. These findings are especially relevant for field applications and might inspire future studies to detect or prevent CM usage in CIT examinations. [ABSTRACT FROM AUTHOR]

Gamma oscillations (>30 Hz) in the brain are involved in attention, perception and memory. They are altered in various pathological states, as well as by neuropharmaceuticals, so that they are of interest in drug and clinical investigations. However, when the human electroencephalogram is recorded on the scalp, this neural high-frequency signal is buried under a range of other electrical signals such that, without careful handling, recordings of the high-frequency electroencephalogram cannot be considered reliable. The artefacts of concern originate from: power line noise, saccade-associated contraction of the extra-ocular muscles, activity of muscles in the scalp, face and neck, screen refresh artefacts and activity of the muscles associated with blinking. Recent progress in dealing with these artefacts is described, including either noise cancellation or phased noise template subtraction for power line noise, regression or independent component analysis for correcting extra-ocular muscle activity and mathematical modelling for reducing scalp, face and neck muscle activity. If the artefacts are properly addressed, the neural gamma signal can be uncovered. © 2016 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Spike trains of retinal ganglion cells (RGCs) are the sole source of visual information to the brain; and understanding how the ~20 RGC types in mammalian retinae respond to diverse visual features and events is fundamental to understanding vision. Suppressed-by-contrast (SbC) RGCs stand apart from all other RGC types in that they reduce rather than increase firing rates in response to light increments (ON) and decrements (OFF). Here, we genetically identify and morphologically characterize SbC-RGCs in mice, and target them for patch-clamp recordings under two-photon guidance. We find that strong ON inhibition (glycine > GABA) outweighs weak ON excitation, and that inhibition (glycine > GABA) coincides with decreases in excitation at light OFF. These input patterns explain the suppressive spike responses of SbC-RGCs, which are observed in dim and bright light conditions. Inhibition to SbC-RGC is driven by rectified receptive field subunits, leading us to hypothesize that SbC-RGCs could signal pattern-independent changes in the retinal image. Indeed, we find that shifts of random textures matching saccade-like eye movements in mice elicit robust inhibitory inputs and suppress spiking of SbC-RGCs over a wide range of texture contrasts and spatial frequencies. Similarly, stimuli based on kinematic analyses of mouse blinking consistently suppress SbC-RGC spiking. Receiver operating characteristics show that SbC-RGCs are reliable indicators of self-generated visual stimuli that may contribute to central processing of blinks and saccades. [ABSTRACT FROM AUTHOR]

In this paper, a methodological scheme for identifying distinct patterns of oculomotor behavior such as saccades, microsaccades, blinks and fixations from time series of eye's angular displacement is presented. The first step of the proposed methodology involves signal detrending for artifacts removal and estimation of eye's angular velocity. Then, feature vectors from fourteen first-order statistical features are formed from each angular displacement and velocity signal using sliding, fixed-length time windows. The obtained feature vectors are used for training and testing three artificial neural network classifiers, connected in cascade. The three classifiers discriminate between blinks and non-blinks, fixations and non-fixations and saccades and microsaccades, respectively. The proposed methodology was tested on a dataset from 1392 subjects, each performing three oculomotor fixation conditions. The average overall accuracy of the three classifiers, with respect to the manual identification of eye movements by experts, was 95.9%. The proposed methodological scheme provided better results than the well-known Velocity Threshold algorithm, which was used for comparison. The findings of the present study indicate that the utilization of pattern recognition techniques in the task of identifying the various eye movements may provide accurate and robust results. [ABSTRACT FROM AUTHOR]

A significant body of literature supports the contention that pupil size varies depending on cognitive load, affective state, and level of drowsiness. Here we assessed whether oculometric measures such as gaze position, blink frequency and pupil size were correlated with the occurrence and time course of self-reported mind-wandering episodes. We recorded the pupil size of two subjects engaged in a monotonous breath counting task while keeping their eyes on a fixation cross. Each subject performed ten 20-minute sessions, for total duration of about 4 hours. This task is conducive to producing mind-wandering episodes. Subjects were instructed to report spontaneous mind-wandering episodes by pressing a button when they lost count of their breath. After each button press, subjects filled in a short questionnaire describing the characteristics of their mind-wandering episode. We observed larger pupil size during the breath-focusing period compared to the mind-wandering period (p< 0.01 for both subjects). Our findings contradict previous research showing a higher baseline pupil size during mind wandering episodes in visual tasks. We discuss possible explanations for this discrepancy. We also analyzed nine other oculometric measures including blink rate, blink duration and gaze position. We built a support vector machine classifier and showed that mean pupil size was the most reliable predictors of mind wandering in both subjects. The classification accuracy of mind wandering data segments versus breath-focusing data segments was 81% for the first subject and 77% for the second subject. Additionally, we analyzed oculometric measures in light of the phenomenological data collected in the questionnaires. We showed that how well subjects remembered their thoughts while mind wandering was positively correlated with pupil size (subject 1, p< 0.001; subject 2, p< 0.05). Feelings of well being were also positively correlated with pupil size (subject 1, p< 0.001; subject 2, p< 0.001).

The response time (RT) based Concealed Knowledge Test (CKT) has been shown to accurately detect participants’ knowledge of mock-crime related information. Tests based on ocular measures such as pupil size and blink rate have sometimes resulted in poor classification, or lacked detailed classification analyses. The present study examines the fitness of multiple pupil and blink related responses in the CKT paradigm. To maximize classification efficiency, participants’ concealed knowledge was assessed using both individual test measures and combinations of test measures. Results show that individual pupil-size, pupil-slope, and pre-response blink-rate measures produce efficient classifications. Combining pupil and blink measures yielded more accuracy classifications than individual ocular measures. Although RT-based tests proved efficient, combining RT with ocular measures had little incremental benefit. It is argued that covertly assessing ocular measures during RT-based tests may guard against effective countermeasure use in applied settings. A compound classification procedure was used to categorize individual participants and yielded high hit rates and low false-alarm rates without the need for adjustments between test paradigms or subject populations. We conclude that with appropriate test paradigms and classification analyses, ocular measures may prove as effective as other indices, though additional research is needed.

The majority of individuals appear to have insight into their own sleepiness, but there is some evidence that this does not hold true for all, for example treated patients with obstructive sleep apnoea. Identification of sleep-related symptoms may help drivers determine their sleepiness, eye symptoms in particular show promise. Sixteen participants completed four motorway drives on two separate occasions. Drives were completed during daytime and night-time in both a driving simulator and on the real road. Ten eye symptoms were rated at the end of each drive, and compared with driving performance and subjective and objective sleep metrics recorded during driving. 'Eye strain', 'difficulty focusing', 'heavy eyelids' and 'difficulty keeping the eyes open' were identified as the four key sleep-related eye symptoms. Drives resulting in these eye symptoms were more likely to have high subjective sleepiness and more line crossings than drives where similar eye discomfort was not reported. Furthermore, drivers having unintentional line crossings were likely to have 'heavy eyelids' and 'difficulty keeping the eyes open'. Results suggest that drivers struggling to identify sleepiness could be assisted with the advice 'stop driving if you feel sleepy and/or have heavy eyelids or difficulty keeping your eyes open'. [ABSTRACT FROM AUTHOR]

Blinks are related to several emotional states, and the present report describes a simple, reliable way to measure blinks from the video stream of an eye obtained during eyetracking, where the source of the eye video is a video camera attached to a head-mounted eyetracker. Computer vision techniques are employed to determine the moments that a blink starts and ends, for the purpose of calculating blink frequency and duration. The video is first processed to show blocks of eyelid and pupil movements, and is then analyzed for blink starts and ends. The moment of a blink start is reported when the eyelid starts to move quickly, exceeding a predetermined threshold. The end of a blink arises when the pupil size increases by less than a separate threshold. We observed several different blink patterns from different subjects, and our algorithm was designed to work for all of these patterns. We evaluated our algorithm by manually measuring the true blinks of five different subjects while they were eyetracked. To test the sensitivity and specificity of the algorithm, we employed a series of threshold values to plot the receiver operating characteristic curves. Using the best thresholds, we achieved excellent sensitivity (>90 %) and specificity (>99 %) over the five subjects. Potential applications of this research include real-time, nonintrusive, continuous and automated measurements of mental workload and other emotional states related to blink rates and durations. [ABSTRACT FROM AUTHOR]

A large number of accidents are due to the driver falling asleep at the wheel, but details of this link have not been studied on a real road. The purpose of the present study was to describe the development of sleepiness indicators, leading to the drive being terminated prematurely by the onboard expert driving instructor because of imminent danger. Eighteen individuals participated during a day drive and a night drive on a motorway (both 90 min). Eight drivers terminated ( N) prematurely (after 43 min) because of sleep-related imminent danger [according to the driving instructor or their own judgement (two cases)]. The results showed very high sleepiness ratings (8.5 units on the Karolinska Sleepiness Scale) immediately before termination (<7 at a similar time interval for those 10 who completed the drive). Group N also showed significantly higher levels of sleep intrusions on the electroencephalography/electro-oculography ( EEG/ EOG) than those who completed the drive (group C). The sleep intrusions were increased in group N during the first 40 min of the night drive. During the day drive, sleep intrusions were increased significantly in group N. The night drive showed significant increases of all sleepiness indicators compared to the day drive, but also reduced speed and driving to the left in the lane. It was concluded that 44% of drivers during late-night driving became dangerously sleepy, and that this group showed higher perceived sleepiness and more sleep intrusions in the EEG/EOG. [ABSTRACT FROM AUTHOR]

Mental workload is a major consideration for the design of emergency operation procedures (EOPs) in nuclear power plants. Continuous and objective measures are desired. This paper compares seven mental workload measurement methods (pupil size, blink rate, blink duration, heart rate variability, parasympathetic/sympathetic ratio, total power and (Goals, Operations, Methods, and Section Rules)-(Keystroke Level Model) GOMS-KLM-based workload index) with regard to sensitivity, validity and intrusiveness. Eighteen participants performed two computerised EOPs of different complexity levels, and mental workload measures were collected during the experiment. The results show that the blink rate is sensitive to both the difference in the overall task complexity and changes in peak complexity within EOPs, that the error rate is sensitive to the level of arousal and correlate to the step error rate and that blink duration increases over the task period in both low and high complexity EOPs. Cardiac measures were able to distinguish tasks with different overall complexity. The intrusiveness of the physiological instruments is acceptable. Finally, the six physiological measures were integrated using group method of data handling to predict perceived overall mental workload. Practitioner Summary:The study compared seven measures for evaluating the mental workload with emergency operation procedure in nuclear power plants. An experiment with simulated procedures was carried out, and the results show that eye response measures are useful for assessing temporal changes of workload whereas cardiac measures are useful for evaluating the overall workload. [ABSTRACT FROM AUTHOR]

Abstract: The Concealed Information Test (CIT) is a method of forensic psychophysiology that allows for revealing concealed crime related knowledge. Such detection is usually based on autonomic responses but there is a huge interest in other measures that can be acquired unobtrusively. Eye movements and blinks might be such measures but their validity is unclear. Using a mock crime procedure with a manipulation of the arousal during the crime as well as the delay between crime and CIT, we tested whether eye tracking measures allow for detecting concealed knowledge. Guilty participants showed fewer but longer fixations on central crime details and this effect was even present after stimulus offset and accompanied by a reduced blink rate. These ocular measures were partly sensitive for induction of emotional arousal and time of testing. Validity estimates were moderate but indicate that a significant differentiation between guilty and innocent subjects is possible. Future research should further investigate validity differences between gaze measures during a CIT and explore the underlying mechanisms. [Copyright &y& Elsevier]