BACKGROUND: In attention-deficit/hyperactivity disorder (ADHD), poor inhibitory control is one of the main characteristics, with oculomotor inhibition impairments being considered a potential biomarker of the disorder. While auditory white noise has demonstrated the ability to enhance working memory in this group, visual white noise is still unexplored and so are the effects of both types of white noise stimulation on oculomotor inhibition.
OBJECTIVE: This crossover study aims to explore the impact of auditory and visual white noise on oculomotor inhibition in children with ADHD and typically developing (TD) children. The study will investigate the impact of different noise levels (25% and 50% visual, 78 dB auditory), and performance will be evaluated both with and without noise stimulation. We hypothesize that exposure to white noise will improve performance in children with ADHD and impair the performance for TD children.
METHODS: Memory-guided saccades and prolonged fixations, known for their sensitivity in detecting oculomotor disinhibition in ADHD, will be used to assess performance. Children diagnosed with ADHD, withdrawing from medication for 24 hours, and TD children without psychiatric disorders were recruited for the study.
RESULTS: Data collection was initiated in October 2023 and ended in February 2024. A total of 97 participants were enrolled, and the first results are expected between September and November 2024.
CONCLUSIONS: This study will examine whether cross-modal sensory stimulation can enhance executive function, specifically eye movement control, in children with ADHD. In addition, the study will explore potential differences between auditory and visual noise effects in both groups. Our goal is to identify implications for understanding how noise can be used to improve cognitive performance.
BACKGROUND: ClinicalTrials.gov NCT06057441; https://clinicaltrials.gov/study/NCT06057441.
UNASSIGNED: DERR1-10.2196/56388.

The purpose of this study was to investigate the difference in oculomotor functioning between Olympic-level contact and non-contact sports participants. In total, 67 male and female Olympic-level contact (n = 27) and non-contact (n = 40) athletes completed oculomotor tasks, including Horizontal Saccade (HS), Circular Smooth Pursuit (CSP), Horizontal Smooth Pursuit (HSP), and Vertical Smooth Pursuit (VSP) using a remote eye tracker. No significant differences for sex or age occurred. Each variable indicated higher scores for contact compared to non-contact athletes (p < .05) except for VSP Pathway differences and CSP Synchronization. A logistic regression was performed to determine the degree that HS measures, CSP synchronization, and VSP pathway predicted sport type. The model was significant, χ2(6) = 37.08, p < .001, explaining 57.4% of the variance and correctly classified 88.1% of cases. The sensitivity was 87.5% and specificity was 88.9%. CSP synchronization did not increase the likelihood of participating in a contact sport. This was the first study to identify oculomotor differences between Olympic athletes of contact and non-contact sports, which adds to the growing evidence that oculomotor functioning may be a reliable, quick, real-time tool to help detect mTBI in sport.

Eye tracking technology is a high-potential tool for different mathematic cognition research areas. Moreover, there is a dire need for more studies that provide detailed information on the quality of registered eye data. This study aimed to illustrate the applicability of eye tracking in the examination of mathematical cognition, focusing specifically on primary school students completing a computerized mental arithmetic task. Results suggested that the eye tracking device effectively captured high-quality eye movement data when primary school children engaged in this specific task. Furthermore, significant negative correlations have been found between task performance and number of eye fixations. Finally, eye movements distinctions between \"Areas of Interest\" have been found, indicating different visual tracking associated with different components of arithmetic calculations. This study underscores the extensive possibilities for future research employing eye tracking devices during computerized calculation tasks as assessment tools to explore the complex visual and cognitive processes.

Combining eye tracking and virtual reality (VR) is a promising approach to tackle various applied research questions. As this approach is relatively new, routines are not established yet and the first steps can be full of potential pitfalls. The present paper gives a practice example to lower the boundaries for getting started. More specifically, I focus on an affordable add-on technology, the Pupil Labs eye tracking add-on for the HTC Vive. As add-on technology with all relevant source code available on GitHub, a high degree of freedom in preprocessing, visualizing, and analyzing eye tracking data in VR can be achieved. At the same time, some extra preparatory steps for the setup of hardware and software are necessary. Therefore, specifics of eye tracking in VR from unboxing, software integration, and procedures to analyzing the data and maintaining the hardware will be addressed. The Pupil Labs eye tracking add-on for the HTC Vive represents a highly transparent approach to existing alternatives. Characteristics of eye tracking in VR in contrast to other headmounded and remote eye trackers applied in the physical world will be discussed. In conclusion, the paper contributes to the idea of open science in two ways: First, by making the necessary routines transparent and therefore reproducible. Second, by stressing the benefits of using open source software.

We compared the performance of two smooth-pursuit-based object selection algorithms in Virtual Reality (VR). To assess the best algorithm for a range of configurations, we systematically varied the number of targets to choose from, their distance, and their movement pattern (linear and circular). Performance was operationalized as the ratio of hits, misses and non-detections. Averaged over all distances, the correlation-based algorithm performed better for circular movement patterns compared to linear ones (F(1,11) = 24.27, p < .001, η² = .29). This was not found for the difference-based algorithm (F(1,11) = 0.98, p = .344, η² = .01). Both algorithms performed better in close distances compared to larger ones (F(1,11) = 190.77, p < .001, η² = .75 correlation-based, and F(1,11) = 148.20, p < .001, η² = .42, difference-based). An interaction effect for distance x movement emerged. After systematically varying the number of targets, these results could be replicated, with a slightly smaller effect. Based on performance levels, we introduce the concept of an optimal threshold algorithm, suggesting the best detection algorithm for the individual target configuration. Learnings of adding the third dimension to the detection algorithms and the role of distractors are discussed and suggestions for future research added.

Mobile eye tracking helps to investigate real-world settings, in which participants can move freely. This enhances the studies\' ecological validity but poses challenges for the analysis. Often, the 3D stimulus is reduced to a 2D image (reference view) and the fixations are manually mapped to this 2D image. This leads to a loss of information about the three-dimensionality of the stimulus. Using several reference images, from different perspectives, poses new problems, in particular concerning the mapping of fixations in the transition areas between two reference views. A newly developed approach (MAP3D) is presented that enables generating a 3D model and automatic mapping of fixations to this virtual 3D model of the stimulus. This avoids problems with the reduction to a 2D reference image and with transitions between images. The x, y and z coordinates of the fixations are available as a point cloud and as .csv output. First exploratory application and evaluation tests are promising: MAP3D offers innovative ways of post-hoc mapping fixation data on 3D stimuli with open-source software and thus provides cost-efficient new avenues for research.

Algorithms for the estimation of gaze direction from mobile and video-based eye trackers typically involve tracking a feature of the eye that moves through the eye camera image in a way that covaries with the shifting gaze direction, such as the center or boundaries of the pupil. Tracking these features using traditional computer vision techniques can be difficult due to partial occlusion and environmental reflections. Although recent efforts to use machine learning (ML) for pupil tracking have demonstrated superior results when evaluated using standard measures of segmentation performance, little is known of how these networks may affect the quality of the final gaze estimate. This work provides an objective assessment of the impact of several contemporary ML-based methods for eye feature tracking when the subsequent gaze estimate is produced using either feature-based or model-based methods. Metrics include the accuracy and precision of the gaze estimate, as well as drop-out rate.

This study examined grammatical gender processing in school-aged children with varying levels of cumulative English exposure. Children participated in a visual world paradigm with a four-picture display where they heard a gendered article followed by a target noun and were in the context where all images were the same gender (same gender), where all of the distractor images were the opposite gender than the target noun (different gender), and where all of the distractor images were the opposite gender, but there was a mismatch in the gendered article and target noun pair. We investigated 51 children (aged 5;0-10;0) who were exposed to Spanish since infancy but varied in their amount of cumulative English exposure. In addition to the visual word paradigm, all children completed an article-noun naming task, a grammaticality judgment task, and standardized vocabulary tests. Parents reported on their child\'s cumulative English language exposure and current English language use. To investigate the time course of lexical facilitation effects, looks to the target were analyzed with a cluster-based permutation test. The results revealed that all children used gender in a facilitatory way (during the noun region), and comprehension was significantly inhibited when the article-noun pairing was ungrammatical rather than grammatical. Compared to children with less cumulative English exposure, children with more cumulative English exposure looked at the target noun significantly less often overall, and compared to younger children, older children looked at the target noun significantly more often overall. Additionally, children with lower cumulative English exposure looked at target nouns more in the different-gender condition than the same-gender condition for masculine items more than feminine items.

Adults with Developmental Coordination Disorder (DCD), sometimes referred to as dyspraxia, experience difficulties in motor development and coordination, which impacts on all aspects of their daily lives. Surprisingly little is known about the mechanisms underlying the difficulties they experience in the motor domain. In childhood DCD, aspects of oculomotor control have been shown to be altered. The purpose of this study was to determine whether oculomotor differences are present in adults with and without probable DCD. Visual fixation stability, smooth pursuit, and pro-and anti-saccade performance were assessed in 21 adults (mean age 29 years) with probable DCD/dyspraxia (pDCD) and 21 typically-developing (TD) adults (mean age 21 years). Eye tracking technology revealed that oculomotor response preparation in the pro- and anti-saccade tasks was comparable across groups, as was pursuit gain in the slower of the two smooth pursuit tasks. However, adults with pDCD made significantly more saccades away from the fixation target than those without DCD and significantly more anti-saccade errors. Further, compared to TD adults, adults with pDCD demonstrated difficulties in maintaining engagement and had lower pursuit gain in the faster pursuit task. This suggests that adults with pDCD have problems with saccadic inhibition and maintaining attention on a visual target. Since this pattern of results has also been reported in children with DCD, oculomotor difficulties may be persistent for those with DCD across the lifespan. An awareness of the impact of atypical oculomotor control in activities of daily living across the lifespan would support clearer understanding of the causes and impacts of these difficulties for those with DCD.

Cognition is crucial to brain function, and accurately classifying cognitive load is essential for understanding the psychological processes across tasks. This paper innovatively combines functional near-infrared spectroscopy (fNIRS) with eye tracking technology to delve into the classification of cognitive load at the neurocognitive level. This integration overcomes the limitations of a single modality, addressing challenges such as feature selection, high dimensionality, and insufficient sample capacity. We employ fNIRS-eye tracking technology to collect neural activity and eye tracking data during various cognitive tasks, followed by preprocessing. Using the maximum relevance minimum redundancy algorithm, we extract the most relevant features and evaluate their impact on the classification task. We evaluate the classification performance by building models (naive Bayes, support vector machine, K-nearest neighbors, and random forest) and employing cross-validation. The results demonstrate the effectiveness of fNIRS-eye tracking, the maximum relevance minimum redundancy algorithm, and machine learning techniques in discriminating cognitive load levels. This study emphasizes the impact of the number of features on performance, highlighting the need for an optimal feature set to improve accuracy. These findings advance our understanding of neuroscientific features related to cognitive load, propelling neural psychology research to deeper levels and holding significant implications for future cognitive science.