Journal of Eye Movement Research

18 pages, 2625 KB

Open AccessArticle

Conventional Versus Virtual Reality-Based Hess–Lancaster Assessment: Agreement and Repeatability in Ocular Motility Evaluation

by Francisco Javier Povedano-Montero, Álvaro Perales-Serrano, Daniela León Lobo, Rut González-Jiménez, Ricardo Bernárdez-Vilaboa and Juan E. Cedrún-Sánchez

J. Eye Mov. Res. 2026, 19(3), 67; https://doi.org/10.3390/jemr19030067 (registering DOI) - 9 Jun 2026

Abstract

Background: The conventional Hess–Lancaster test is widely used to assess ocular misalignment across diagnostic gaze positions, but it relies on subjective responses and manual recording. Virtual reality may provide a more standardized framework for ocular motility assessment. Objectives: To evaluate the agreement and [...] Read more.

Background: The conventional Hess–Lancaster test is widely used to assess ocular misalignment across diagnostic gaze positions, but it relies on subjective responses and manual recording. Virtual reality may provide a more standardized framework for ocular motility assessment. Objectives: To evaluate the agreement and within-method repeatability of point-by-point deviation measurements obtained with the conventional Hess–Lancaster test and a VR-based Hess–Lancaster assessment implemented in Dicopt Pro. Methods: This cross-sectional observational study included 52 adults with suspected or diagnosed ocular motility disorders. Participants underwent both assessments using the same predefined gaze positions. Agreement was assessed using Bland–Altman analysis, concordance correlation coefficients, mean absolute differences, and mixed-effects modeling. Repeatability was evaluated in a subset with repeated measurements using session-to-session differences and intraclass correlation coefficients. Results: The VR-based assessment showed moderate agreement with the conventional test, with a mean concordance correlation coefficient of 0.57 for both eyes. Mean bias was 1.22 prism diopters for the right eye and 0.10 prism diopters for the left eye. Repeatability estimates were moderate-to-good, with ICC values ranging from 0.62 to 0.83, although repeated measurements were available only in a subset of participants. Conclusions: The VR-based Hess–Lancaster assessment showed small mean differences and moderate agreement with the conventional test, although both methods should be interpreted within the context of the complete clinical examination. Full article

(This article belongs to the Special Issue Digital Advances in Binocular Vision and Eye Movement Assessment)

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27 pages, 1312 KB

Open AccessArticle

Reading to Translate or Translating to Read? Modeling Translators’ Eye Movements with Multilingual Pre-Trained Models

by Yiyu Zhang, Xiajing Yao and Dechao Li

J. Eye Mov. Res. 2026, 19(3), 66; https://doi.org/10.3390/jemr19030066 (registering DOI) - 8 Jun 2026

Abstract

Translation and post-editing both integrate reading into bilingual text production, yet it remains unclear which computational predictors from multilingual pre-trained models best account for translators’ reading patterns across task types and translation directions. We recruited twenty-six Chinese L1 translators who completed en→zh and [...] Read more.

Translation and post-editing both integrate reading into bilingual text production, yet it remains unclear which computational predictors from multilingual pre-trained models best account for translators’ reading patterns across task types and translation directions. We recruited twenty-six Chinese L1 translators who completed en→zh and zh→en translation and post-editing tasks, yielding 104 eye-tracking sessions. Dependent measures were source reading time (TrtS), target reading time (TrtT), and target production duration (Dur). Predictors were derived from two model architectures, a decoder-only language model (LM) and an encoder–decoder neural machine translation (NMT) model, and they included monolingual surprisal, translation surprisal with source context, and attention features computed from models’ internal weights. Analyses showed that LM surprisal provided the strongest account of target reading, while source reading was most strongly predicted by encoder self-attention with LM surprisal, a robust secondary predictor, and target production duration drew on both LM and NMT translation surprisal. Direction effects were broader than task effects, especially on target measures. These findings suggest that although translation reading is bilingual in task structure, cumulative reading time is best explained by monolingual LM surprisal, whereas production duration additionally reflects NMT translation surprisal and revision behavior. Full article

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12 pages, 1246 KB

Open AccessArticle

Correlation Between Accommodative Facility and Light-Evoked Pupil Responses in Individuals with History of Mild Traumatic Brain Injury

by Curt Fritts-Davis, Andrew T. E. Hartwick and Marjean T. Kulp

J. Eye Mov. Res. 2026, 19(3), 65; https://doi.org/10.3390/jemr19030065 - 8 Jun 2026

Abstract

Introduction: Previous studies have shown those with a history of a traumatic brain injury (TBI) have altered pupillary light responses compared with those without a history of TBI. Those with a history of TBI are also more likely to have accommodative deficits. We [...] Read more.

Introduction: Previous studies have shown those with a history of a traumatic brain injury (TBI) have altered pupillary light responses compared with those without a history of TBI. Those with a history of TBI are also more likely to have accommodative deficits. We investigated the relationship between light-evoked pupil dynamics and accommodative function in individuals who have previously experienced a TBI. Methods: A total of 17 participants with a history of mild TBI were recruited. Pupil metrics were measured using a commercial pupillometer and included baseline diameter, latency, constriction amplitude, average constriction velocity, peak constriction velocity and peak dilation velocity. Accommodative function was assessed using clinical measurements of facility and amplitude. Pupil metrics were compared among those with versus without accommodative dysfunction. Results: One-way ANCOVA testing (controlling for age and time since most recent TBI) comparing groups with and without accommodative dysfunction showed that those with accommodative dysfunction had significantly larger light-evoked pupil constriction amplitudes (p = 0.037) and significantly faster average constriction velocity (p = 0.007) compared with those without accommodative dysfunction. No significant differences were observed for other pupil metrics (p > 0.05 for all). ANCOVA testing (controlling for age and time since TBI) to determine whether decreased amplitude of accommodation or facility was more strongly related to the differences in pupil metrics observed between those with versus without accommodative dysfunction, showed significantly larger light-evoked pupil constriction amplitudes (p = 0.007) and significantly faster average constriction velocity (p = 0.002) among those with reduced accommodative facility compared with those with normal accommodative facility. No statistically significant differences were observed between those with reduced versus normal accommodative amplitude (p ≥ 0.07). Among all participants, monocular accommodative facility measures were significantly correlated with greater pupil constriction amplitude (right eye: rho = −0.721, p = 0.001; left eye: rho = −0.65, p = 0.005), and greater average constriction velocity (right eye: rho = −0.58, p = 0.015; left eye: rho = −0.57, p = 0.016). Conclusions: The results of this small-sample study suggest that accommodative function and light-evoked pupillary dynamics are correlated in individuals with a history of TBI. Those with accommodative dysfunction showed greater pupil constriction amplitudes and velocities and this relationship may reflect shared autonomic or oculomotor mechanisms. Full article

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29 pages, 6910 KB

Open AccessArticle

An Eye-Tracking and Forecasting Experiment on Consumer Purchasing Decisions Through Product Reviews

by Seda Busra Sarac, Kazim Baris Atici, Ismail Bezci, Ata Erinc Dansuk and Fatma Semira Yildirim

J. Eye Mov. Res. 2026, 19(3), 64; https://doi.org/10.3390/jemr19030064 - 6 Jun 2026

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Abstract

This study aims to provide insight into consumer purchasing decisions by integrating eye-tracking data with forecasting techniques. First, the study investigates how consumption motives (hedonic vs. utilitarian) and purchasing purposes (for oneself vs. for others) influence visual attention and decision-making processes. An experimental [...] Read more.

This study aims to provide insight into consumer purchasing decisions by integrating eye-tracking data with forecasting techniques. First, the study investigates how consumption motives (hedonic vs. utilitarian) and purchasing purposes (for oneself vs. for others) influence visual attention and decision-making processes. An experimental design was conducted with 128 participants in a simulated online shopping environment, where eye-tracking data were collected based on fixation counts and durations across defined Areas of Interest (AOIs). Second, a total of 20 input features were collected, comprising fixation counts and fixation durations for 10 review-related Areas of Interest (AOIs), and these features were evaluated across the experimental scenarios, while the binary output variable represented the participant’s purchase decision. These biometric features, together with scenario information, were used to forecast purchasing decisions using six machine-learning methods, including Artificial Neural Networks, Random Forest, Support Vector Machine, K-Nearest Neighbors, Naive Bayes, and Logistic Regression. The results indicate that consumers’ visual attention aligns with their consumption motives and purchasing purposes, revealing distinct gaze patterns across different scenarios. In the forecasting phase, the accuracy of different methods for predicting purchasing decisions using review-related eye-tracking data is evaluated. Support Vector Machines achieved the highest overall accuracy, approximately 59–60% across the evaluated datasets, compared with a validation-specific majority-class baseline of 53.85%. This corresponds to a modest improvement of approximately 5.15–6.15 percentage points over the naive benchmark. Overall, the findings suggest that objectively recorded review-related eye-tracking data can be operationalized as behavioral input features in a machine-learning-based purchase-decision classification framework, highlighting the methodological value of integrating eye-tracking insights with consumer behavior forecasting. Full article

(This article belongs to the Special Issue Eye Tracking and Visualization)

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18 pages, 660 KB

Open AccessArticle

Cognitive Mechanisms of Referential Ambiguity Resolution in L2 Russian by Chinese Learners: Evidence from Eye-Tracking

by Tian Ran, Lijun Guo and Hong Xu

J. Eye Mov. Res. 2026, 19(3), 63; https://doi.org/10.3390/jemr19030063 - 3 Jun 2026

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Abstract

A central question in second language (L2) sentence processing concerns how learners resolve referential ambiguity in real time, particularly when cues from their first language (L1) conflict with those of the target language. Given the substantial typological distance between Chinese (an analytic language) [...] Read more.

A central question in second language (L2) sentence processing concerns how learners resolve referential ambiguity in real time, particularly when cues from their first language (L1) conflict with those of the target language. Given the substantial typological distance between Chinese (an analytic language) and Russian (a highly inflectional language), this study employs eye-tracking methodology to investigate the developmental trajectory of the cognitive mechanisms in referential ambiguity resolution among Chinese learners of Russian. The results revealed proficiency-related differences in ambiguity processing. Both proficiency groups showed increased processing difficulty when encountering ambiguous pronouns, indicating that referential ambiguity imposed a measurable online cost. High-proficiency learners read more efficiently overall, whereas low-proficiency learners showed a stronger first-mention anchoring pattern. These findings suggest that increasing L2 proficiency is associated with changes in processing efficiency and cue weighting during referential resolution. Notably, even high-proficiency learners did not categorically rely on Russian gender agreement to resolve reference in the morphologically disambiguated condition, suggesting that the integration of morphosyntactic cues into real-time reference resolution remains effortful at advanced proficiency. The study contributes eye-tracking evidence on how Chinese-speaking learners manage referential ambiguity in a morphologically rich L2. Full article

(This article belongs to the Special Issue Insights from Eye-Tracking on Second Language Learning and Processing)

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48 pages, 13281 KB

Open AccessArticle

Characterizing Visual Neurosurgical Expertise in Brain MRI Visualization Using Eye-Tracking and 3D Fractal Dimension Analysis

by Poonam Kumari, Ghasem Azemi, Carlo Russo and Antonio Di Ieva

J. Eye Mov. Res. 2026, 19(3), 62; https://doi.org/10.3390/jemr19030062 - 2 Jun 2026

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Abstract

Eye-tracking has been utilized to characterize visual behavior in medical image visualization and interpretation, yet neurosurgeons remain underrepresented. Characterizing neurosurgery-specific visual expertise is important for understanding expert search strategies, informing training, and developing computational models. This study examined gaze behavior in naïve observers [...] Read more.

Eye-tracking has been utilized to characterize visual behavior in medical image visualization and interpretation, yet neurosurgeons remain underrepresented. Characterizing neurosurgery-specific visual expertise is important for understanding expert search strategies, informing training, and developing computational models. This study examined gaze behavior in naïve observers (N_p = 29), neurosurgery registrars (N_p = 16), and consultant neurosurgeons (N_p = 24), viewing normal (N_p = 20) and pathological (N_p = 19) brain MR images under a free-viewing paradigm. To capture expertise-related characteristics, we analyzed two features at each fixation location: (i) fixation duration, reflecting temporal allocation of visual attention, and (ii) three-dimensional fractal dimension (3DFD) around each fixation location, quantifying local structural complexity. To assess pathological-type effects, we grouped similar pathologies into five stimulus groups. Linear mixed-effects modelling revealed systematic expertise-related differences, with experts exhibiting longer fixation durations in pathological stimulus groups and pathology-type-dependent complexity sampling. Combined fixation duration and 3DFD features captured complementary aspects of visual expertise, improving Random Forest classifier’s accuracy (>93%) compared to individual features, for all five stimulus groups. These findings highlight neurosurgery-specific markers of visual expertise and demonstrate that combining behavioral and image-derived features could underpin computational models and training tools that emulate expert-level strategies in neurosurgical image interpretation. Future work should evaluate its applicability to other medical domains. Full article

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22 pages, 367 KB

Open AccessArticle

Lexical Elaboration and Intentional Vocabulary Acquisition: An Eye-Tracking Study

by Taegang Lee, Byeongchae Choi, Sungmook Choi and Soo-Ok Kweon

J. Eye Mov. Res. 2026, 19(3), 61; https://doi.org/10.3390/jemr19030061 - 1 Jun 2026

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Abstract

Prior research on lexical elaboration (providing additional information about unfamiliar words) has yielded non-significant effects on incidental vocabulary acquisition. Building on this, the present study used eye-tracking technology to examine whether similar results replicate under intentional learning conditions. Participants were Korean undergraduate students [...] Read more.

Prior research on lexical elaboration (providing additional information about unfamiliar words) has yielded non-significant effects on incidental vocabulary acquisition. Building on this, the present study used eye-tracking technology to examine whether similar results replicate under intentional learning conditions. Participants were Korean undergraduate students (N = 67) who were randomly assigned to one of three groups: baseline, unenhanced elaboration, or enhanced elaboration. They were instructed to read an English text twice while their eye movements were recorded. After reading, they responded to two forewarned vocabulary assessments measuring form and meaning recall. Overall, the unenhanced elaboration group exhibited distinct target-word processing patterns and higher meaning recall performance compared to the baseline group, whereas the enhanced elaboration group’s outcomes were comparable to the baseline group. For instance, generalized linear mixed-effects modeling (GLMM) revealed that while the unenhanced elaboration group maintained stable reading times on target words across the two readings, the baseline and enhanced elaboration groups exhibited significant reductions. Furthermore, only the unenhanced elaboration group significantly outperformed the baseline group in meaning recall. Collectively, our findings suggest that lexical elaboration, particularly without input enhancement, may facilitate vocabulary acquisition under intentional learning conditions by promoting more sustained attention to unfamiliar words. Full article

(This article belongs to the Special Issue Insights from Eye-Tracking on Second Language Learning and Processing)

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18 pages, 5301 KB

Open AccessArticle

The Geometry of Suspicion: Visual Exploration Patterns in Email Phishing Detection

by Francesco Di Nocera, Lorenzo Arciulo, Giorgia Tempestini, Pierpaolo Zivi, Giulio Errico and Fabio Ferlazzo

J. Eye Mov. Res. 2026, 19(3), 60; https://doi.org/10.3390/jemr19030060 - 1 Jun 2026

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Abstract

This study examined visual exploration strategies in phishing-email detection by integrating conventional AOI-based eye-tracking measures with a complementary scene-based indicator, the Nearest Neighbor Index (NNI), to capture the global spatial organization of fixations. Thirty-two volunteers completed an email-classification task involving 106 static email [...] Read more.

This study examined visual exploration strategies in phishing-email detection by integrating conventional AOI-based eye-tracking measures with a complementary scene-based indicator, the Nearest Neighbor Index (NNI), to capture the global spatial organization of fixations. Thirty-two volunteers completed an email-classification task involving 106 static email stimuli; data from 30 participants were included in the final analyses. For each stimulus, participants judged whether the email was authentic or phishing, allowing for the computation of eye-tracking metrics across Signal Detection Theory classification outcomes. Concerning the NNI, the results showed that the spatial distribution of fixations was higher for suspicious than for non-suspicious emails, indicating a broader visual exploration pattern under higher task demands. More importantly, correct and incorrect responses differed reliably: hits were associated with more dispersed and regular fixation patterns, whereas false alarms were associated with more clustered scanning; misses showed a descriptively similar tendency that did not survive correction for multiple comparisons. Participants also responded faster when correct than when incorrect. When cybersecurity awareness (CAIN) was included as a mean-centered covariate, the primary effects of Signal and Outcome on NNI and decision time remained significant, indicating that the experimental effects are robust to individual differences in cybersecurity knowledge. However, CAIN did not emerge as a reliable predictor of eye-tracking measures within these models, suggesting that its role operates more at the level of classification performance than moment-by-moment gaze organization. Full article

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15 pages, 3237 KB

Open AccessArticle

Active Vision in Driving: Joint Modeling of Scanpaths and Risk Perception

by Chao Gou, Yueyao Lin, Yuchen Zhou, Wenjie Shi and Jincheng Jiang

J. Eye Mov. Res. 2026, 19(3), 59; https://doi.org/10.3390/jemr19030059 - 1 Jun 2026

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Abstract

Under the Active Vision hypothesis, eye movements are not passive responses to visual stimuli but are actively guided by task demands and internal goals. In driving, scanpaths may therefore reflect an ongoing process of information sampling for risk assessment. However, current computational models [...] Read more.

Under the Active Vision hypothesis, eye movements are not passive responses to visual stimuli but are actively guided by task demands and internal goals. In driving, scanpaths may therefore reflect an ongoing process of information sampling for risk assessment. However, current computational models often isolate scanpath prediction from risk assessment, overlooking their intrinsic cognitive coupling. In this study, we investigate whether driver scanpaths and traffic risk perception can be jointly modeled within a unified framework. We propose a computational approach based on the introduced Adversarial Inverse Reinforcement Learning (AIRL), where gaze behavior is interpreted as a policy that maximizes a latent safety-related reward. By employing a generator to simulate human-like sequences of fixations and saccades, and a discriminator to approximate the internal reward signal, our framework ensures that generated scanpaths synergistically inform downstream risk perception. To facilitate this research, we constructed the BDDA dataset, aggregating over 13,000 spatio-temporal gaze points with explicit risk annotations to study this joint mechanism. Experimental results indicate that simultaneously modeling the “where” (scanpath dynamics) and the “why” (risk perception) significantly outperforms the compared baseline methods on the proposed BDDA dataset. These findings provide computational evidence for a functional coupling between visual attention and risk perception, supporting the view that eye movements serve as an active mechanism for acquiring task-relevant information in safety-critical environments. Full article

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18 pages, 1419 KB

Open AccessArticle

Effects of Notation Type and Score Difficulty on Eye Movements During Erhu Sight-Reading

by Siyu Li, Yi Weng and Xiyu Wu

J. Eye Mov. Res. 2026, 19(3), 58; https://doi.org/10.3390/jemr19030058 - 27 May 2026

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Abstract

A parallel notational system comprising number notation and staff notation has long been employed in the pedagogy of traditional Chinese instrumental music. However, it remains unclear how these two representationally distinct notational systems shape performers’ visual-processing strategies. Therefore, using eye-tracking methods, the present [...] Read more.

A parallel notational system comprising number notation and staff notation has long been employed in the pedagogy of traditional Chinese instrumental music. However, it remains unclear how these two representationally distinct notational systems shape performers’ visual-processing strategies. Therefore, using eye-tracking methods, the present study examined the interactive effects of notation type and score difficulty on visual–cognitive processing in a sight-reading task performed on the erhu, a Chinese two-stringed bowed musical instrument. The results showed that increased difficulty generally led to greater fixation-related load and a contracted eye–hand span (EHS). Interaction analyses further indicated that numbered notation was associated with a more favorable eye-movement profile at intermediate difficulty, whereas this pattern was attenuated under difficult score conditions and accompanied by increased processing demands. In contrast, the eye-movement measures in staff notation appeared to be less sensitive to difficulty-related changes than those observed in numbered notation, a pattern that may reflect differences in the representational structures of the two notational systems. Collectively, these findings suggest that notational symbols may modulate sight-reading strategies among trained erhu students, providing preliminary evidence for music reading across different notational systems. Full article

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21 pages, 1034 KB

Open AccessArticle

Machine Learning Integration of Eye-Tracking and Cognitive Screening for Detecting Cognitive Impairment

by Joan Goset, Clara Mestre, Valldeflors Vinuela-Navarro, Mikel Aldaba, Mar Ariza, Neus Cano, Bàrbara Delàs, Olga Gelonch, Maite Garolera, REHAB Project Collaborative Group and Meritxell Vilaseca

J. Eye Mov. Res. 2026, 19(3), 57; https://doi.org/10.3390/jemr19030057 - 20 May 2026

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Abstract

Cognitive impairment is common in Post-COVID-19 Condition (PCC), yet full neuropsychological testing remains resource-intensive. Because eye movements are known to be altered in certain cognitive disorders, Eye-Tracking (ET) offers a fast, non-invasive complementary approach for large-scale screening. This study aimed to predict neuropsychological [...] Read more.

Cognitive impairment is common in Post-COVID-19 Condition (PCC), yet full neuropsychological testing remains resource-intensive. Because eye movements are known to be altered in certain cognitive disorders, Eye-Tracking (ET) offers a fast, non-invasive complementary approach for large-scale screening. This study aimed to predict neuropsychological test scores of participants with PCC from ET metrics using machine and deep learning models. ET data was collected from 172 participants performing a battery of visual tasks designed to elicit smooth pursuit and fixational eye movements, as well as pupil responses to light. Cognitive performance was assessed through established neuropsychological tests. We applied regression and classification models (e.g., Random Forest, XGBoost, and deep neural networks) to predict neuropsychological performance. Models were trained using ET data alone and in combination with the Montreal Cognitive Assessment (MoCA) scores, a widely used neuropsychological test for global cognitive screening. Although predicting individual test scores was challenging, combining them into a global composite measure improved performance. Model sensitivity and specificity reached 88% and 34% using ET data alone, and 87% and 60% when integrating ET with MoCA. This last trained model outperformed the conventional MoCA, highlighting the potential of ET as a rapid screening support tool for cognitive assessment. Full article

(This article belongs to the Special Issue The Future Challenges of Eye Tracking Technologies)

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29 pages, 2543 KB

Open AccessArticle

Ab Initio Binocular Formulation of Listing’s Law

by Jacek Turski

J. Eye Mov. Res. 2026, 19(3), 56; https://doi.org/10.3390/jemr19030056 - 16 May 2026

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Abstract

Human eyes do not have perfectly aligned optical components; the fovea is displaced from the posterior pole, and the crystalline lens is tilted away from the eye’s optical axis. Important in the study of vision quality, it is included here in binocular and [...] Read more.

Human eyes do not have perfectly aligned optical components; the fovea is displaced from the posterior pole, and the crystalline lens is tilted away from the eye’s optical axis. Important in the study of vision quality, it is included here in binocular and oculomotor research. In the binocular system, with the eye’s optical asymmetry, all axes differ. The eye’s posture change is decomposed into the torsion-free part that gives the change in visual axis direction and the torsional part that best approximates the rotation about the lens’s optical axis. This geometric formulation, supported by computer simulations and modern ophthalmology studies, leads to binocular Listing’s law and the related half-angle rule, important for oculomotor control by constraining the eye’s redundant torsional degree of freedom. The eye’s primary position and the Listing plane, indispensable ingredients of Listing’s law, are replaced with the binocular eyes’ posture corresponding to the eye muscles’ natural tonus resting position, which serves as a zero-reference level for convergence effort. Further, the binocular constraints couple 3D changes in the torsional positions of the eyes within the ab initio formulation of Listing’s law here, which was previously proposed ad hoc. Finally, the noncommutativity rule underlying Listing’s law and the half-angle rule are discussed by specifying the configuration space of sequences of fixations of binocularly constrained eyes, which are visualized in 3D simulations. The results obtained in this study should be a part of the answers to the questions posted in the literature on the relevance of Listing’s law to clinical practices. Full article

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19 pages, 901 KB

Open AccessArticle

Eye-Tracking Evidence That Verifiable Explanations Support Visual Evidence Checking in AI-Assisted Chest Radiograph Interpretation

by Yong Han, Wumin Ouyang, Hemin Du, Mengyun Ma and Guanning Wang

J. Eye Mov. Res. 2026, 19(3), 55; https://doi.org/10.3390/jemr19030055 - 15 May 2026

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Abstract

Evaluations of medical artificial intelligence (AI) explanations often rely on self-reported trust, perceived usefulness, acceptance, or final decision outcomes, while less directly characterizing whether users check evidence around AI outputs during decision making. In AI-assisted chest radiograph interpretation, a critical process-level question is [...] Read more.

Evaluations of medical artificial intelligence (AI) explanations often rely on self-reported trust, perceived usefulness, acceptance, or final decision outcomes, while less directly characterizing whether users check evidence around AI outputs during decision making. In AI-assisted chest radiograph interpretation, a critical process-level question is whether users return from the AI output to the original image evidence when further scrutiny is needed. To address this question, we examined whether verifiable explanations—explanations designed to make AI recommendations checkable against the original image evidence—are associated with process markers of visual evidence checking in AI-assisted chest radiograph interpretation using eye-tracking and human-factors process measures. A 2 × 2 between-subjects experiment manipulated verifiable explanations (present vs. absent) and risk context (high vs. low), with AI recommendation correctness embedded at the trial level. Fifty-six clinically trained participants each completed 24 interpretation trials. Analyses focused primarily on gaze transitions between the AI output and the original image and dwell time on the original image, with response time and exploratory verification-related behavioral states used as auxiliary process measures. Verifiable explanations did not simply increase acceptance of AI recommendations. Instead, when AI recommendations were incorrect, they were most clearly associated with more frequent AI–image transitions and longer absolute dwell time on the original image evidence. Exploratory state-based analyses further suggested a lower tendency toward no-verify adopt under incorrect AI recommendations, but these findings were treated as complementary rather than primary evidence. Overall, the value of verifiable explanations lies not only in final decisions but in whether they make AI recommendations more inspectable against the original evidence. These findings provide eye-tracking evidence consistent with visual evidence checking in AI-assisted diagnostic interfaces and underscore the value of process-sensitive human-factors measures in medical AI evaluation. Full article

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17 pages, 1376 KB

Open AccessArticle

Cognitive Mechanisms of Predictive Processing in Chinese Reading: An Eye-Movement Analysis Based on the Ex-Gaussian Distribution

by Wen Tong, Xiaojiao Li, Yingdi Liu and Zhifang Liu

J. Eye Mov. Res. 2026, 19(3), 54; https://doi.org/10.3390/jemr19030054 - 15 May 2026

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Abstract

This study employed the Ex-Gaussian distribution model to analyse eye-tracking data, to elucidate the cognitive mechanisms underlying predictive processing during Chinese reading. Using a single-factor, two-level within-subjects design (contextual predictability: high vs. low), data from 32 adult readers were analysed across the pre-target [...] Read more.

This study employed the Ex-Gaussian distribution model to analyse eye-tracking data, to elucidate the cognitive mechanisms underlying predictive processing during Chinese reading. Using a single-factor, two-level within-subjects design (contextual predictability: high vs. low), data from 32 adult readers were analysed across the pre-target and target word regions. The results revealed that predictive reading follows a three-stage cognitive model. In the expectation generation stage (pre-target region), a significant negative τ effect indicated resource pre-allocation driven by strong contextual constraints, thereby facilitating the construction of predictive lexical representations. In the verification and integration stage (target word region), a significant negative μ effect in the later measurement window indicated that successful prediction–input matching accelerated lexical identification and enhanced integration efficiency; the σ parameter did not reach significance in either measurement window. In the conflict resolution stage (pre-target and target word regions), a significant positive τ effect indicated that verification failure triggered lexical activation competition at the target word, driving regressive fixations to the pre-target region for contextual reanalysis; conflict resolution costs were markedly higher under the low-predictability condition, owing to the absence of a dominant activation anchor. These findings suggest that contextual predictability influences reading through a dual mechanism: the μ parameter modulates the automatic processing speed of lexical identification, whereas the τ parameter regulates the cognitive control processes underlying expectation generation and conflict resolution. Together, these results provide empirical support for the integration of predictive coding theory and cognitive control frameworks. Full article

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14 pages, 828 KB

Open AccessArticle

Diagnostic Criteria for Convergence Excess: Diagnostic Validity of Clinical Signs Associated with Near Esophoria

by Pilar Cacho-Martínez, Mario Cantó-Cerdán, Zaíra Cervera-Sánchez and Ángel García-Muñoz

J. Eye Mov. Res. 2026, 19(3), 53; https://doi.org/10.3390/jemr19030053 - 14 May 2026

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Abstract

To propose which tests may be used for diagnosing convergence excess. A prospective study of a consecutive clinical sample was performed. Patients (18–35 years) attending optometric care underwent subjective refraction, cover test, and Symptom Questionnaire for Visual Dysfunctions (SQVD). Based on cover test [...] Read more.

To propose which tests may be used for diagnosing convergence excess. A prospective study of a consecutive clinical sample was performed. Patients (18–35 years) attending optometric care underwent subjective refraction, cover test, and Symptom Questionnaire for Visual Dysfunctions (SQVD). Based on cover test and SQVD scores, two groups were recruited: 64 symptomatic subjects with near esophoria and 64 asymptomatic with normal binocular vision. Accommodative and binocular tests were assessed, identifying those with significant statistical differences between groups. Diagnostic validity was analysed using ROC curves, sensitivity, specificity, and likelihood ratios. A serial testing strategy combining tests was also evaluated. ROC analysis showed best diagnostic accuracy for binocular accommodative facility (BAF) failing with −2.00 D (area under the curve, AUC = 0.865) and vergence facility (VF) failing with base-in prisms (AUC = 0.864). Using cutoffs from ROC analysis (BAF: ≤8.25 cpm and VF ≤ 12.75 cpm), their combination showed best validity (S = 0.625, Sp = 0.938, LR+ = 10, LR− = 0.4). The combined AUC was 0.932. The proposal for diagnosing convergence excess is to use, in addition to near esophoria with normal distance heterophoria, the combination of failing BAF with negative lenses and failing vergence facility with base-in prisms. Full article

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19 pages, 1233 KB

Open AccessArticle

Effects of Word Frequency, Word Length, and Visual Complexity on Chinese Sentence Oral Reading: An Eye Movement Comparison Study Between Children and Adults

by Kunyu Lian, Junhui Pei, Feifei Liang, Jie Ma, Rong Lian and Xuejun Bai

J. Eye Mov. Res. 2026, 19(3), 52; https://doi.org/10.3390/jemr19030052 - 13 May 2026

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Abstract

This study investigated how word frequency, word length and visual complexity affect lexical processing during Chinese sentence oral reading, and whether these effects differ between developing and skilled readers. Third-grade children and adults read sentences aloud while their eye movements were recorded with [...] Read more.

This study investigated how word frequency, word length and visual complexity affect lexical processing during Chinese sentence oral reading, and whether these effects differ between developing and skilled readers. Third-grade children and adults read sentences aloud while their eye movements were recorded with an EyeLink 1000 Plus eye-tracker. Linear mixed-effects models revealed three main findings. First, children showed larger word-frequency and visual-complexity effects than adults, indicating less efficient lexical processing in developing readers. Second, word length moderated the effects of word frequency and visual complexity. Frequency effects were amplified for two-character words, whereas visual-complexity effects were stronger for single-character words on early measures and followed a different pattern on some late measures. Third, at the sentence level, children exhibited shorter forward saccades, more regressions and longer total reading times than adults. These findings provide developmental evidence for the visual and linguistic constraints hypothesis and show how visual recognition and overt phonological output jointly shape foveal lexical processing in Chinese oral reading. Full article

(This article belongs to the Special Issue Eye Movements in Reading and Related Difficulties)

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23 pages, 9319 KB

Open AccessArticle

Eye Movement Patterns as Robust Biomarkers for Schizophrenia Identification Using a Novel Data Transformation Approach

by Lijin Huang, Senhao Li, Zhi Liu, Dan Zhang, Lihua Xu, Tianhong Zhang and Jijun Wang

J. Eye Mov. Res. 2026, 19(3), 51; https://doi.org/10.3390/jemr19030051 - 11 May 2026

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Abstract

Although eye movement abnormalities are documented in schizophrenia (SZ), their translation into objective diagnostic biomarkers remains limited. In this study, we propose a novel identification framework that integrates a Sparsity-Scoring Kernel Entropy Component Analysis (SSKECA) algorithm with a multidimensional eye movement feature set. [...] Read more.

Although eye movement abnormalities are documented in schizophrenia (SZ), their translation into objective diagnostic biomarkers remains limited. In this study, we propose a novel identification framework that integrates a Sparsity-Scoring Kernel Entropy Component Analysis (SSKECA) algorithm with a multidimensional eye movement feature set. A total of 40 patients with SZ and 50 healthy controls (HC) completed a free-viewing task involving 100 distinct semantic images. The proposed SSKECA algorithm optimizes multidimensional feature representations to capture latent eye movement patterns characteristic of SZ. The SSKECA–AdaBoost model achieved competitive performance, with an accuracy of 0.933 and an area under the receiver operating characteristic curve (AUC) of 0.960. Notably, when restricted to only 25 highly discriminative images, the SSKECA–XGBoost model achieved an accuracy of 0.922. Feature ablation analyses not only reproduced previously reported eye movement findings but also highlighted additional atypical patterns. Misclassification analyses revealed more pronounced eye movement deficits in incorrectly classified SZ patients. Overall, the proposed framework translates complex eye movement patterns into robust indicators for subject-level identification, offering a practical and efficient tool to support objective assessment in SZ. Full article

(This article belongs to the Special Issue Digital Advances in Binocular Vision and Eye Movement Assessment)

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24 pages, 2218 KB

Open AccessArticle

Quantification of Cognitive States via Eye Tracking and Using Artificial Intelligence to Analyze Virtual Reality Learning Experiences

by Haram Choi and Sanghun Nam

J. Eye Mov. Res. 2026, 19(3), 50; https://doi.org/10.3390/jemr19030050 - 5 May 2026

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Abstract

Virtual reality (VR) technology provides a high sense of immersion and presence to users and can enhance the engagement and performance of learning. However, the VR learning environment introduces more complex audio–visual stimuli than the traditional multimedia learning environment. These excessive stimuli cause [...] Read more.

Virtual reality (VR) technology provides a high sense of immersion and presence to users and can enhance the engagement and performance of learning. However, the VR learning environment introduces more complex audio–visual stimuli than the traditional multimedia learning environment. These excessive stimuli cause negative effects such as distraction and cognitive overload. To minimize these negative impacts and improve the learning environment, we must evaluate learners’ cognitive states under the VR environment. Cognitive states can be evaluated subjectively (e.g., through questionnaires) or objectively (e.g., using biometric signals). Subjective and objective methods must be used simultaneously, and correlations between them must be analyzed for quantifying objective measures. The accurate detection of cognitive states is challenging for traditional statistical analysis methods, necessitating the exploration of artificial intelligence (AI) techniques that can classify cognitive states. This study develops a VR learning experience evaluation system based on eye-tracking data. Cognitive states during VR learning are classified as cognitive overload, immersion, and distraction. Correlations between each cognitive state and eye-tracking metrics are evaluated, and the possibility of cognitive-state quantification is discussed. An LSTM-based model developed in this study classified cognitive states from eye-tracking data with moderate accuracy (75.60%) under a subject-independent validation setting. Full article

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16 pages, 1585 KB

Open AccessArticle

Oculomotor Vergence Eye Movement Endurance in Normal Vision via Virtual Reality-Integrated Eye Tracking

by Fatema F. Hirani, Farzin Hajebrahimi and Tara L. Alvarez

J. Eye Mov. Res. 2026, 19(3), 49; https://doi.org/10.3390/jemr19030049 - 5 May 2026

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Abstract

Modern societies are becoming increasingly dependent on electronics, leading to an increase in visual symptoms. Vergence endurance, the ability to sustain performance, may serve as a quantitative metric to complement symptom surveys to assess vergence performance during near visual tasks. To quantify vergence [...] Read more.

Modern societies are becoming increasingly dependent on electronics, leading to an increase in visual symptoms. Vergence endurance, the ability to sustain performance, may serve as a quantitative metric to complement symptom surveys to assess vergence performance during near visual tasks. To quantify vergence endurance, 48 participants, aged 15 to 23 years with normal binocular vision, completed a 15 min symmetrical disparity vergence step task to assess potential changes in peak vergence speed over the course of the experiment. Peak velocity, final amplitude, and the slope of the linear regression fit of the peak velocity as a function of stimulus recording were quantified for convergence and divergence responses using an eye tracker integrated in a virtual reality headset. Peak velocity was sustained by 63% and 69% of participants for convergence and divergence eye movements, respectively. Convergence and divergence responses were significantly different for peak velocity (p < 0.001) and vergence endurance (p < 0.03). The endurance metric tool has potential that may help shape future clinical applications for those with acquired brain injuries, including concussions or neurodegenerative diseases such as multiple sclerosis or Parkinson’s disease. Full article

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27 pages, 15688 KB

Open AccessArticle

Effects of Driving Task Demands and Information Load on AR-HUD Cognitive Efficiency: The Moderating Role of Working Memory Capacity in a VR-Based Simulated Driving Environment

by Jing Li, Min Lin, Xinyu Feng, Hua Zhang, Chuchu Wang and Yulian Ma

J. Eye Mov. Res. 2026, 19(3), 48; https://doi.org/10.3390/jemr19030048 - 3 May 2026

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Abstract

The driving scenario and information load jointly influence the cognitive efficiency of augmented reality head-up display (AR-HUD) interfaces. However, the moderating role of drivers’ working memory capacity (WMC) remains unclear. To investigate this mechanism, a simulated driving experiment with a mixed design was [...] Read more.

The driving scenario and information load jointly influence the cognitive efficiency of augmented reality head-up display (AR-HUD) interfaces. However, the moderating role of drivers’ working memory capacity (WMC) remains unclear. To investigate this mechanism, a simulated driving experiment with a mixed design was conducted in a low-immersivity desktop virtual reality (VR) environment. First, 40 volunteers were screened using an automated operation span task, yielding 16 high- and low-WMC participants. They then drove under three scenarios (urban intersection, expressway, construction zone) and six levels of AR-HUD visual information load. Generalized linear models were applied to the reaction time, fixation duration, and pupil diameter. The results revealed a significant three-way interaction among WMC, scenario, and information load. High-WMC drivers maintained faster responses and lower subjective loads up to Levels 4–6, adopting a deep processing strategy; low-WMC drivers already showed cognitive overload at Level 4 and above, requiring an optimal load range of Level 2–3. The construction zone induced the steepest increase in cognitive load, whereas the expressway markedly reduced sensitivity to additional visual information. Therefore, the optimal AR-HUD information load must be adapted to drivers’ WMC: high-WMC drivers can safely handle Levels 4–6 in low- or medium-demand scenarios, whereas low-WMC drivers require a minimalist presentation of Levels 2–3 in high-demand situations. This study provides quantitative, empirically grounded guidelines for designing cognitively adaptive AR-HUD interfaces. Full article

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23 pages, 2993 KB

Open AccessArticle

Differential Fixation and Eye Alignment Patterns in Strabismus with and Without Amblyopia Across Viewing Conditions

by Archayeeta Rakshit, Ibrahim M. Quagraine, Gokce Busra Cakir, Aasef G. Shaikh and Fatema F. Ghasia

J. Eye Mov. Res. 2026, 19(3), 47; https://doi.org/10.3390/jemr19030047 - 3 May 2026

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Abstract

Fixation instability (FI) and vergence instability (VI) in amblyopia and strabismus are associated with disrupted physiologic fixation eye movements (FEMs). This study examined how viewing conditions affect FEM patterns in strabismic subjects with and without amblyopia. FEMs of the non-dominant/amblyopic and dominant/fellow eyes [...] Read more.

Fixation instability (FI) and vergence instability (VI) in amblyopia and strabismus are associated with disrupted physiologic fixation eye movements (FEMs). This study examined how viewing conditions affect FEM patterns in strabismic subjects with and without amblyopia. FEMs of the non-dominant/amblyopic and dominant/fellow eyes were recorded using video-oculography during both-eye viewing (BEV), fellow/dominant-eye viewing (FEV/DEV), and amblyopic/non-dominant-eye viewing (AEV/NDEV) in strabismic subjects with amblyopia (SA, n = 56), without amblyopia (S, n = 19), and controls (C, n = 25). FI, VI, fast FEM amplitudes, slow FEM velocities, and time-based control of eye deviation were analyzed. The SA group showed the greatest FI in the amblyopic eye during AEV compared with the fellow eye during FEV, whereas minimal inter-ocular FI differences were observed in the S group and controls. Under monocular viewing, both SA and S groups exhibited increased FI in the non-viewing eye and higher VI than controls. Regression analyses indicated that visual acuity deficits primarily influenced viewing-eye FI and FEM dynamics, while strabismus mainly affected non-viewing-eye FI and slow FEMs. C and S groups showed the least eye deviation during BEV, whereas the SA group showed the least eye deviation—but the highest VI—during AEV, indicating a distinct pattern of incomitance. Distinct FEM patterns shaped by viewing conditions may reflect underlying visuomotor control mechanisms and serve as biomarkers for AI (artificial intelligence)-based classification. Full article

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13 pages, 323 KB

Open AccessArticle

Oculometric Function More Strongly Predicts Working Memory than Stress in Military Officers

by Mollie McGuire, Neda Bahrani, Quinn Kennedy and Dorion Liston

J. Eye Mov. Res. 2026, 19(3), 46; https://doi.org/10.3390/jemr19030046 - 2 May 2026

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Abstract

Working memory, the capacity to store information for near-immediate use, and visual attention, the ability to focus on task-relevant information, are integral skills for military personnel. In civilian populations, stress is associated with worse skills. However, little is known about the relationship between [...] Read more.

Working memory, the capacity to store information for near-immediate use, and visual attention, the ability to focus on task-relevant information, are integral skills for military personnel. In civilian populations, stress is associated with worse skills. However, little is known about the relationship between stress, working memory, and visual attention in military officers, who are trained to handle acute stress and operate in high-stress environments. Thirty-three military officers completed a working memory test, a Perceived Stress Questionnaire (PSQ), and an oculometric assessment of visual tracking. The oculometric test was a modified step-ramp test that produces 10 z-scored metrics. Working memory and executive function were assessed via the n-back task. Oculometric performance and self-reported stress levels were independently associated with n-back accuracy, explaining 67% of the variance (adjusted R², n = 30). The association between oculometric performance and n-back accuracy was driven by directional anisotropy, directional noise and proportion of smooth pursuit. The association between oculometric performance and stress was complicated by sex differences. Results have important implications for the assessment of cognitive readiness in military populations. The strong relationship between oculometric performance and working memory suggests that eye-tracking-based metrics may serve as candidate indicators of cognitive function under operational demands. Full article

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19 pages, 2494 KB

Open AccessArticle

Effects of Cognitive, Simulator, and Real-World Training on Novice Driver Gaze Behaviour: A Pre–Post Study

by Prem Sudhakar Lawrence and Aiswaryah Radhakrishnan

J. Eye Mov. Res. 2026, 19(3), 45; https://doi.org/10.3390/jemr19030045 - 30 Apr 2026

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Abstract

Novice drivers demonstrate inefficient visual scanning and elevated crash risk relative to experienced drivers. Different training programmes may influence gaze behaviour and performance in distinct ways. This study compared the impact of cognitive, simulator-based, and real-world training on visual attention and driving-related outcomes [...] Read more.

Novice drivers demonstrate inefficient visual scanning and elevated crash risk relative to experienced drivers. Different training programmes may influence gaze behaviour and performance in distinct ways. This study compared the impact of cognitive, simulator-based, and real-world training on visual attention and driving-related outcomes in novice drivers. Thirty novice drivers (18–27 years; ≤1 year driving experience) were randomized into three training groups (n = 10 each): cognitive training (PsyToolkit, Version 3.7.0), game-based simulator training, and supervised real-world driving. Baseline and post-training assessments included visuomotor performance (Fitts’ Law), attentional cueing (valid/invalid reaction time), simulator-based driving errors, and eye-tracking measures of gaze behaviour. Eye-tracking outcomes included dwell-time percentage and first-fixation order across predefined areas of interest (AOIs). Participants completed 10 consecutive days of modality-specific training. Cognitive training improved visuomotor performance and increased forward road monitoring. Game-based simulator training yielded the largest reductions in simulator driving errors, particularly lane deviations (Z = −2.89, p = 0.004). Real-world driving altered visual scanning patterns, with significant differences in rear-view mirror prioritization (p = 0.024). Across groups, gaze shifted from dashboard view toward safety-relevant AOIs. Training modifies novice drivers’ gaze behaviour in modality-specific ways, suggesting that a multimodal training approach may enhance visual attention and driving safety Full article

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15 pages, 852 KB

Open AccessArticle

Validating Temporal Eye Tracking Metrics as Orthogonal Biomarkers for Aggressive Traits: A Mixed-Effects Analysis

by Omar Alvarado-Cando, Oscar Casanova-Carvajal and José-Javier Serrano-Olmedo

J. Eye Mov. Res. 2026, 19(3), 44; https://doi.org/10.3390/jemr19030044 - 28 Apr 2026

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Abstract

Atypical visual attention to aversive or threatening stimuli is a clinically relevant feature of aggressive behavior. However, the developmental dissociation between sustained visual allocation and early orienting remains unclear. This study examined the temporal dynamics of visual attentional biases in a sample of [...] Read more.

Atypical visual attention to aversive or threatening stimuli is a clinically relevant feature of aggressive behavior. However, the developmental dissociation between sustained visual allocation and early orienting remains unclear. This study examined the temporal dynamics of visual attentional biases in a sample of 119 children and adolescents (51 males, 68 females), clinically and behaviorally categorized into aggressive and non-aggressive cohorts. Using a free-viewing paradigm with standardized emotional stimulus pairs selected from the International Affective Picture System (IAPS), eye-tracking analysis focused on first-fixation direction and dwell time. Inferential analyses were conducted using Linear Mixed-Effect Models (LMM) and Generalized Linear Mixed-Effects Models (GLMM). The linear model revealed a significant main effect of behavioral condition: individuals with aggressive traits, regardless of their stage of development, showed greater sustained visual allocation toward negative stimuli. In contrast, the GLMM for first-fixation direction identified a significant age-by-condition interaction, indicating that early orienting differences were more clearly expressed in the aggressive adolescent cohort. These findings suggest that sustained visual preference for negative content may represent a relatively stable correlate of aggressive traits, whereas early orienting differences may vary across developmental stages. Together, these two temporal eye-tracking measures may provide complementary information for future computational approaches to aggression screening. In conclusion, these two temporal oculomotor dimensions may provide a useful feature space for future machine-learning pipelines and may serve as complementary candidate markers for comparing computational predictions against clinically established ground truth in aggression screening research. Full article

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12 pages, 14012 KB

Open AccessArticle

Reversible Orbital Apex Syndrome

by Yakov Rabinovich, Inbal Man Peles, Zina Almer, Iris Ben Bassat-Mizrachi, Jonathan Sapir, Noa Hadar, Alon Zahavi and Nitza Goldenberg-Cohen

J. Eye Mov. Res. 2026, 19(3), 43; https://doi.org/10.3390/jemr19030043 - 27 Apr 2026

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Abstract

Orbital apex syndrome (OAS) is characterized by optic neuropathy and ophthalmoplegia and is generally associated with poor visual prognosis. The aim of this study was to describe patients with acute OAS who demonstrated substantial recovery of visual function and ocular motility. We retrospectively [...] Read more.

Orbital apex syndrome (OAS) is characterized by optic neuropathy and ophthalmoplegia and is generally associated with poor visual prognosis. The aim of this study was to describe patients with acute OAS who demonstrated substantial recovery of visual function and ocular motility. We retrospectively reviewed the medical records of patients treated for OAS at a tertiary medical center between 2019 and 2024 whose condition ultimately proved reversible. Data on demographics, clinical findings, imaging, management, and follow-up were collected. Six patients (three female, three male; age range 14–87 years) were included and followed for a median follow-up of 7 months (range 2–31). All presented with reduced vision and ophthalmoplegia of varying severity. Underlying etiologies included inflammatory disease (n = 2), lymphoma, infection, blunt trauma, and post-surgical OAS of undetermined etiology (n = 1 each). Treatment was directed at the underlying cause. Visual acuity ranged from 20/30 to hand motion (HM) at presentation and 20/15 to 20/60 at the final visit. Improvement in vision and ocular motility occurred after a median time to clinical improvement of 2.37 months (range 0.25–5 months). Near-complete recovery of ocular motility was observed in all patients, with only one retaining mild abduction limitation. These findings highlight a subset of OAS cases with favorable outcomes and emphasize the importance of early diagnosis and etiology-directed management. Full article

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25 pages, 703 KB

Open AccessReview

Eye-Tracking-Based Interventions for School-Age Specific Learning Disorders: A Narrative Review of Functional Assessment and Gaze-Contingent Training

by Pierluigi Diotaiuti, Francesco Di Siena, Salvatore Vitiello, Alessandra Zanon, Pio Alfredo Di Tore and Stefania Mancone

J. Eye Mov. Res. 2026, 19(3), 42; https://doi.org/10.3390/jemr19030042 - 24 Apr 2026

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Abstract

Eye tracking (ET) provides process-level indices of how students sample task-relevant information during core academic activities. In school-age learners (6–18 years) with specific learning disorders (SLDs; dyslexia, dysgraphia, and dyscalculia), ET can complement behavioural assessment by quantifying oculomotor patterns linked to decoding, model–production [...] Read more.

Eye tracking (ET) provides process-level indices of how students sample task-relevant information during core academic activities. In school-age learners (6–18 years) with specific learning disorders (SLDs; dyslexia, dysgraphia, and dyscalculia), ET can complement behavioural assessment by quantifying oculomotor patterns linked to decoding, model–production coordination, and stepwise strategy execution. This narrative review synthesises ET findings in SLD across reading, handwriting/copying, and arithmetic and translates them into an applied framework for school-oriented use. We summarise key metrics and Areas of Interest (AOI)-based analyses, highlight technical and data-quality requirements for valid acquisition in educational settings, and outline compact functional assessment protocols integrated with standard academic and neuropsychological measures. Building on these foundations, we propose six hypothesis-driven gaze-contingent paradigms (H1–H6) as preliminary models for future experimental testing rather than as established interventions, and we map each to its current level of empirical support, specifying primary gaze outcomes and curriculum-relevant behavioural endpoints. We emphasise that eye-movement findings in specific learning disorders are heterogeneous and may vary as a function of age, task demands, and comorbidity. Accordingly, credible training effects require retention and transfer probes under standard, non-contingent display conditions, appropriate controls, and explicit developmental interpretation. Eye tracking is positioned as complementary functional evidence and as a platform for experimentally testable, mechanism-based interventions in school-age specific learning disorders. Full article

(This article belongs to the Special Issue Eye Movements in Reading and Related Difficulties)

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J. Eye Mov. Res., Volume 19, Issue 3 (June 2026) – 26 articles

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