Vision

13 pages, 1312 KB

Open AccessArticle

Comparing Visual Search Efficiency Across Different Facial Characteristics

by Navdeep Kaur, Isabella Hooge and Andrea Albonico

Vision 2025, 9(4), 88; https://doi.org/10.3390/vision9040088 - 15 Oct 2025

Face recognition is an important skill that helps people make social judgments by identifying both who a person is and other characteristics such as their expression, age, and ethnicity. Previous models of face processing, such as those proposed by Bruce and Young and [...] Read more.

Face recognition is an important skill that helps people make social judgments by identifying both who a person is and other characteristics such as their expression, age, and ethnicity. Previous models of face processing, such as those proposed by Bruce and Young and by Haxby and colleagues, suggest that identity and other facial features are processed through partly independent systems. This study aimed to compare the efficiency with which different facial characteristics are processed in a visual search task. Participants viewed arrays of two, four, or six faces and judged whether one face differed from the others. Four tasks were created, focusing separately on identity, expression, ethnicity, and gender. We found that search times were significantly longer when looking for identity and shorter when looking for ethnicity. Significant correlations were found among almost all tests in all outcome variables. Comparison of target-present and target-absent trials suggested that performance in none of the tests seems to follow a serial-search-terminating model. These results suggest that different facial characteristics share early processing but differentiate into independent recognition mechanisms at a later stage. Full article

(This article belongs to the Section Visual Neuroscience)

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11 pages, 923 KB

Open AccessArticle

Development of a Neural Network to Predict Optimal IOP Reduction in Glaucoma Management

by Raheem Remtulla, Sidrat Rahman and Hady Saheb

Vision 2025, 9(4), 87; https://doi.org/10.3390/vision9040087 - 15 Oct 2025

Abstract

Glaucoma management relies on lowering intraocular pressure (IOP), but determining the target reduction at presentation is challenging, particularly in normal-tension glaucoma (NTG). We developed and internally validated a neural network regression model using retrospective clinical data from Qiu et al. (2015), including 270 [...] Read more.

Glaucoma management relies on lowering intraocular pressure (IOP), but determining the target reduction at presentation is challenging, particularly in normal-tension glaucoma (NTG). We developed and internally validated a neural network regression model using retrospective clinical data from Qiu et al. (2015), including 270 patients (118 with NTG). A single-layer artificial neural network with five nodes was trained in MATLAB R2024b using the Levenberg–Marquardt algorithm. Inputs included demographic, refractive, structural, and functional parameters, with IOP reduction as the output. Data were split into 65% training, 15% validation, and 20% testing, with training repeated 10 times. Model performance was strong and consistent (average RMSE: 1.90 ± 0.29 training, 2.18 ± 0.34 validation, 2.11 ± 0.30 testing; Pearson’s r: 0.92 ± 0.02, 0.88 ± 0.02, 0.88 ± 0.04). The best-performing model achieved RMSEs of 1.57, 2.90, and 1.77 with r values of 0.93, 0.91, and 0.93, respectively. Feature ablation revealed significant contributions from IOP, axial length, CCT, diagnosis, VCDR, spherical equivalent, mean deviation, and laterality. This study demonstrates that a simple neural network can reliably predict individualized IOP reduction targets, supporting personalized glaucoma management and improved outcomes. Full article

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12 pages, 507 KB

Open AccessArticle

Clinical Assessment of a Virtual Reality Perimeter Versus the Humphrey Field Analyzer: Comparative Reliability, Usability, and Prospective Applications

by Marco Zeppieri, Caterina Gagliano, Francesco Cappellani, Federico Visalli, Fabiana D’Esposito, Alessandro Avitabile, Roberta Amato, Alessandra Cuna and Francesco Pellegrini

Vision 2025, 9(4), 86; https://doi.org/10.3390/vision9040086 - 11 Oct 2025

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Abstract

Background: This study compared the performance of a Head-mounted Virtual Reality Perimeter (HVRP) with the Humphrey Field Analyzer (HFA), the standard in automated perimetry. The HFA is the established standard for automated perimetry but is constrained by lengthy testing, bulky equipment, and limited [...] Read more.

Background: This study compared the performance of a Head-mounted Virtual Reality Perimeter (HVRP) with the Humphrey Field Analyzer (HFA), the standard in automated perimetry. The HFA is the established standard for automated perimetry but is constrained by lengthy testing, bulky equipment, and limited patient comfort. Comparative data on newer head-mounted virtual reality perimeters are limited, leaving uncertainty about their clinical reliability and potential advantages. Aim: The aim was to evaluate parameters such as visual field outcomes, portability, patient comfort, eye tracking, and usability. Methods: Participants underwent testing with both devices, assessing metrics like mean deviation (MD), pattern standard deviation (PSD), and duration. Results: The HVRP demonstrated small but statistically significant differences in MD and PSD compared to the HFA, while maintaining a consistent trend across participants. MD values were slightly more negative for HFA than HVRP (average difference −0.60 dB, p = 0.0006), while pattern standard deviation was marginally higher with HFA (average difference 0.38 dB, p = 0.00018). Although statistically significant, these differences were small in magnitude and do not undermine the clinical utility or reproducibility of the device. Notably, HVRP showed markedly shorter testing times with HVRP (7.15 vs. 18.11 min, mean difference 10.96 min, p < 0.0001). Its lightweight, portable design allowed for bedside and home testing, enhancing accessibility for pediatric, geriatric, and mobility-impaired patients. Participants reported greater comfort due to the headset design, which eliminated the need for chin rests. The device also offers potential for AI integration and remote data analysis. Conclusions: The HVRP proved to be a reliable, user-friendly alternative to traditional perimetry. Its advantages in comfort, portability, and test efficiency support its use in both clinical settings and remote screening programs for visual field assessment. Its portability and user-friendly design support broader use in clinical practice and expand possibilities for bedside assessment, home monitoring, and remote screening, particularly in populations with limited access to conventional perimetry. Full article

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15 pages, 897 KB

Open AccessArticle

Comparative Assessment of Large Language Models in Optics and Refractive Surgery: Performance on Multiple-Choice Questions

by Leah Attal, Elad Shvartz, Alon Gorenshtein, Shirley Pincovich and Daniel Bahir

Vision 2025, 9(4), 85; https://doi.org/10.3390/vision9040085 - 9 Oct 2025

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Abstract

This study aimed to evaluate the performance of seven advanced AI Large Language Models (LLMs)—ChatGPT 4o, ChatGPT O3 Mini, ChatGPT O1, DeepSeek V3, DeepSeek R1, Gemini 2.0 Flash, and Grok-3—in answering multiple-choice questions (MCQs) in optics and refractive surgery, to assess their role [...] Read more.

This study aimed to evaluate the performance of seven advanced AI Large Language Models (LLMs)—ChatGPT 4o, ChatGPT O3 Mini, ChatGPT O1, DeepSeek V3, DeepSeek R1, Gemini 2.0 Flash, and Grok-3—in answering multiple-choice questions (MCQs) in optics and refractive surgery, to assess their role in medical education for residents. The AI models were tested using 134 publicly available MCQs from national ophthalmology certification exams, categorized by the need to perform calculations, the relevant subspecialty, and the use of images. Accuracy was analyzed and compared statistically. ChatGPT O1 achieved the highest overall accuracy (83.5%), excelling in complex optical calculations (84.1%) and optics questions (82.4%). DeepSeek V3 displayed superior accuracy in refractive surgery-related questions (89.7%), followed by ChatGPT O3 Mini (88.4%). ChatGPT O3 Mini significantly outperformed others in image analysis, with 88.2% accuracy. Moreover, ChatGPT O1 demonstrated comparable accuracy rates for both calculated and non-calculated questions (84.1% vs. 83.3%). This is in stark contrast to other models, which exhibited significant discrepancies in accuracy for calculated and non-calculated questions. The findings highlight the ability of LLMs to achieve high accuracy in ophthalmology MCQs, particularly in complex optical calculations and visual items. These results suggest potential applications in exam preparation and medical training contexts, while underscoring the need for future studies designed to directly evaluate their role and impact in medical education. The findings highlight the significant potential of AI models in ophthalmology education, particularly in performing complex optical calculations and visual stem questions. Future studies should utilize larger, multilingual datasets to confirm and extend these preliminary findings. Full article

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14 pages, 1203 KB

Open AccessArticle

Myopia Prediction Using Machine Learning: An External Validation Study

by Rajat S. Chandra, Bole Ying, Jianyong Wang, Hongguang Cui, Guishuang Ying and Julius T. Oatts

Vision 2025, 9(4), 84; https://doi.org/10.3390/vision9040084 - 9 Oct 2025

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Abstract

We previously developed machine learning (ML) models for predicting cycloplegic spherical equivalent refraction (SER) and myopia using non-cycloplegic data and following a standardized protocol (cycloplegia with 0.5% tropicamide and biometry using NIDEK A-scan), but the models’ performance may not be generalizable to other [...] Read more.

We previously developed machine learning (ML) models for predicting cycloplegic spherical equivalent refraction (SER) and myopia using non-cycloplegic data and following a standardized protocol (cycloplegia with 0.5% tropicamide and biometry using NIDEK A-scan), but the models’ performance may not be generalizable to other settings. This study evaluated the performance of ML models in an independent cohort using a different cycloplegic agent and biometer. Chinese students (N = 614) aged 8–13 years underwent autorefraction before and after cycloplegia with 0.5% tropicamide (n = 505) or 1% cyclopentolate (n = 109). Biometric measures were obtained using an IOLMaster 700 (n = 207) or Optical Biometer SW-9000 (n = 407). ML models were evaluated using R², mean absolute error (MAE), sensitivity, specificity, and area under the ROC curve (AUC). The XGBoost model predicted cycloplegic SER very well (R² = 0.95, MAE (SD) = 0.32 (0.30) D). Both ML models predicted myopia well (random forest: AUC 0.99, sensitivity 93.7%, specificity 96.4%; XGBoost: sensitivity 90.1%, specificity 96.8%) and accurately predicted the myopia rate (observed 62.9%; random forest: 60.6%; XGBoost: 58.8%) despite heterogeneous cycloplegia and biometry factors. In this independent cohort of students, XGBoost and random forest performed very well for predicting cycloplegic SER and myopia status using non-cycloplegic data. This external validation study demonstrated that ML may provide a useful tool for estimating cycloplegic SER and myopia prevalence with heterogeneous clinical parameters, and study in additional populations is warranted. Full article

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17 pages, 1050 KB

Open AccessArticle

Oculomotor Training Improves Reading and Associated Cognitive Functions in Children with Learning Difficulties: A Pilot Study

by Alessio Facchin, Silvio Maffioletti, Marta Maffioletti, Gabriele Esposito, Marta Bonetti, Luisa Girelli and Roberta Daini

Vision 2025, 9(4), 83; https://doi.org/10.3390/vision9040083 - 7 Oct 2025

Viewed by 668

Abstract

In the first years of schooling, inefficient eye movements can impair the development of reading skills. Nonetheless, the improvement of these abilities has been little investigated in children. This pilot study aimed to verify the effectiveness of Office Based Oculomotor Training (OBOT) in [...] Read more.

In the first years of schooling, inefficient eye movements can impair the development of reading skills. Nonetheless, the improvement of these abilities has been little investigated in children. This pilot study aimed to verify the effectiveness of Office Based Oculomotor Training (OBOT) in enhancing reading skills in ‘poor’ readers. Twenty-one children (aged 7–12 years) underwent an assessment of reading, visual, and perceptual abilities before and after a training of oculomotor skills (i.e., execution of saccadic movements with symbol charts in various modes and types; 14 participants) or a simple reading exercise (7 participants). The overall duration of the training was six weeks. The results showed a specific improvement, in the group subjected to oculomotor training only, not only in oculomotor abilities but also in reading, visuo-perceptual skills, and the ability to resolve crowding. These primary results suggest that the improvement of oculomotor abilities can lead to an indirect increase in reading in developmental age. Full article

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9 pages, 201 KB

Open AccessArticle

Ocular Manifestations in Pediatric Traumatic Brain Injury Admitted to the ICU: A Prospective Analysis

by Amer Jaradat, Rami Al-Dwairi, Adam Abdallah, Atef F. Hulliel, Rawhi Alshaykh, Mahmood Al Nuaimi, Ala’ Al Barbarawi, Seren Al Beiruti and Abdelwahab Aleshawi

Vision 2025, 9(4), 82; https://doi.org/10.3390/vision9040082 - 4 Oct 2025

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Abstract

Background: Traumatic Brain Injury (TBI) in children is a major cause of morbidity and mortality worldwide. Ocular manifestations are common but often overlooked, despite their potential to cause long-term visual impairment. This study aimed to evaluate the prevalence and characteristics of ocular findings [...] Read more.

Background: Traumatic Brain Injury (TBI) in children is a major cause of morbidity and mortality worldwide. Ocular manifestations are common but often overlooked, despite their potential to cause long-term visual impairment. This study aimed to evaluate the prevalence and characteristics of ocular findings in pediatric TBI patients admitted to the intensive care unit (ICU). Method: We prospectively reviewed records of pediatric patients (≤16 years) with TBI admitted to the Neurosurgery ICU at King Abdullah University Hospital (January 2022–December 2024). TBI was defined using U.S. CDC criteria and confirmed by clinical and radiological findings. Ocular manifestations were identified from ophthalmology consultations, neurosurgical notes, and bedside examinations. Demographics, injury details, and clinical outcomes were recorded. Statistical analyses included Chi-square, Fisher’s exact, and Mann–Whitney U tests, with significance set at p ≤ 0.05. Results: Thirty-eight patients (median age: 8 years; 55.3% male) were included. Ocular findings were present in 20 patients (52.6%). These patients were significantly older (median age 10 vs. 6 years, p = 0.007) and had lower admission GCS scores (11 vs. 14, p = 0.016). Male predominance was higher in the ocular group (75.0% vs. 33.3%, p = 0.030). Ocular findings were significantly associated with surgical intervention (60.0% vs. 22.2%, p = 0.025), orbital fractures (40.0% vs. 5.6%, p = 0.021), basal skull fracture signs (p = 0.036), and extraocular muscle limitation (p = 0.048). On multivariable analysis, orbital fracture remained the only independent predictor of ocular findings (aOR 2.22, 95% CI 1.17–3.57, p = 0.02). Conclusion: Over half of pediatric ICU TBI patients demonstrated ocular manifestations, closely linked to greater injury severity and craniofacial trauma. Routine, comprehensive ophthalmological evaluation should be integrated into the multidisciplinary management of severe pediatric TBI to optimize visual and functional outcomes. Full article

17 pages, 1767 KB

Open AccessArticle

Too Bright to Focus? Influence of Brightness Illusions and Ambient Light Levels on the Dynamics of Ocular Accommodation

by Antonio Rodán, Angélica Fernández-López, Jesús Vera, Pedro R. Montoro, Beatriz Redondo and Antonio Prieto

Vision 2025, 9(4), 81; https://doi.org/10.3390/vision9040081 - 30 Sep 2025

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Abstract

Can brightness illusions modulate ocular accommodation? Previous studies have shown that brightness illusions can influence pupil size as if caused by actual luminance increases. However, their effects on other ocular responses—such as accommodative or focusing dynamics—remain largely unexplored. This study investigates the influence [...] Read more.

Can brightness illusions modulate ocular accommodation? Previous studies have shown that brightness illusions can influence pupil size as if caused by actual luminance increases. However, their effects on other ocular responses—such as accommodative or focusing dynamics—remain largely unexplored. This study investigates the influence of brightness illusions, under two ambient lighting conditions, on accommodative and pupillary dynamics (physiological responses), and on perceived brightness and visual comfort (subjective responses). Thirty-two young adults with healthy vision viewed four stimulus types (blue bright and non-bright, yellow bright and non-bright) under low- and high-contrast ambient lighting while ocular responses were recorded using a WAM-5500 open-field autorefractor. Brightness and comfort were rated after each session. The results showed that high ambient contrast (mesopic) and brightness illusions increased accommodative variability, while yellow stimuli elicited a greater lag under photopic condition. Pupil size decreased only under mesopic lighting. Perceived brightness was enhanced by brightness illusions and blue color, whereas visual comfort decreased for bright illusions, especially under low light. These findings suggest that ambient lighting and visual stimulus properties modulate both physiological and subjective responses, highlighting the need for dynamic accommodative assessment and visually ergonomic display design to reduce visual fatigue during digital device use. Full article

(This article belongs to the Special Issue Effects of Optical and Behavioral Factors on the Ocular Accommodation Response)

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14 pages, 428 KB

Open AccessSystematic Review

Evaluating the Clinical Validity of Commercially Available Virtual Reality Headsets for Visual Field Testing: A Systematic Review

by Jesús Vera, Alan N. Glazier, Mark T. Dunbar, Douglas Ripkin and Masoud Nafey

Vision 2025, 9(4), 80; https://doi.org/10.3390/vision9040080 - 24 Sep 2025

Viewed by 1043

Abstract

Virtual reality (VR) technology has emerged as a promising alternative to conventional perimetry for assessing visual fields. However, the clinical validity of commercially available VR-based perimetry devices remains uncertain due to variability in hardware, software, and testing protocols. A systematic review was conducted [...] Read more.

Virtual reality (VR) technology has emerged as a promising alternative to conventional perimetry for assessing visual fields. However, the clinical validity of commercially available VR-based perimetry devices remains uncertain due to variability in hardware, software, and testing protocols. A systematic review was conducted following PRISMA guidelines to evaluate the validity of VR-based perimetry compared to the Humphrey Field Analyzer (HFA). Literature searches were performed across MEDLINE, Embase, Scopus, and Web of Science. Studies were included if they assessed commercially available VR-based visual field devices in comparison to HFA and reported visual field outcomes. Devices were categorized by regulatory status (FDA, CE, or uncertified), and results were synthesized narratively. Nineteen studies were included. Devices such as Heru, Olleyes VisuALL, and the Advanced Vision Analyzer showed promising agreement with HFA metrics, especially in moderate to advanced glaucoma. However, variability in performance was observed depending on disease severity, population type, and device specifications. Limited dynamic range and lack of eye tracking were common limitations in lower-complexity devices. Pediatric validation and performance in early-stage disease were often suboptimal. Several VR-based perimetry systems demonstrate clinically acceptable validity compared to HFA, particularly in certain patient subgroups. However, broader validation, protocol standardization, and regulatory approval are essential for widespread clinical adoption. These devices may support more accessible visual field testing through telemedicine and decentralized care. Full article

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Vision, Volume 9, Issue 4 (December 2025) – 9 articles

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