EARLY DETECTION OF VISUAL FUNCTION CHANGES IN HEALTHY CHILDREN THROUGH THE ASSESSMENT OF VISUAL ACUITY USING THE VISUAL EVOKED POTENTIAL (VEP) METHOD

АННОТАЦИЯ

В данном исследовании проведено сравнение возрастных особенностей развития зрительного анализатора у здоровых детей и детей с миопией с использованием метода зрительных вызванных потенциалов (ВЗП). Всего было обследовано 50 испытуемых (100 глаз) с применением следующих методов: исследование остроты зрения, клиническая оценка рефракции и регистрация ВЗП. Участники были в возрасте от 7 до 17 лет и разделены на три возрастные группы, а также отдельную группу с диагностированной миопией. При монокулярной стимуляции и регистрации с ипсилатерального полушария средние латентные периоды компонентов N75, P100 и N145 составили (M±SE): Группа 1: 79,9 ± 0,9 мс, 112,8 ± 1,1 мс и 156,9 ± 1,9 мс, Группа 2: 78,9 ± 0,9 мс, 109,8 ± 1,2 мс и 155,3 ± 1,7 мс, Группа 3: 79,5 ± 0,6 мс, 108,1 ± 1,4 мс и 146,8 ± 1,8 мс. Были выявлены значимые различия в конфигурации, компонентах и характеристиках ВЗП при стимуляции центрального и периферического полей зрения. Статистически значимые различия обнаружены также в степени зрелости макулы (жёлтого пятна) между здоровыми испытуемыми и детьми с миопическими жалобами. Обнаруженные различия в развитии зрительного анализатора указывают на различные сроки созревания первичных сенсорных механизмов и когнитивных путей обработки информации у детей с нормальной остротой зрения по сравнению с детьми, страдающими миопией.

ABSTRACT

This study compares age-related characteristics of the visual analyzer in healthy children and those with myopia using visual evoked potentials (VEPs). A total of 50 subjects (100 eyes) were examined using the following methods: visual acuity testing, clinical refraction assessment, and VEP recording. The participants were between 7 and 17 years old and were divided into three age-based groups, with an additional group diagnosed with myopia. For monocular stimulation and ipsilateral hemisphere recording, the mean latencies of components N75, P100, and N145 were as follows (M±SE): Group 1: 79.9 ± 0.9 ms, 112.8 ± 1.1 ms, and 156.9 ± 1.9 ms

Group 2: 78.9 ± 0.9 ms, 109.8 ± 1.2 ms, and 155.3 ± 1.7 ms

Group 3: 79.5 ± 0.6 ms, 108.1 ± 1.4 ms, and 146.8 ± 1.8 ms

Significant differences were observed in the configuration, components, and characteristics of the VEP stimulation patterns during central and peripheral field stimulation. Statistically significant differences were identified in the degree of maturation of the macula lutea (yellow spot) between healthy subjects and those with myopic complaints. The detected differences in the development of the visual analyzer indicate distinct maturation timelines of primary sensory mechanisms and cognitive processing pathways in children with normal visual acuity compared to those with myopia. 

Keywords: Ciliary muscle; Macula lutea; Optic tract; Development of the visual system; Axial length; Visual Evoked Potentials (VEPs); Myopia; Visual cortex; Stimulation; Landolt rings.

Ключевые слова: Цилиарная мышца; Макула (жёлтое пятно); Зрительный тракт; Развитие зрительной системы; Аксиальная длина глаза; Зрительные вызванные потенциалы (ВЗП); Миопия; Зрительная кора; Стимуляция; Кольца Ландольта.

 Introduction. The study of developmental processes and characteristics of the visual system, particularly during childhood and adolescence, is currently considered one of the most important and relevant tasks of ophthalmic physiology. This relevance is largely associated with the substantial technogenic pressure exerted on the developing organism of children living in a highly digital and technology-driven environment.

Myopia (nearsightedness) is the most widespread refractive disorder globally. The progression of myopia can lead to irreversible structural changes in the eye and significant visual impairment. It is no secret that high and pathological myopia increasingly results in various forms of visual disability.

According to global visual health statistics reported by the World Health Organization, approximately 610 million people worldwide suffer from visual and visual-acuity–related disorders, including myopia. More than 91.5 million (over 15%) of this population consists of children and adolescents aged 7 to 16 years. In 2024–2025, ophthalmology specialists reported for the first time in history that severe pathological forms of myopia were approaching epidemic proportions, with the number of individuals affected by myopia rising rapidly across the world. It is projected that by the end of this century—around 2075–2085—nearly 3.2 billion people will be affected by myopia, representing more than half of the global population, with children and adolescents constituting the majority of this demographic [2].

In recent years, myopia has become the leading cause of visual impairment worldwide, accounting for 25.7% of all visual pathologies (39.8 million people). In Uzbekistan, pediatric ophthalmologists frequently encounter complaints associated with myopia: approximately 44% of children—about 2.3 million—have been registered with a diagnosis of myopia [3].

The etiology of myopia is multifactorial, with several key contributing factors, including: prolonged near work without proper visual hygiene or adequate lighting; excessive strain on the visual apparatus; hereditary predispositions associated with the anatomical and metabolic features of the eye; weakened scleral tissues associated with collagen abnormalities; insufficient accommodation mechanisms regulated by the ciliary muscle responsible for regulating lens curvature (refractive power); and continuous near-focus activities requiring prolonged visual effort [4].

Researchers traditionally focus their attention on the peripheral components of the visual analyzer, while the central mechanisms of vision—and their roles in visual impairment and the development of myopia—have been studied to a lesser extent. It is well established that Visual Evoked Potentials (VEPs) represent one of the most advanced and objective methods for evaluating visual function. Evoked potentials are an objective assessment of central nervous system activity based on recording the brain’s electrical responses to sensory stimulation.

At present, this method has become widely used both clinically and scientifically. It enables the acquisition of objective data without relying on the patient’s subjective responses, which is particularly crucial when examining children, individuals with visual impairments, or patients who demonstrate poor cooperation during ophthalmic testing. Visual Evoked Potentials (VEPs) allow for an objective assessment of the functional state of all structural components of the visual system—including the eyes, cranial nerves, and the occipital cortex of the cerebral hemispheres.

VEPs provide valuable information for the differential diagnosis of functional and morphological visual impairments, assessment of therapeutic efficacy, examination of the optic pathway (optic tract), and evaluation of cortical disorders resulting from trauma, stroke, tumors, or congenital anomalies. They also assist in identifying both specific and nonspecific pathologies affecting the visual afferent pathways.

Objective. To compare the age-related characteristics of visual analyzer development in healthy individuals and patients with myopia using the visual evoked potential (VEP) method.

Materials and Methods. A total of 50 subjects (100 eyes) were examined. Participants were primarily volunteers—school-aged children and adolescents from Namangan region—who were included based on parental informed consent. According to the examination results, the subjects were divided into the following groups:

Group 1: Subjects with normal visual acuity, aged 7–11 years (7 ± 4 years, M ± SD), 17 subjects (34 eyes).

Group 2: Subjects with normal visual acuity, aged 12–17 years (12 ± 5 years, M ± SD), 19 subjects (38 eyes).

Group 3: Subjects with mild to high myopia, aged 7–17 years (7 ± 10 years, M ± SD), 14 subjects (28 eyes).

We examined both functional and morpho-anatomical parameters of the visual system. The morpho-anatomical assessment included clinical refraction parameters (sphere, cylinder, axis—the geometric and optical axis of the eye). Functional parameters included visual acuity measured using Landolt rings (optotype for visual acuity testing), Snellen optotypes, and a large set of VEP amplitude–latency characteristics for evaluating corrected normal and uncorrected (myopic) visual acuity.

All examinations were performed in accordance with clinical practice standards and ethical principles. The study protocol was approved by all participating medical staff members. Written informed consent was obtained from the parents of all participants prior to enrollment.

Assessment of Visual Acuity.

In ophthalmology, visual acuity is determined using Snellen, Landolt, and Golovin–Sivtsev optotype charts. In tests employing letter optotypes, an eye is considered normal if it can distinguish the gap in the Landolt ring or letter width corresponding to one arc-minute or less [6]. For this study, visual acuity was assessed using Golovin–Sivtsev charts, Snellen symbols, and Landolt rings covering a visual acuity range of 0.7 to 3.0. Tests were performed separately for each eye—OD (Oculus Dexter), OS (Oculus Sinister)—and binocularly (OU, Oculus Uterque).

Assessment of Clinical Refraction.

Refraction—an evaluation of how light rays converge through the optical system (primarily the cornea and lens) to form an image on the retina—was measured using a Grand Seiko Co. GR-21 computerized autorefractometer with an accuracy of 0.25 D. After alignment, the device automatically measured clinical refraction across all meridians and provided the results in eyeglass prescription format (sph—spherical lens value in myopia/hyperopia; cyl—cylindrical lens power in astigmatism; axis—orientation of the cylindrical lens in the 0–180° range).

Visual Evoked Potentials (VEP).

VEPs were recorded using the Neuro-MEP computer system (Neurosoft, Ivanovo). Signals were obtained with surface electrodes and a pattern-reversal checkerboard visual stimulator at a recording window of 500 ms. Active electrodes were placed over the occipital region: O2 (right occipital) and O1 (left occipital). The reference electrode was placed at CZ (vertex), and ER electrodes were placed in the auricular region, with the ground electrode at Fpz.

Characteristics of the pattern-reversal checkerboard stimulus:

high-contrast black-and-white checks;

full-field monocular stimulation with central fixation;

pattern-reversal frequency of 1.5 Hz;

check sizes from 10 to 240 arc-minutes;

maximum luminance 70–80%;

testing conducted in a dark room.

Check sizes were selected according to the clinical goal. Small checks (10 arc-minutes) were used for assessing central visual mechanisms, as these signals are highly sensitive to defocus and reductions in visual acuity. Large checks (250 arc-minutes) were used to stimulate peripheral mechanisms, as these VEP responses are less sensitive to defocus and visual acuity decline.

VEP recordings were obtained separately for each eye (OD, OS) and binocularly (OU). All tests were conducted with optimal refractive correction. VEP results were analyzed as averaged waveforms, focusing on the amplitude and peak latency of conventional components: N75, P100, N145, and P200.

Statistical Analysis. Data processing was performed using the Statistica 8.0 software package (StatSoft). Initial data analysis included evaluation of statistical parameters and the distribution pattern of each variable. Comparisons between groups were conducted using parametric tests (Student’s t-test, Fisher’s F-test) [7, 8]. Data were presented as mean (M), minimum (Min), maximum (Max), standard deviation (SD), and standard error (SE).

Dynamic changes in the analyzed parameters were evaluated using analysis of variance (ANOVA), which assesses the reliability, magnitude, and nature of the influence of one or more controlled factors on the outcome variable [9].

“Controlled factors” refer to variables that the researcher can manipulate or at least observe (e.g., distance, time). These factors differ in their “gradations”—the levels or manifestations of the variable. All other variables that may affect the outcome but are not controlled during the experiment or observation are considered random.

Results. In the first stage of the study, differences in VEP responses during stimulation of the central (10 arc-minutes) and peripheral (240 arc-minutes) visual fields were examined. General group data are presented in Figure B. Compared to peripheral VEP responses, stimulation of the central visual field produced longer latencies in the early components (N75 and P100) and substantially larger amplitudes in the late components (N145 and P200). These findings indicate slower response times and more complex cortical processing mechanisms associated with central visual-field stimulation.

In the context of our study, the data obtained at this stage partially demonstrate the relationship between age- and pathology-related (nosological) factors and the development and functioning of different aspects of vision.

Age-related characteristics of visual acuity in normal healthy vision.The results of the differences identified between age groups are presented in the table.

LCOU – central visual-field stimulation, recording from the O1 electrode (left occipital region).

RCOU – central visual-field stimulation, recording from the O2 electrode (right occipital region).

LPOU – peripheral visual-field stimulation, recording from the O1 electrode (left occipital region).

RPOU – peripheral visual-field stimulation, recording from the O2 electrode (right occipital region).Note: O1 and O2 denote occipital electrode positions according to the international 10–20 EEG system.

A–B–Б graphs: Pattern-reversal visual evoked potentials under binocular stimulation in response to alternating (reversing) checkerboard patterns:

A — in ophthalmologically healthy children;

B — in adult participants;

Б — in patients with myopia.

Table 1.

Primary Statistical Estimates Across Different Age Groups (Mean, Minimum and Maximum Values, Standard Deviation).

Note: CIp-N75 — macular, ipsilateral lead, N75 latency;

CIp-P100 — macular, ipsilateral lead, P100 latency;

CIp-N145 — macular, ipsilateral lead, N145 latency;

CCon-N75 — macular, contralateral lead, N75 latency;

CCon-P100 — macular, contralateral lead, P100 latency;

CCon-N145 — macular, contralateral lead, N145 latency;

FFIp-N75 — paramacular, ipsilateral lead, N75 latency;

FFIp-P100 — paramacular, ipsilateral lead, P100 latency;

FFIp-N145 — paramacular, ipsilateral lead, N145 latency;

FFCon-N75 — paramacular, contralateral lead, N75 latency;

FFCon-P100 — paramacular, contralateral lead, P100 latency;

FFCon-N145 — paramacular, contralateral lead, N145 latency.

In children, the immaturity of the structures responsible for visual perception is reflected in the higher amplitudes and the reduced complexity of the response components (Figure A). This is particularly characteristic of central VEPs, which are marked by an emphasis on early components (P50, N75, and P100) associated with the direct arrival of sensory input to the cortex, along with a flattening—or even absence—of later components (N145 and P200) that reflect integrative and higher-order cortical processing.

Age-related changes in peripheral VEPs are less pronounced, which indicates the relatively early maturation of peripheral visual mechanisms that do not impose high cognitive demands. When comparing the groups of subjects with myopia (Figure C) and those with normal vision (see Figure B), only minor differences were observed in the responses of the peripheral visual fields; these were primarily expressed as an increase in peak latency, most notably in the P100, N145, and P200 components. In contrast, responses from the central visual field showed a marked reduction in the amplitudes of all components (N75, P100, N145, and P200), accompanied by a shift of their temporal characteristics toward longer latencies. Of particular interest is the observation that the response configuration in children aged 7–11 years shows a strong resemblance to the cortical response patterns of both healthy and myopic subjects (see Figures A and B). These intergroup differences appear to be highly stable and cannot be eliminated by optical correction. This effect is most likely related to the inefficiency or immaturity of sensory integration mechanisms in children and adolescents with myopia.

Latency intervals of VEP responses in subjects with myopia and normal vision. For the comparative analysis of VEP parameters in normal and myopic subjects, the 1st and 2nd age groups with normal vision were combined to obtain an age-matched sample. As a result, the mean age of the combined group of children and adolescents with normal visual acuity was 10 ± 1 years (7–17 years, M ± SE). The group of children and adolescents with myopia also had a mean age of 10 ± 1 years (7–17 years, M ± SE). The age difference between the groups was statistically insignificant (p = 0.35).

In myopia, compared to normal values, a statistically significant decrease in N75 latency was observed across both macular and broader stimulation fields (p = 0.019–0.044). For the P100 response, the pattern was opposite: shorter latencies were noted in individuals with normal vision, although these differences did not reach statistical significance.

In myopia, N145 latency was greater under macular stimulation (p = 0.017). Under paramacular stimulation, N145 latency values were approximately equal between groups.

Finally, we developed an interpretation suggesting that the age-related differences identified between groups are consistent with the hypothesis that various VEP components originate from distinct levels of the visual system. According to this hypothesis, the earliest recorded responses predominantly reflect subcortical activity along the visual pathway. Postsynaptic activity in layers III and IV of the visual cortex is manifested in the P100 response.

The absence of differences in the early VEP components across age groups likely reflects the similarity of functional activity within the subcortical structures of the visual system. By the time the third examined group (7–17 years) reaches late adolescence, all major adaptations of the visual pathway—including synaptic stabilization and the establishment of the final neuronal population size in the visual cortex and pre-cortical regions—are largely complete. Considering this, differences in the maturity of the primary visual cortex between younger children (7–11 years) and adolescents can be expected. This distinction is most clearly reflected in the results of macular stimulation.

It is plausible that accumulating visual experience and increased precision in the visual system’s responses to structured stimuli lead to the formation of the shortest N145 latencies within the older age group [5]. In our study, responses to high-spatial-frequency stimuli (checker size: 10 arc-minutes) were expected to reflect parvocellular transmission to the visual cortex, whereas low-spatial-frequency stimulation (250 arc-minutes) involved magnocellular information processing. It appears that after the age of 7, the development of magno- and parvocellular transmission systems at the prestriate level does not undergo major changes. A comparative analysis of N75 latency across age groups — which showed no statistically significant differences — supports this assumption.

However, the parvocellular pathway, which largely contributes to the P100 response and reflects neuronal activity within the primary visual cortex, demonstrated age-dependent shortening of latency, indicating that this cortical zone may continue to develop beyond the age of 17 [5]. At the same time, the absence of differences in magnocellular-driven responses — which are rapid and selective for motion and coarse patterns — suggests that the generators of P100 within the primary visual cortex reach maturity earlier.

Finally, differences in N145 latencies observed between age groups during activation of both magno- and parvocellular pathways likely reflect the prolonged maturation of associative visual cortical areas involved in higher-order visual processing. Previous studies indicate that the formation of associative regions of the visual cortex does not conclude at 6–7 years of age but continues well beyond this period. In our view, age-dependent changes in the development and functioning of associative cortical areas depend less on the specific input channel (magno- or parvocellular) and more on the progressive maturation of cortical integration processes themselves.

According to our findings, myopia is associated with compromised transmission of high-quality signals from the retina to the primary sensory and motor visual cortices. This is supported by statistically significant differences (p = 0.019 and p = 0.044) in N75 latency between normal and myopic groups under macular and paramacular stimulation. Based on the P100 and N145 responses, compensatory mechanisms at the level of projection and associative zones of the visual cortex appear to be insufficiently activated in myopia. Consequently, this leads to delayed processing of signals generated by blurred retinal images. Analyzing a focused visual image requires the engagement of a larger number of intracortical and intercortical connections. However, low-spatial-frequency stimuli impose lower processing demands compared to high-spatial-frequency components, which require more time for analysis (p = 0.017).

These findings may indicate that visual information-processing systems in the brains of individuals with myopia exhibit insufficient functional optimization. It can be hypothesized that the maturity of central visual mechanisms plays a crucial role in the development and progression of myopia.

Conclusion. The individual components of pattern-VEP responses across different age groups reflect varying degrees of maturation within the subcortical and cortical zones of the visual system. In early childhood, the developmental level of subcortical structures corresponds to that observed in older groups; however, this cannot be said for the primary projection areas and associative regions of the visual cortex. After approximately 25 years of age, the processes of neural impulse transmission along the visual pathway reach full maturity, indicating the functional optimization of central cortical systems.

At the level of the parvocellular system—responsible for transmitting and processing fine spatial details and high-spatial-frequency visual stimuli—adult-like optical maturity is achieved between 12 and 17 years of age. In contrast, the magnocellular system reaches full and stable maturation much earlier, typically by 6–7 years of age.

In myopia, compared to normal vision, the prestriate stage—before signals reach the striate cortex—exhibits relatively efficient signal conduction; however, at later stages, involving projection and associative areas of the visual cortex, the processes of signal analysis appear to be diminished. The differences identified in this study suggest that primary sensory mechanisms and higher-order cognitive processing mechanisms may reach functional maturity at different developmental times in both healthy individuals and those with myopia.

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