The Area Under the Waveform as an Alternative Measure of the Photopic Negative Response

The Area Under the Waveform as an Alternative Measure of the Photopic Negative Response | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Area Under the Waveform as an Alternative Measure of the Photopic Negative Response Radouil Tzekov, Jan Kremers, Sara Safari This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7327743/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Mar, 2026 Read the published version in Documenta Ophthalmologica → Version 1 posted 9 You are reading this latest preprint version Abstract Purpose: To explore how the photopic negative response (PhNR), measured as an area defined by the ERG waveform can be used as complementary or an alternative measure to the traditionally measured PhNR amplitude. Methods: A retrospective chart review and data analysis of light-adapted 3.0 ERG records in normal subjects patients aged 18 and older undergoing routine ERG testing was conducted. A new measure was analyzed: area defined by the PhNR curve. It was obtained in two ways: as an area under the ERG waveform (AUW) and an area above the ERG waveform (AAW) with starting points defined by the b-wave peak. A linear regression was conducted between PhNR1 amplitude (trough before i-wave), PhNR2 amplitude (trough after i-wave), PhNR AUW, and PhNR AAW. Furthermore, a prediction analysis based on AUW/AAW was conducted where the strongest correlated measures were used to predict the PhNR2 amplitude. Results: The ERG recordings of 70 patients/135 eyes (52F/18M,average age: 49.2 ± 15.3 years) and six healthy subjects (1F/5M, age between 22 and 58) were included in this study. 26 patients had well-defined PhNR2 troughs and were used for prediction analysis. There was good correlation between PhNR1 and PhNR2 amplitudes (r² 0.9755-0.9759 when amplitude was measured from the b-wave peak and 0.7265-0.6413, when amplitude was measured from baseline). The best predictors for PhNR2 amplitude were areas of 35 ms duration: AAW starting 30 ms after b-wave peak and AUW starting at 35 ms after the peak, when amplitude was measured from b-wave peak or baseline, respectively. Similar results were obtained by conducting similar prediction analysis on a small number of healthy volunteers. Conclusions: Determining and using AAW/AUW for PhNR2 prediction could be a valuable method in cases where the PhNR2 peak is not well defined. eye retina electroretinography oscillatory potentials photopic negative response ERG PhNR Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1 Introduction The full-field ERG is a composite recording of the bioelectrical activity of the retina. The most studied components of the full-field flash ERG are the a- and b-waves. The a-wave is traditionally measured from the baseline to the trough of the wave while the b-wave is traditionally measured from the trough of the a-wave to its peak. An additional ERG component are the oscillatory potentials which are small rhythmic wavelets superimposed on the ascending portion of the b-wave [1, 2] The photopic negative response (PhNR) of the light-adapted full-field ERG is less well studied. It is a slow negative-going wave following the b-wave peak [3]. The PhNR has been attributed to spiking activity of retinal ganglion cells (RGC); therefore, its clinical significance has been recognized in glaucoma in addition to other ocular pathologies [4, 5]. An extended protocol for PhNR recording in clinical settings was published by ISCEV in 2018 [6]. The PhNR amplitude is measured from b-wave peak, before and after the i-wave, as PhNR1(fP) and PhNR2(fP) respectively or from the baseline as PhNR1(fB) and PhNR2(fB). Confident determination of the PhNR is difficult due to various artifacts that can occur at the trough of the PhNR. These include the photomyoclonic reflex, blinking, and facial muscle activity [7]. Given the difficult determination of PhNR measures in some patients, in this work we propose an alternative measure of PhNR involving the area under the ERG waveform. The starting points for calculation of the area under the waveform are the peak of the photopic b-wave and various time points thereafter and with varying time differences between starting and end points. The traditional way of measuring the area under the curve involves determining the area constrained by a curve and a horizontal line which in the context of ERG is equivalent to the isoelectric baseline. When the signal crosses the baseline, the area is split into parts with positive and negative responses. This is the traditional way to evaluate the area under the curve which will be referred to as area under the waveform (AUW). We explored this method in conjunction with an alternative approach where the area is determined by the shape of the waveform relative to the peak of the b-wave referred to as the area above the waveform (AAW). 2 Methods 2.1 Subject Characteristics 2.1.1 USF patients A retrospective chart review and data analysis of patients aged 18 and older undergoing routine ERG testing from October 2018 to October 2021 at USF Eye Institute (Tampa, FL) was conducted. Exclusion criteria included a clinical diagnosis or suspicion of glaucoma, age under 18 years, and poor-quality ERG recordings. Specifically, ERG traces were excluded if the averaged signal was based on fewer than five individual runs or if the average b-wave amplitude was less than 10 µV. Additional exclusion was applied to traces exhibiting visible high-frequency noise or other artifacts. A “quality run” was defined as a single ERG sweep free of significant noise or artifacts and showing a clear b-wave response. The study was approved by the Institutional Review Board of the University of South Florida and was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments. 2.1.2 Normal Subjects An additional analysis was conducted on normal, healthy volunteers to further investigate the validity of our main analyses. This cohort was composed of 6 participants (5M/1F, between 22-58 years of age). The full-field ERG response was recorded as part of a larger series in the right eye only at the University Hospital Erlangen and the results were previously published with a different type of analysis on different ERG measures [8]. 2.2 ERG Recording Conditions 2.2.1 USF Patient Population Full field ERG was recorded binocularly using UTAS SunBurst (LKC Technologies, Gaithersburg, MD) with fiber electrodes as active and Ag/AgCl single-use skin electrodes on the lower eyelids as reference. The UTAS SunBurst system recorded the ERG using the following parameters: 0.3 to 3,000 Hz bandpass; 3750 Hz sampling rate, and 512 samples over a 136.27ms period per run. LA3 was recorded according to ISCEV standard using a ~2.5 cd·s/m² white flash on a 30 cd/m² white background after ten minutes of light adaptation[9, 10]. 2.2.2 Normal Subjects Full-field ERGs were recorded using the Retiport Ganzfeld Q450 system (Roland Consult, Germany). Only the responses to full-field stimuli obtained under white flash on a white background (“WoW”, corresponding to ISCEV LA 3.0 ERG conditions) were used in this current analysis. More detailed information regarding the recording is provided in the original source [8]. All ERG measurements and correlations applied to the patient population from USF were also applied to this normal subject population. 2.3 ERG measurements A-wave and b-wave amplitudes were measured in the classical way from the isoelectrical baseline to the trough and from the trough to the most prominent peak, respectively. PhNR amplitude was measured in four different ways: a) as a trough before the i-wave peak (PhNR1 as in Ortiz et al [7]), from the b-wave peak (PhNR1(fP)) and from the isoelectric baseline (PhNR1 (fB)), and b) as a trough after the i-wave peak (PhNR2 as in Ortiz et al [7]), from the b-wave peak (PhNR2(fP)) and from the isoelectric baseline (PhNR2 (fB)). 2.4 Area Defined by the PhNR Waveform As the proposed measure is intended to robustly complement or, in some cases, potentially substitute the standard PhNR measurement, we decided to evaluate areas defined by the PhNR waveform. Areas are integrations over time and thus expected to be less variable than maxima or minima. The starting point was at the peak of the b-wave and extended it to different time points after that. Two different approaches were used: (a) the area which is calculated under the waveform in the traditional way (geometric area subtended within the waveform), including both positive and negative deflections, with positive and negative areas automatically calculated and then the absolute values added together in statistical software (e.g. in GraphPad Prism); (b) the area which is calculated above the waveform relative to the peak of the b-wave (area subtended above the waveform, assuming only a negative deflection). These approaches are referred to in the text as Area Under the Waveform (AUW) and Area Above the Waveform (AAW) respectively and are illustrated in Figure 1 . In the context of both methods, the extent of the area under the waveform in time was set using two main approaches. First, we calculated the areas for time spans with different starting and endpoints that were all determined by the b-wave. The starting points varied between 0 and 30 ms after the b-wave in steps of 5 ms. The endpoints were located between 5 and 45 ms after the starting points (again in 5 ms steps) but was never located more than 45 ms after the b-wave resulting in 42 time intervals for AUW/AAW calculations ( Figure 2; Supplementary figure 1 ). Second, we used variable time windows starting at a b-wave peak and ending at the peaks of the two physiological components located between the b-wave peak and the PhNR2 trough: the PhNR1 trough and the i-wave peak. The AAW/AUW values were compared using linear regression models to the amplitude of traditionally measured ERG amplitude parameters: a-wave, b-wave, PhNR1, and PhNR2. 2.5 PhNR2 Prediction Analysis A prediction analysis was conducted on ERG datasets in which the PhNR2 waveform was clearly defined in both USF patients and normal subjects. The methodology followed the general structure of Ortiz et al. [7], but instead of using PhNR1 amplitude as the primary predictor, we evaluated waveform-defined area measures (AUW and AAW) as potential predictors of PhNR2 amplitude. A key innovation in our approach was the use of the Percent Prediction Error Range (PPER) as the primary performance metric. PPER quantifies the spread of prediction error by summing the maximum positive percent error and the absolute value of the maximum negative percent error within a prediction group. In this framework, a lower PPER indicates better predictive performance , as it reflects tighter agreement between predicted and actual values. Unlike the R² value, which reflects the proportion of variance explained, PPER captures the practical bounds of predictive accuracy and can be more informative in clinical contexts where over- or under-estimation has asymmetric consequences. While both R² and PPER were computed on the same dataset and might be expected to show an inverse relationship—since higher explained variance typically coincides with smaller prediction errors—they capture fundamentally different aspects of model performance. R² reflects the strength of the correlation, whereas PPER quantifies the extremity of predictive deviations, which can be disproportionately influenced by outliers or clinically relevant edge cases. Thus, the two metrics offer complementary, but not necessarily inversely correlated, insights. Importantly, this analysis is exploratory and descriptive, as the absence of an independent test set precludes a fully generalizable predictive model. Nonetheless, PPER-based ranking allows identification of the most stable predictors within this dataset, which can guide future prospective validation. 2.6 Statistical analysis Normality of the data distribution was checked with Shapiro-Wilk test. As it turned out that some of the data were not normally distributed, median values and ranges or percentiles were reported. A linear regression was conducted between selected ERG components: a-wave amplitude, b-wave amplitude, PhNR1 amplitude, PhNR2 amplitude, PhNR AUW, and PhNR AAW. GraphPad Prism 10 (GraphPad Software LLC, San Diego, CA) was used for statistical analysis and graphing. 3 Results 3.1 USF Patient Population Clinical Characteristics The ERG recordings of 77 patients/154 eyes were initially evaluated. With application of inclusion and exclusion criteria, the ERG recordings of 70 patients/135 eyes (52F/18M, average age: 49.2 ± 15.3 years) were evaluated. Based on the 10 th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10)[11], the primary clinical diagnoses of the patients were distributed as such: Other retinal disorders (H35) – 19 patients Blindness and low vision (H54) – 14 patients Visual disturbances (H53) – 25 patients Chorioretinal inflammation and other disorders of the choroid (H30/H31) – 4 patients Other categories ­– 8 patients, including other disorders of the optic nerve and visual pathways (H47, n = 3), optic neuritis (H46, n = 3), disorders of the vitreous body (H43, n = 1), and retinal vascular occlusions (H34, n = 1). 3.2 PhNR as an Identifiable ERG Component After careful visual inspection of all ERG traces, an unambiguous PhNR1 trough was identified in 63 right eyes and 61 left eyes (90.0%, 87.1%). In contrast, an unambiguous PhNR2 trough was identified in only 25 right eyes and 29 left eyes (37.3%, 43.3%) . Both PhNR1 and PhNR2 were identifiable in 25 right eyes and 24 left eyes (OS). 3.3 Correlation between PhNR1 and PhNR2 amplitudes and peak time To evaluate the consistency of PhNR measures across clinical and normative datasets, we performed linear regression analyses comparing PhNR1 and PhNR2 amplitudes in both USF patients and normal healthy volunteers. In the USF cohort, the correlation between PhNR1(fP) and PhNR2(fP) amplitudes was strong (R² = 0.9755 for right eyes, 0.9759 for left eyes). For comparison, data from healthy individuals recorded at the University Hospital Erlangen—where only right eye recordings were obtained—showed a similarly high correlation (R² = 0.9772). In contrast, correlations based on baseline-referenced amplitudes [PhNR1(fB) vs. PhNR2(fB)] were somewhat weaker in USF patients (R² = 0.7265 right, 0.6413 left) and lower still in the Erlangen data (R² = 0.4560). Despite these variations in R², the slopes of the regression lines were highly consistent. Statistical comparisons of slopes between the right eyes of USF patients and Erlangen subjects showed no significant differences for either fP (p = 0.7259) or fB (p = 0.2970), indicating that the relationship between PhNR1 and PhNR2 amplitudes is preserved across populations and recording setups. This supports the broader applicability of PhNR1 as a predictive surrogate when PhNR2 is not clearly measurable. When the peak times of PhNR1 and PhNR2 were compared, the R 2 values for patients were higher compared to R 2 values for normal healthy volunteers (NHVs): RE = 0.4996; LE = 0.5100 vs. RE (NHVs) = 0.2863 (Figure 3). However, as with amplitudes, the slopes of the regression lines for right eyes in patients vs. normal healthy volunteers were very similar (0.4788 vs. 0.4625) and an F-test showed no significant difference between the slopes (p = 0.9461). Therefore, it can be summarized that despite the differences in recording methods and populations, the correlation between PhNR1 and PhNR2 amplitudes and peak times showed practically identical relationships. The lower R² values for the NHVs can probably be attributed to the lower number of participants. 3.4 Area defined by the waveform as an additional method of predicting PhNR2 amplitude R 2 comparison . We compared the coefficients of determination (R²) between the two variable-time intervals (PhNR1 and i-wave), the 42 fixed-time intervals, and the amplitudes of the a-wave, b-wave, PhNR2(fB), and PhNR2(fP) in both USF patients and normal healthy volunteers. The full distribution of R² values across all comparisons is shown in Supplementary Figures 2–5 . Overall, R² distribution patterns were consistent between the two populations. Notably, R² values were generally higher for AUWs than for AAWs when predicting PhNR2(fB), whereas AAWs showed higher R² values when predicting PhNR2(fP). This outcome is expected, as AAWs are calculated relative to the b-wave peak and are therefore directly influenced by b-wave amplitude—potentially confounding their interpretation as indicators of ganglion cell activity. In contrast, AUWs are measured relative to the isoelectric baseline and are less dependent on earlier waveform components. Since PhNR2(fB) is considered more clinically relevant due to its stronger association with retinal ganglion cell activity, AUW may offer a more robust and interpretable predictive metric in clinical settings. A summary of the R² values for variable-time areas and the strongest fixed-time predictors is shown in Supplementary Table 1 , which also demonstrates that fixed-time areas yielded higher correlations with PhNR2 amplitudes than variable-time intervals (i.e. with endpoints of the time windows in which the areas were calculated defined by the PhNR1 or the i-wave). Prediction analysis. As a further step, analysis of predicting the PhNR2 amplitude was conducted using both area measures. Focusing on the AAW method, the PPER distribution was similar between patients and healthy volunteers. The best predictor area was always a fixed-time interval with the endpoint at 20 ms or more after the b-wave peak, as further shown in Figure 4. The PPER distribution based on the AUW analysis is shown in Figure 5 . As with the AAW, the PPER distribution showed similarities between USF patients and normal healthy volunteers, the best PPER range occurring with a beginning at the b-wave peak and with a time span of 15 to 40 ms. However, there was an exception to that with the prediction of PhNR2(fB) amplitude in NHVs, where the best PPER was found to be with a beginning at 20 ms after b-wave and a range of 20ms ( Figure 5 ). A graphical presentation of the relationship between PhNR2 and the percentage error for both approaches (AAW and AUW) is shown in Supplementary Figures 6-9 . 3.4.1 Are AAW/AUWs better predictors for PhNR2 amplitude compared with PhNR1 amplitude? Next, we summarized and examined the PPER values of PhNR1 amplitude vs. the best (smallest) PPER values for either AAW (values marked by arrows in Figure 4) or AUW (values marked by arrows in Figure 5) in predicting the PhNR2(fB) or PhNR2(fP) amplitude. The differences in PPERs can be quite large as can be further seen in Table 1 . The best PPER were always associated with the use of fixed-time areas: AUW for PhNR2 (fB) (which is, as mentioned above, the clinically relevant metric) and AAW for PhNR2 (fP) (values in bold font in Table 1 ). Table 1. Summary of the percentage prediction error ranges of PhNR1 amplitude, PhNR1 AAW/AUW, i-wave AAW/AUW vs. the best performing predictors from fixed time AAW or AUW measurements . For AAW/AUW measures, the characteristics of the best performing predictors are provided in parentheses below the error ranges: time from the b-wave peak outlined first, followed by duration of the AAW/AUW. For fixed-time areas under the waveform, the best parameter is shown in parentheses below the PPER values with the first number indicating time from b-wave peak and the second number indicating time span of the area. 4 Discussion 4.1 Introduction The present work could be considered to be a continuation of efforts to improve and refine the confidence and accuracy in determination of PhNR component parameters which was initially explored in Ortiz et al. [7]. This would be especially important in cases where the PhNR2 trough is not well defined and the commonly used evaluation of the PhNR amplitude based on a well-defined trough in the ERG waveform is inaccurate, or, in some cases, impossible, due to the presence of various artifacts. In the dataset obtained from USF patients in this study, this turned out to be the majority of cases, as a clearly identifiable PhNR2 trough was present in 37%. On the other hand, it has been established that the PhNR2 (particularly the PhNR2(fB)) is a marker for spiking activity of the retinal ganglion cells [3]. It therefore would be helpful to have a surrogate marker in the case the PhNR2 cannot be measured and predictions of PhNR2 based on alternative measures of PhNR becomes very important. Our data show that such prediction is possible and can be relatively accurate which is discussed in detail below. 4.2 Correlation between PhNR1 and PhNR2 Measures A correlation between PhNR1 and PhNR2 measures has been infrequently addressed in the literature. In our previous study [7], we demonstrated a strong correlation between PhNR1(fP) and PhNR2(fP) amplitudes. The current study confirms this finding in a different cohort of patients and a small group of healthy volunteers. In addition, we observed a consistent correlation between the peak times of PhNR1 and PhNR2, further reinforcing the physiological relationship between these two components. Since peak time is an intrinsic temporal feature of the waveform, it remains unaffected by the choice of amplitude reference (baseline vs. b-wave peak). Overall, the results from Ortiz et al. [7] and the present study support the conclusion that, under standard light-adapted 3.0 ERG conditions, PhNR1 amplitude and timing can serve as reliable surrogates for PhNR2—particularly when the latter is obscured by noise or artifacts 4.3 Measure of PhNR Amplitude In the current work, we decided to explore an additional measure of PhNR amplitude, in the form of either area under the waveform (AUW) or area above the waveform (AAW). These types of areas measure are variations of area under the curve (AUC) measurement, a method that, to the best of our knowledge, has not been used to evaluate the PhNR process in either pre-clinical or clinical settings [12]. In general, AUC measurements have rarely been used in visual electrophysiology for determining the response area and its characteristics [13, 14] and no correlation was ever performed with other measures. The purpose of introducing this measure was purely in the context of correlating it with other amplitude measures and for prediction of PhNR2 amplitude analysis. Within this context, it was demonstrated that both AUW and AAW measures could be used as relatively good predictors of PhNR2 amplitude, surpassing the predictive power of PhNR1 amplitude. Whether these measures could have additional usefulness in terms of any diagnostic value would be the subject of future research. 4.4 Study Limitations This study has several limitations that should be acknowledged. Small sample size , especially among healthy volunteers. The overall sample size in this study was limited, with a particularly small number of healthy control participants. This imbalance may affect the generalizability of the findings, especially when comparing pathological responses to normal visual electrophysiological patterns. Future studies with larger and more balanced cohorts are necessary to validate these results and strengthen statistical power. Limited emphasis on temporal prediction. The current analysis did not incorporate mechanisms for predicting the precise timing of electrophysiological responses. While modeling temporal dynamics remains a valuable direction for future work, it is important to note that, for clinical applications such as glaucoma diagnostics, response amplitudes are typically of greater relevance. This is especially true given the high variability in the timing of components like the PhNR2, which reduces the clinical utility of precise temporal prediction in such contexts. Use of fixed 5 ms increments in response prediction. In this study, the identification of the optimal response predictor was conducted using fixed 5-millisecond increments. While this provided a reasonable and practical resolution, it may have introduced minor limitations in pinpointing the exact peak response timing. Although it is unclear whether more granular or continuous methods would lead to substantial improvements, future work may explore such approaches to assess their potential benefits. 5 Conclusions This study extends previous work on improving the accuracy of PhNR measurements in cases where traditional trough-based evaluation is unreliable. A strong correlation between PhNR1 and PhNR2 amplitude and timing was confirmed, suggesting that PhNR1 can serve as a useful surrogate for PhNR2 under standard recording conditions. Novel area-based measures— AUW and AAW —were introduced and shown to be effective predictors of PhNR2 amplitude, with AUW emerging as the more robust option . Unlike AAW, which is inherently influenced by variations in b-wave amplitude, AUW provides a more targeted assessment of ganglion cell activity and is thus less susceptible to unrelated signal components. While rarely used in visual electrophysiology, these AUC-type metrics show promise and warrant further exploration. Study limitations include a relatively small sample size, the absence of precise timing prediction, and the use of fixed 5 ms increments, which may have modestly constrained temporal resolution. Future research will aim to address these issues through larger cohorts and refined modeling approaches. Declarations Financial Support: The authors received no financial support for the research, authorship, and/or publication of this article. Conflict of Interest: The authors declare that they have no conflict of interest. Compliance with Ethical Standards: No funding was received for this research. All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. For this type of study formal consent is not required. The study was approved by the local institutional review board. Author Contributions: RT conceptualized the study and supervised data analysis. JK contributed to methodology development and statistical interpretation. SS and RT collected and processed clinical data. All authors contributed to manuscript writing and approved the final version. Data Availability: The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request. References Cobb, W.A. and H.B. Morton, A new component of the human electroretinogram. The Journal of Physiology, 1953: p. 36-37. Yonemura, D., K. Tsuzuki, and T. Aoki, Clinical importance of the oscillatory potential in the human ERG. Acta Ophthalmol Suppl, 1962. Suppl 70 : p. 115-23. Viswanathan, S., et al., The photopic negative response of the macaque electroretinogram: reduction by experimental glaucoma. Invest Ophthalmol Vis Sci, 1999. 40 (6): p. 1124-36. Cvenkel, B., M. Sustar, and D. Perovsek, Ganglion cell loss in early glaucoma, as assessed by photopic negative response, pattern electroretinogram, and spectral-domain optical coherence tomography. Doc Ophthalmol, 2017. 135 (1): p. 17-28. Moss, H.E., J.C. Park, and J.J. McAnany, The Photopic Negative Response in Idiopathic Intracranial Hypertension. Invest Ophthalmol Vis Sci, 2015. 56 (6): p. 3709-14. Frishman, L., et al., ISCEV extended protocol for the photopic negative response (PhNR) of the full-field electroretinogram. Doc Ophthalmol, 2018. 136 (3): p. 207-211. Ortiz, G., et al., The photopic negative response of the Light-adapted 3.0 ERG in clinical settings. Doc Ophthalmol, 2020. 140 (2): p. 115-128. Nittmann, M.G., et al., Relationship between stimulus size and different components of the electroretinogram (ERG) elicited by flashed stimuli. Doc Ophthalmol, 2021. 142 (2): p. 213-231. McCulloch, D.L., et al., ISCEV Standard for full-field clinical electroretinography (2015 update). Doc Ophthalmol, 2015. 130 (1): p. 1-12. Robson, A.G., et al., ISCEV Standard for full-field clinical electroretinography (2022 update). Doc Ophthalmol, 2022. 144 (3): p. 165-177. Organization, W.H. ICD-10 Browser . 2019 2019; 10:[Available from: https://www.who.int/standards/classifications/classification-of-diseases. Joachimsthaler, A., et al., Changes in glycinergic neurotransmission alter mammalian retinal information processing. Front Mol Neurosci, 2025. 18 : p. 1564870. Chapman, R.M. and A.B. Lall, Electroretinogram characteristics and the spectral mechanisms of the median ocellus and the lateral eye in Limulus polyphemus. J Gen Physiol, 1967. 50 (9): p. 2267-87. Jagle, H., J. Heine, and A. Kurtenbach, L:M-cone ratio estimates of the outer and inner retina and its impact on sex differences in ERG amplitudes. Doc Ophthalmol, 2006. 113 (2): p. 105-13. Additional Declarations No competing interests reported. Supplementary Files SupplInfoAUC2025FINAL.pdf Cite Share Download PDF Status: Published Journal Publication published 01 Mar, 2026 Read the published version in Documenta Ophthalmologica → Version 1 posted Editorial decision: Revision requested 06 Jan, 2026 Reviews received at journal 31 Dec, 2025 Reviewers agreed at journal 09 Nov, 2025 Reviews received at journal 28 Sep, 2025 Reviewers agreed at journal 08 Sep, 2025 Reviewers invited by journal 29 Aug, 2025 Editor assigned by journal 09 Aug, 2025 Submission checks completed at journal 09 Aug, 2025 First submitted to journal 08 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7327743","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":507631938,"identity":"edf2c5d0-e380-43f2-8b86-7051f52cfc06","order_by":0,"name":"Radouil Tzekov","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtklEQVRIiWNgGAWjYJACxgYGBjkg9YCBgY0Y9WwQLcYMDMwGpGlJbCBai/n89ocPZ1QcTt9w/jADw4eyw4S1yBxjSDbccOZw7oYbyQyMM84RoUWCjeGY5MO2NKAW/gPMvG1EaWFs/wnUkm4AdBjzX+K0MLMxbmyzSTA4kMzAzEicljRmyRlnbAxnAv1ysOdcOhFamI8//NhTISHPd/4w44MfZdaEtaCAAySqHwWjYBSMglGACwAAugI5FjWkFjMAAAAASUVORK5CYII=","orcid":"","institution":"University of South Florida","correspondingAuthor":true,"prefix":"","firstName":"Radouil","middleName":"","lastName":"Tzekov","suffix":""},{"id":507631939,"identity":"4eb09d10-4a89-45ef-ab21-dee0363effe9","order_by":1,"name":"Jan Kremers","email":"","orcid":"","institution":"University Hospital Erlangen","correspondingAuthor":false,"prefix":"","firstName":"Jan","middleName":"","lastName":"Kremers","suffix":""},{"id":507631940,"identity":"2562c8d9-545e-4d00-8205-9da945210842","order_by":2,"name":"Sara Safari","email":"","orcid":"","institution":"University of South Florida","correspondingAuthor":false,"prefix":"","firstName":"Sara","middleName":"","lastName":"Safari","suffix":""}],"badges":[],"createdAt":"2025-08-08 13:38:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7327743/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7327743/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10633-026-10088-9","type":"published","date":"2026-03-01T15:59:02+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90544110,"identity":"d4dd2f96-0f8a-45a5-9521-2e83b6fbf982","added_by":"auto","created_at":"2025-09-04 00:15:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":158757,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExample of an LA 3.0 ERG response with an illustration of the area defined by the PhNR waveform used in the current study.\u003c/strong\u003e (A) Area Under the Waveform (AUW) (B) Area Above the Waveform (AAW). The area was constrained between the photopic b-wave peak and a point on the ERG trace at 15 ms after it. The area itself is indicated with red diagonal lines.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7327743/v1/9a54e360b492bff18ec9306b.png"},{"id":90544108,"identity":"ca2d3f60-0a57-4c4a-9e90-211ee9f5cdf7","added_by":"auto","created_at":"2025-09-04 00:15:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":38328,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic representation of time position and duration of areas under the waveform with a start point at or after the b-wave peak\u003c/strong\u003e. Two variable-time areas (determined by the b-wave peak and the PhNR1/ i-wave peak) and 42 fixed-time areas are shown. The areas extending into the time span, including 35 to 45 ms after the b-wave peak are indicated with lighter color. Tabp – time after b-wave peak. For more details, see the main text.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7327743/v1/da7ac4d13291c7f62f213589.png"},{"id":90544116,"identity":"37ee847f-ee56-4e99-a774-09a91a5240bd","added_by":"auto","created_at":"2025-09-04 00:15:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":114400,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelations between PhNR1 and PhNR2 amplitudes and peak times.\u003c/strong\u003e (A), (B): comparison between amplitudes of PhNR1(fP) and PhNR2(fP). (C), (D): comparison between amplitudes of PhNR1(fB) and PhNR2(fB). (E), (F): comparison between peak time of PhNR1 and PhNR2. (A), (C), (E): data from USF patients; (B), (D), (F): data from normal healthy volunteers.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7327743/v1/c7d8cb056dac3fe7cef23fdf.png"},{"id":90544118,"identity":"7f06c3a3-4eb5-4ffa-bdb8-dd8282381691","added_by":"auto","created_at":"2025-09-04 00:15:39","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":227400,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSummary of the percentage prediction error range of the regression analyses between AAWs and PhNR2 measures\u003c/strong\u003e. (A) Percent prediction error range for AAW in USF patients for PhNR2 (fB) (B) Percent prediction error range for AAW in USF patients for PhNR2 (fP); (C) Percent prediction error range for AAW in NHVs for PhNR2 (fB) (D) Percent prediction error range for AAW in NHVs for PhNR2 (fP). Cells outlined by arrows indicate the time windows in which the areas predicted the PhNR2 best. The percentage prediction error range values are (from left to right): 111.4%, 9.2%, 53.9%, 2.2%.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7327743/v1/0b567cd6b79795fd1319cc6d.png"},{"id":90544121,"identity":"a61bc7eb-a45d-4fa9-9f34-0a801553d412","added_by":"auto","created_at":"2025-09-04 00:15:39","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":228746,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSummary of percentage prediction error range of the regression analyses between AUWs. \u003c/strong\u003e(A) Percent prediction error range for AUW in USF patients for PhNR2 (fB) (B) Percent prediction error range for AUW in USF patients for PhNR2 (fP); (C) Percent prediction error range for AUW in NHVs for PhNR2 (fB) (D) Percent prediction error range for AUW in NHVs for PhNR2 (fP). Cells outlined by arrows indicate the best (narrowest) range for each condition. The percentage prediction error range values are (from left to right): 38.3%, 57.1%, 9.5%, 35.9%.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7327743/v1/32ecd523abea09ccc6e93edd.png"},{"id":103765815,"identity":"574d7a85-d3c0-4948-bc2c-fc0dc108f277","added_by":"auto","created_at":"2026-03-02 16:09:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1663219,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7327743/v1/7068230b-40ba-4bff-9a3c-ce238fc1836c.pdf"},{"id":90544109,"identity":"a07f67a3-f284-4bac-9aeb-227bdf860e41","added_by":"auto","created_at":"2025-09-04 00:15:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":664590,"visible":true,"origin":"","legend":"","description":"","filename":"SupplInfoAUC2025FINAL.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7327743/v1/25d919879959b5ef0a31a53d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Area Under the Waveform as an Alternative Measure of the Photopic Negative Response","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eThe full-field ERG is a composite recording of the bioelectrical activity of the retina. The most studied components of the full-field flash ERG are the a- and b-waves. The a-wave is traditionally measured from the baseline to the trough of the wave while the b-wave is traditionally measured from the trough of the a-wave to its peak. An additional ERG component are the oscillatory potentials which are small rhythmic wavelets superimposed on the ascending portion of the b-wave [1, 2]\u003c/p\u003e\n\u003cp\u003eThe photopic negative response (PhNR) of the light-adapted full-field ERG is less well studied. It is a slow negative-going wave following the b-wave peak [3]. The PhNR has been attributed to spiking activity of retinal ganglion cells (RGC); therefore, its clinical significance has been recognized in glaucoma in addition to other ocular pathologies [4, 5]. An extended protocol for PhNR recording in clinical settings was published by ISCEV in 2018 [6]. The PhNR amplitude is measured from b-wave peak, before and after the i-wave, as PhNR1(fP) and PhNR2(fP) respectively or from the baseline as PhNR1(fB) and PhNR2(fB). Confident determination of the PhNR is difficult due to various artifacts that can occur at the trough of the PhNR. These include the photomyoclonic reflex, blinking, and facial muscle activity [7].\u003c/p\u003e\n\u003cp\u003eGiven the difficult determination of PhNR measures in some patients, in this work we propose an alternative measure of PhNR involving the area under the ERG waveform. The starting points for calculation of the area under the waveform are the peak of the photopic b-wave and various time points thereafter and with varying time differences between starting and end points. The traditional way of measuring the area under the curve involves determining the area constrained by a curve and a horizontal line which in the context of ERG is equivalent to the isoelectric baseline. When the signal crosses the baseline, the area is split into parts with positive and negative responses. This is the traditional way to evaluate the area under the curve which will be referred to as area under the waveform (AUW). We explored this method in conjunction with an alternative approach where the area is determined by the shape of the waveform relative to the peak of the b-wave referred to as the area above the waveform (AAW).\u0026nbsp;\u003c/p\u003e"},{"header":"2\tMethods","content":"\u003ch2\u003e2.1 Subject Characteristics\u003c/h2\u003e\n\u003ch3\u003e2.1.1 USF patients\u003c/h3\u003e\n\u003cp\u003eA retrospective chart review and data analysis of patients aged 18 and older undergoing routine ERG testing from October 2018 to October 2021 at USF Eye Institute (Tampa, FL) was conducted. Exclusion criteria included a clinical diagnosis or suspicion of glaucoma, age under 18 years, and poor-quality ERG recordings. Specifically, ERG traces were excluded if the averaged signal was based on fewer than five individual runs or if the average b-wave amplitude was less than 10 \u0026micro;V. Additional exclusion was applied to traces exhibiting visible high-frequency noise or other artifacts. A \u0026ldquo;quality run\u0026rdquo; was defined as a single ERG sweep free of significant noise or artifacts and showing a clear b-wave response. The study was approved by the Institutional Review Board of the University of South Florida and was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments. \u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e2.1.2 Normal Subjects\u003c/h3\u003e\n\u003cp\u003eAn additional analysis was conducted on normal, healthy volunteers to further investigate the validity of our main analyses. This cohort was composed of 6 participants (5M/1F, between 22-58 years of age). The full-field ERG response was recorded as part of a larger series in the right eye only at the University Hospital Erlangen and the results were previously published with a different type of analysis on different ERG measures [8].\u003c/p\u003e\n\u003ch2\u003e2.2 ERG Recording Conditions \u0026nbsp;\u003c/h2\u003e\n\u003ch3\u003e2.2.1 USF Patient Population\u003c/h3\u003e\n\u003cp\u003eFull field ERG was recorded binocularly using UTAS SunBurst (LKC Technologies, Gaithersburg, MD) with fiber electrodes as active and Ag/AgCl single-use skin electrodes on the lower eyelids as reference. The UTAS SunBurst system recorded the ERG using the following parameters: 0.3 to 3,000 Hz bandpass; 3750 Hz sampling rate, and 512 samples over a 136.27ms period per run. LA3 was recorded according to ISCEV standard using a ~2.5 cd\u0026middot;s/m\u0026sup2; white flash on a 30 cd/m\u0026sup2; white background after ten minutes of light adaptation[9, 10].\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e2.2.2 Normal Subjects\u003c/h3\u003e\n\u003cp\u003eFull-field ERGs were recorded using the Retiport Ganzfeld Q450 system (Roland Consult, Germany). Only the responses to full-field stimuli obtained under white flash on a white background (\u0026ldquo;WoW\u0026rdquo;, corresponding to ISCEV LA 3.0 ERG conditions) were used in this current analysis. More detailed information regarding the recording is provided in the original source [8]. All ERG measurements and correlations applied to the patient population from USF were also applied to this normal subject population.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e2.3 ERG measurements\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eA-wave and b-wave amplitudes were measured in the classical way from the isoelectrical baseline to the trough and from the trough to the most prominent peak, respectively. PhNR amplitude was measured in four different ways: a) as a trough before the i-wave peak (PhNR1 as in Ortiz et al [7]), from the b-wave peak (PhNR1(fP)) and from the isoelectric baseline (PhNR1 (fB)), and b) as a trough after the i-wave peak (PhNR2 as in Ortiz et al [7]), from the b-wave peak (PhNR2(fP)) and from the isoelectric baseline (PhNR2 (fB)). \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e2.4 Area Defined by the PhNR Waveform\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eAs the proposed measure is intended to robustly complement or, in some cases, potentially substitute the standard PhNR measurement, we decided to evaluate areas defined by the PhNR waveform. Areas are integrations over time and thus expected to be less variable than maxima or minima. The starting point was at the peak of the b-wave and extended it to different time points after that.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTwo different approaches were used:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(a) the area which is calculated under the waveform in the traditional way (geometric area subtended within the waveform), including both positive and negative deflections, with positive and negative areas automatically calculated and then the absolute values added together in statistical software (e.g. in GraphPad Prism);\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(b) the area which is calculated above the waveform relative to the peak of the b-wave (area subtended above the waveform, assuming only a negative deflection).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThese approaches are referred to in the text as Area Under the Waveform (AUW) and Area Above the Waveform (AAW) respectively and are illustrated in \u003cstrong\u003eFigure 1\u003c/strong\u003e. In the context of both methods, the extent of the area under the waveform in time was set using two main approaches.\u003c/p\u003e\n\u003cp\u003eFirst, we calculated the areas for time spans with different starting and endpoints that were all determined by the b-wave. The starting points varied between 0 and 30 ms after the b-wave in steps of 5 ms. The endpoints were located between 5 and 45 ms after the starting points (again in 5 ms steps) but was never located more than 45 ms after the b-wave resulting in 42 time intervals for\u003cu\u003e\u0026nbsp;\u003c/u\u003eAUW/AAW calculations (\u003cstrong\u003eFigure 2; Supplementary figure 1\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSecond, we used \u003cem\u003evariable\u0026nbsp;\u003c/em\u003etime\u003cem\u003e\u0026nbsp;\u003c/em\u003ewindows starting at a b-wave peak and ending at the peaks of the two physiological components located between the b-wave peak and the PhNR2 trough: the PhNR1 trough and the i-wave peak.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe AAW/AUW values were compared using linear regression models to the amplitude of traditionally measured ERG amplitude parameters: a-wave, b-wave, PhNR1, and PhNR2.\u003c/p\u003e\n\u003ch2\u003e2.5 PhNR2 Prediction Analysis\u003c/h2\u003e\n\u003cp\u003eA prediction analysis was conducted on ERG datasets in which the PhNR2 waveform was clearly defined in both USF patients and normal subjects. The methodology followed the general structure of Ortiz et al. [7], but instead of using PhNR1 amplitude as the primary predictor, we evaluated waveform-defined area measures (AUW and AAW) as potential predictors of PhNR2 amplitude. A key innovation in our approach was the use of the \u003cstrong\u003ePercent Prediction Error Range (PPER)\u003c/strong\u003e as the primary performance metric. PPER quantifies the spread of prediction error by summing the maximum positive percent error and the absolute value of the maximum negative percent error within a prediction group. In this framework, \u003cstrong\u003ea lower PPER indicates better predictive performance\u003c/strong\u003e, as it reflects tighter agreement between predicted and actual values. Unlike the R\u0026sup2; value, which reflects the proportion of variance explained, PPER captures the practical bounds of predictive accuracy and can be more informative in clinical contexts where over- or under-estimation has asymmetric consequences. While both R\u0026sup2; and PPER were computed on the same dataset and might be expected to show an inverse relationship\u0026mdash;since higher explained variance typically coincides with smaller prediction errors\u0026mdash;they capture fundamentally different aspects of model performance. R\u0026sup2; reflects the strength of the correlation, whereas PPER quantifies the extremity of predictive deviations, which can be disproportionately influenced by outliers or clinically relevant edge cases. Thus, the two metrics offer complementary, but not necessarily inversely correlated, insights. Importantly, this analysis is exploratory and descriptive, as the absence of an independent test set precludes a fully generalizable predictive model. Nonetheless, PPER-based ranking allows identification of the most stable predictors within this dataset, which can guide future prospective validation.\u003c/p\u003e\n\u003ch2\u003e2.6 Statistical analysis\u003c/h2\u003e\n\u003cp\u003eNormality of the data distribution was checked with Shapiro-Wilk test. As it turned out that some of the data were not normally distributed, median values and ranges or percentiles were reported. \u0026nbsp;A linear regression was conducted between selected ERG components: a-wave amplitude, b-wave amplitude, PhNR1 amplitude, PhNR2 amplitude, PhNR AUW, and PhNR AAW. GraphPad Prism 10 (GraphPad Software LLC, San Diego, CA) was used for statistical analysis and graphing.\u003c/p\u003e"},{"header":"3 Results","content":"\u003ch2\u003e3.1 USF Patient Population Clinical Characteristics\u003c/h2\u003e\n\u003cp\u003eThe ERG recordings of 77 patients/154 eyes were initially evaluated. With application of inclusion and exclusion criteria, the ERG recordings of 70 patients/135 eyes (52F/18M, average age: 49.2 \u0026plusmn; 15.3 years) were evaluated.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBased on the 10\u003csup\u003eth\u003c/sup\u003e revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10)[11], the primary clinical diagnoses of the patients were distributed as such:\u0026nbsp;\u003c/p\u003e\n\u003cul class=\"decimal_type\"\u003e\n \u003cli\u003eOther retinal disorders (H35) \u0026ndash; 19 patients\u003c/li\u003e\n \u003cli\u003eBlindness and low vision (H54) \u0026ndash; 14 patients\u003c/li\u003e\n \u003cli\u003eVisual disturbances (H53) \u0026ndash; 25 patients\u003c/li\u003e\n \u003cli\u003eChorioretinal inflammation and other disorders of the choroid (H30/H31) \u0026ndash; 4 patients\u003c/li\u003e\n\u003c/ul\u003e\n\u003cul\u003e\n \u003cli\u003eOther categories \u0026shy;\u0026ndash; 8 patients, including other disorders of the optic nerve and visual pathways (H47, n = 3), optic neuritis (H46, n = 3), disorders of the vitreous body (H43, n = 1), and retinal vascular occlusions (H34, n = 1).\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch2\u003e3.2 PhNR as an Identifiable ERG Component\u003c/h2\u003e\n\u003cp\u003eAfter careful visual inspection of all ERG traces, an unambiguous PhNR1 trough was identified in 63 right eyes and 61 left eyes (90.0%, 87.1%). In contrast, an unambiguous PhNR2 trough was identified in only 25 right eyes and 29 left eyes\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(37.3%, 43.3%)\u003cstrong\u003e.\u003c/strong\u003e Both PhNR1 and PhNR2 were identifiable in 25 right eyes and 24 left eyes (OS).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e3.3 Correlation between PhNR1 and PhNR2 amplitudes and peak time\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eTo evaluate the consistency of PhNR measures across clinical and normative datasets, we performed linear regression analyses comparing PhNR1 and PhNR2 amplitudes in both USF patients and normal healthy volunteers. In the USF cohort, the correlation between PhNR1(fP) and PhNR2(fP) amplitudes was strong (R\u0026sup2; = 0.9755 for right eyes, 0.9759 for left eyes). For comparison, data from healthy individuals recorded at the University Hospital Erlangen\u0026mdash;where only right eye recordings were obtained\u0026mdash;showed a similarly high correlation (R\u0026sup2; = 0.9772). In contrast, correlations based on baseline-referenced amplitudes [PhNR1(fB) vs. PhNR2(fB)] were somewhat weaker in USF patients (R\u0026sup2; = 0.7265 right, 0.6413 left) and lower still in the Erlangen data (R\u0026sup2; = 0.4560). Despite these variations in R\u0026sup2;, the slopes of the regression lines were highly consistent. Statistical comparisons of slopes between the right eyes of USF patients and Erlangen subjects showed no significant differences for either fP (p = 0.7259) or fB (p = 0.2970), indicating that the relationship between PhNR1 and PhNR2 amplitudes is preserved across populations and recording setups. This supports the broader applicability of PhNR1 as a predictive surrogate when PhNR2 is not clearly measurable. When the peak times of PhNR1 and PhNR2 were compared, the R\u003csup\u003e2\u003c/sup\u003e values for patients were higher compared to R\u003csup\u003e2\u003c/sup\u003e values for normal healthy volunteers (NHVs): RE = 0.4996; LE = 0.5100 vs. RE (NHVs) = 0.2863 (Figure 3). However, as with amplitudes, the slopes of the regression lines for right eyes in patients vs. normal healthy volunteers were very similar (0.4788 vs. 0.4625) and an F-test showed no significant difference between the slopes (p = 0.9461). \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTherefore, it can be summarized that despite the differences in recording methods and populations, the correlation between PhNR1 and PhNR2 amplitudes and peak times showed practically identical relationships. The lower R\u0026sup2; values for the NHVs can probably be attributed to the lower number of participants.\u003c/p\u003e\n\u003ch2\u003e3.4 Area defined by the waveform as an additional method of predicting PhNR2 amplitude\u003c/h2\u003e\n\u003cp\u003e\u003cu\u003eR\u003csup\u003e2\u003c/sup\u003e comparison\u003c/u\u003e. We compared the coefficients of determination (R\u0026sup2;) between the two variable-time intervals (PhNR1 and i-wave), the 42 fixed-time intervals, and the amplitudes of the a-wave, b-wave, PhNR2(fB), and PhNR2(fP) in both USF patients and normal healthy volunteers. The full distribution of R\u0026sup2; values across all comparisons is shown in \u003cstrong\u003eSupplementary Figures 2\u0026ndash;5\u003c/strong\u003e. Overall, R\u0026sup2; distribution patterns were consistent between the two populations. Notably, R\u0026sup2; values were generally higher for AUWs than for AAWs when predicting PhNR2(fB), whereas AAWs showed higher R\u0026sup2; values when predicting PhNR2(fP). This outcome is expected, as AAWs are calculated relative to the b-wave peak and are therefore directly influenced by b-wave amplitude\u0026mdash;potentially confounding their interpretation as indicators of ganglion cell activity. In contrast, AUWs are measured relative to the isoelectric baseline and are less dependent on earlier waveform components. Since PhNR2(fB) is considered more clinically relevant due to its stronger association with retinal ganglion cell activity, AUW may offer a more robust and interpretable predictive metric in clinical settings. A summary of the R\u0026sup2; values for variable-time areas and the strongest fixed-time predictors is shown in \u003cstrong\u003eSupplementary Table 1\u003c/strong\u003e, which also demonstrates that fixed-time areas yielded higher correlations with PhNR2 amplitudes than variable-time intervals (i.e. with endpoints of the time windows in which the areas were calculated defined by the PhNR1 or the i-wave).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003ePrediction analysis.\u003c/u\u003e As a further step, analysis of predicting the PhNR2 amplitude was conducted using both area measures. Focusing on the AAW method, the PPER distribution was similar between patients and healthy volunteers. The best predictor area was always a fixed-time interval with the endpoint at 20 ms or more after the b-wave peak, as further shown in \u003cstrong\u003eFigure 4.\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe PPER distribution based on the AUW analysis is shown in \u003cstrong\u003eFigure 5\u003c/strong\u003e. As with the AAW, the PPER distribution showed similarities between USF patients and normal healthy volunteers, the best PPER range occurring with a beginning at the b-wave peak and with a time span of 15 to 40 ms. However, there was an exception to that with the prediction of PhNR2(fB) amplitude in NHVs, where the best PPER was found to be with a beginning at 20 ms after b-wave and a range of 20ms (\u003cstrong\u003eFigure 5\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA graphical presentation of the relationship between PhNR2 and the percentage error for both approaches (AAW and AUW) is shown in \u003cstrong\u003eSupplementary Figures 6-9\u003c/strong\u003e.\u003c/p\u003e\n\u003ch3\u003e3.4.1 Are AAW/AUWs better predictors for PhNR2 amplitude compared with PhNR1 amplitude?\u003c/h3\u003e\n\u003cp\u003eNext, we summarized and examined the PPER values of PhNR1 amplitude vs. the best (smallest) PPER values for either AAW (values marked by arrows in Figure 4) or AUW (values marked by arrows in Figure 5) in predicting the PhNR2(fB) or PhNR2(fP) amplitude. The differences in PPERs can be quite large as can be further seen in \u003cstrong\u003eTable 1\u003c/strong\u003e. The best PPER were always associated with the use of fixed-time areas: AUW for PhNR2 (fB) (which is, as mentioned above, the clinically relevant metric) and AAW for PhNR2 (fP) (values in bold font in \u003cstrong\u003eTable 1\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Summary of the percentage prediction error ranges of PhNR1 amplitude, PhNR1 AAW/AUW, i-wave AAW/AUW vs. the best performing predictors from fixed time AAW or AUW measurements\u003c/strong\u003e. For AAW/AUW measures, the characteristics of the best performing predictors are provided in parentheses below the error ranges: time from the b-wave peak outlined first, followed by duration of the AAW/AUW. For fixed-time areas under the waveform, the best parameter is shown in parentheses below the PPER values with the first number indicating time from b-wave peak and the second number indicating time span of the area.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cimg 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\" width=\"1018\" height=\"570\"\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003ch2\u003e4.1 Introduction\u003c/h2\u003e\n\u003cp\u003eThe present work could be considered to be a continuation of efforts to improve and refine the confidence and accuracy in determination of PhNR component parameters which was initially explored in Ortiz et al. [7]. This would be especially important in cases where the PhNR2 trough is not well defined and the commonly used evaluation of the PhNR amplitude based on a well-defined trough in the ERG waveform is inaccurate, or, in some cases, impossible, due to the presence of various artifacts. In the dataset obtained from USF patients in this study, this turned out to be the majority of cases, as a clearly identifiable PhNR2 trough was present in 37%. On the other hand, it has been established that the PhNR2 (particularly the PhNR2(fB)) is a marker for spiking activity of the retinal ganglion cells [3]. It therefore would be helpful to have a surrogate marker in the case the PhNR2 cannot be measured and predictions of PhNR2 based on alternative measures of PhNR becomes very important. Our data show that such prediction is possible and can be relatively accurate which is discussed in detail below.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e4.2 Correlation between PhNR1 and PhNR2 Measures\u003c/h2\u003e\n\u003cp\u003eA correlation between PhNR1 and PhNR2 measures has been infrequently addressed in the literature. In our previous study [7], we demonstrated a strong correlation between PhNR1(fP) and PhNR2(fP) amplitudes. The current study confirms this finding in a different cohort of patients and a small group of healthy volunteers. In addition, we observed a consistent correlation between the \u003cstrong\u003epeak times\u003c/strong\u003e of PhNR1 and PhNR2, further reinforcing the physiological relationship between these two components. Since peak time is an intrinsic temporal feature of the waveform, it remains unaffected by the choice of amplitude reference (baseline vs. b-wave peak). Overall, the results from Ortiz et al. [7] and the present study support the conclusion that, under standard light-adapted 3.0 ERG conditions, PhNR1 amplitude and timing can serve as reliable surrogates for PhNR2\u0026mdash;particularly when the latter is obscured by noise or artifacts\u003c/p\u003e\n\u003ch2\u003e4.3 Measure of PhNR Amplitude\u003c/h2\u003e\n\u003cp\u003eIn the current work, we decided to explore an additional measure of PhNR amplitude, in the form of either \u003cem\u003earea under the waveform\u003c/em\u003e (AUW) or \u003cem\u003earea above the waveform\u0026nbsp;\u003c/em\u003e(AAW). These types of areas measure are variations of area under the curve (AUC) measurement, a method that, to the best of our knowledge, has not been used to evaluate the PhNR process in either pre-clinical or clinical settings [12]. In general, AUC measurements have rarely been used in visual electrophysiology for determining the response area and its characteristics [13, 14] and no correlation was ever performed with other measures.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe purpose of introducing this measure was purely in the context of correlating it with other amplitude measures and for prediction of PhNR2 amplitude analysis. Within this context, it was demonstrated that both AUW and AAW measures could be used as relatively good predictors of PhNR2 amplitude, surpassing the predictive power of PhNR1 amplitude. Whether these measures could have additional usefulness in terms of any diagnostic value would be the subject of future research. \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e4.4 Study Limitations\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThis study has several limitations that should be acknowledged.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSmall sample size\u003c/em\u003e, especially among healthy volunteers. The overall sample size in this study was limited, with a particularly small number of healthy control participants. This imbalance may affect the generalizability of the findings, especially when comparing pathological responses to normal visual electrophysiological patterns. Future studies with larger and more balanced cohorts are necessary to validate these results and strengthen statistical power.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLimited emphasis on temporal prediction.\u003c/em\u003e The current analysis did not incorporate mechanisms for predicting the precise timing of electrophysiological responses. While modeling temporal dynamics remains a valuable direction for future work, it is important to note that, for clinical applications such as glaucoma diagnostics, response amplitudes are typically of greater relevance. This is especially true given the high variability in the timing of components like the PhNR2, which reduces the clinical utility of precise temporal prediction in such contexts.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eUse of fixed 5 ms increments in response prediction.\u003c/em\u003e In this study, the identification of the optimal response predictor was conducted using fixed 5-millisecond increments. While this provided a reasonable and practical resolution, it may have introduced minor limitations in pinpointing the exact peak response timing. Although it is unclear whether more granular or continuous methods would lead to substantial improvements, future work may explore such approaches to assess their potential benefits.\u003c/p\u003e"},{"header":"5 Conclusions","content":"\u003cp\u003eThis study extends previous work on improving the accuracy of PhNR measurements in cases where traditional trough-based evaluation is unreliable. A strong correlation between PhNR1 and PhNR2 amplitude and timing was confirmed, suggesting that PhNR1 can serve as a useful surrogate for PhNR2 under standard recording conditions.\u003c/p\u003e\u003cp\u003eNovel area-based measures\u0026mdash;\u003cb\u003eAUW\u003c/b\u003e and \u003cb\u003eAAW\u003c/b\u003e\u0026mdash;were introduced and shown to be effective predictors of PhNR2 amplitude, with \u003cb\u003eAUW emerging as the more robust option\u003c/b\u003e. Unlike AAW, which is inherently influenced by variations in b-wave amplitude, AUW provides a more targeted assessment of ganglion cell activity and is thus less susceptible to unrelated signal components. While rarely used in visual electrophysiology, these AUC-type metrics show promise and warrant further exploration.\u003c/p\u003e\u003cp\u003eStudy limitations include a relatively small sample size, the absence of precise timing prediction, and the use of fixed 5 ms increments, which may have modestly constrained temporal resolution. Future research will aim to address these issues through larger cohorts and refined modeling approaches.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eFinancial Support:\u003c/p\u003e\n\u003cp\u003eThe authors received no financial support for the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003eConflict of Interest:\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003eCompliance with Ethical Standards:\u003c/p\u003e\n\u003cp\u003eNo funding was received for this research. All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers\u0026rsquo; bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. For this type of study formal consent is not required. The study was approved by the local institutional review board.\u003c/p\u003e\n\u003cp\u003eAuthor Contributions:\u003c/p\u003e\n\u003cp\u003eRT conceptualized the study and supervised data analysis. JK contributed to methodology development and statistical interpretation. SS and RT collected and processed clinical data. All authors contributed to manuscript writing and approved the final version.\u003c/p\u003e\n\u003cp\u003eData Availability:\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCobb, W.A. and H.B. Morton, \u003cem\u003eA new component of the human electroretinogram.\u003c/em\u003e The Journal of Physiology, 1953: p. 36-37.\u003c/li\u003e\n\u003cli\u003eYonemura, D., K. Tsuzuki, and T. Aoki, \u003cem\u003eClinical importance of the oscillatory potential in the human ERG.\u003c/em\u003e Acta Ophthalmol Suppl, 1962. \u003cstrong\u003eSuppl 70\u003c/strong\u003e: p. 115-23.\u003c/li\u003e\n\u003cli\u003eViswanathan, S., et al., \u003cem\u003eThe photopic negative response of the macaque electroretinogram: reduction by experimental glaucoma.\u003c/em\u003e Invest Ophthalmol Vis Sci, 1999. \u003cstrong\u003e40\u003c/strong\u003e(6): p. 1124-36.\u003c/li\u003e\n\u003cli\u003eCvenkel, B., M. Sustar, and D. Perovsek, \u003cem\u003eGanglion cell loss in early glaucoma, as assessed by photopic negative response, pattern electroretinogram, and spectral-domain optical coherence tomography.\u003c/em\u003e Doc Ophthalmol, 2017. \u003cstrong\u003e135\u003c/strong\u003e(1): p. 17-28.\u003c/li\u003e\n\u003cli\u003eMoss, H.E., J.C. Park, and J.J. McAnany, \u003cem\u003eThe Photopic Negative Response in Idiopathic Intracranial Hypertension.\u003c/em\u003e Invest Ophthalmol Vis Sci, 2015. \u003cstrong\u003e56\u003c/strong\u003e(6): p. 3709-14.\u003c/li\u003e\n\u003cli\u003eFrishman, L., et al., \u003cem\u003eISCEV extended protocol for the photopic negative response (PhNR) of the full-field electroretinogram.\u003c/em\u003e Doc Ophthalmol, 2018. \u003cstrong\u003e136\u003c/strong\u003e(3): p. 207-211.\u003c/li\u003e\n\u003cli\u003eOrtiz, G., et al., \u003cem\u003eThe photopic negative response of the Light-adapted 3.0 ERG in clinical settings.\u003c/em\u003e Doc Ophthalmol, 2020. \u003cstrong\u003e140\u003c/strong\u003e(2): p. 115-128.\u003c/li\u003e\n\u003cli\u003eNittmann, M.G., et al., \u003cem\u003eRelationship between stimulus size and different components of the electroretinogram (ERG) elicited by flashed stimuli.\u003c/em\u003e Doc Ophthalmol, 2021. \u003cstrong\u003e142\u003c/strong\u003e(2): p. 213-231.\u003c/li\u003e\n\u003cli\u003eMcCulloch, D.L., et al., \u003cem\u003eISCEV Standard for full-field clinical electroretinography (2015 update).\u003c/em\u003e Doc Ophthalmol, 2015. \u003cstrong\u003e130\u003c/strong\u003e(1): p. 1-12.\u003c/li\u003e\n\u003cli\u003eRobson, A.G., et al., \u003cem\u003eISCEV Standard for full-field clinical electroretinography (2022 update).\u003c/em\u003e Doc Ophthalmol, 2022. \u003cstrong\u003e144\u003c/strong\u003e(3): p. 165-177.\u003c/li\u003e\n\u003cli\u003eOrganization, W.H. \u003cem\u003eICD-10 Browser\u003c/em\u003e. 2019 2019; 10:[Available from: https://www.who.int/standards/classifications/classification-of-diseases.\u003c/li\u003e\n\u003cli\u003eJoachimsthaler, A., et al., \u003cem\u003eChanges in glycinergic neurotransmission alter mammalian retinal information processing.\u003c/em\u003e Front Mol Neurosci, 2025. \u003cstrong\u003e18\u003c/strong\u003e: p. 1564870.\u003c/li\u003e\n\u003cli\u003eChapman, R.M. and A.B. Lall, \u003cem\u003eElectroretinogram characteristics and the spectral mechanisms of the median ocellus and the lateral eye in Limulus polyphemus.\u003c/em\u003e J Gen Physiol, 1967. \u003cstrong\u003e50\u003c/strong\u003e(9): p. 2267-87.\u003c/li\u003e\n\u003cli\u003eJagle, H., J. Heine, and A. Kurtenbach, \u003cem\u003eL:M-cone ratio estimates of the outer and inner retina and its impact on sex differences in ERG amplitudes.\u003c/em\u003e Doc Ophthalmol, 2006. \u003cstrong\u003e113\u003c/strong\u003e(2): p. 105-13.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":true,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"documenta-ophthalmologica","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"doop","sideBox":"Learn more about [Documenta Ophthalmologica](http://link.springer.com/journal/10633)","snPcode":"10633","submissionUrl":"https://submission.nature.com/new-submission/10633/3","title":"Documenta Ophthalmologica","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"eye, retina, electroretinography, oscillatory potentials, photopic negative response, ERG, PhNR","lastPublishedDoi":"10.21203/rs.3.rs-7327743/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7327743/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose: \u003c/strong\u003eTo explore how the photopic negative response (PhNR), measured as an area defined by the ERG waveform can be used as complementary or an alternative measure to the traditionally measured PhNR amplitude.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A retrospective chart review and data analysis of light-adapted 3.0 ERG records in normal subjects patients aged 18 and older undergoing routine ERG testing was conducted. A new measure was analyzed: area defined by the PhNR curve. It was obtained in two ways: as an area under the ERG waveform (AUW) and an area above the ERG waveform (AAW) with starting points defined by the b-wave peak. A linear regression was conducted between PhNR1 amplitude (trough before i-wave), PhNR2 amplitude (trough after i-wave), PhNR AUW, and PhNR AAW. Furthermore, a prediction analysis based on AUW/AAW was conducted where the strongest correlated measures were used to predict the PhNR2 amplitude.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe ERG recordings of 70 patients/135 eyes (52F/18M,average age: 49.2 ± 15.3 years) and six healthy subjects (1F/5M, age between 22 and 58) were included in this study. 26 patients had well-defined PhNR2 troughs and were used for prediction analysis. There was good correlation between PhNR1 and PhNR2 amplitudes (r² 0.9755-0.9759 when amplitude was measured from the b-wave peak and 0.7265-0.6413, when amplitude was measured from baseline). \u0026nbsp;The best predictors for PhNR2 amplitude were areas of 35 ms duration: AAW starting 30 ms after b-wave peak and AUW starting at 35 ms after the peak, when amplitude was measured from b-wave peak or baseline, respectively. Similar results were obtained by conducting similar prediction analysis on a small number of healthy volunteers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eDetermining\u003cstrong\u003e \u003c/strong\u003eand using AAW/AUW for PhNR2 prediction could be a valuable method in cases where the PhNR2 peak is not well defined.\u003c/p\u003e","manuscriptTitle":"The Area Under the Waveform as an Alternative Measure of the Photopic Negative Response","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-04 00:15:34","doi":"10.21203/rs.3.rs-7327743/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-06T15:29:59+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-31T08:21:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"58954676402800076787399084480650791594","date":"2025-11-09T21:38:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-28T16:54:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"216039876218034761754698679912883334757","date":"2025-09-08T18:53:50+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-29T21:22:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-09T10:03:55+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-09T10:02:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Documenta Ophthalmologica","date":"2025-08-08T13:23:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"documenta-ophthalmologica","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"doop","sideBox":"Learn more about [Documenta Ophthalmologica](http://link.springer.com/journal/10633)","snPcode":"10633","submissionUrl":"https://submission.nature.com/new-submission/10633/3","title":"Documenta Ophthalmologica","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"ffdab527-6be3-4a19-9571-9795a832c3fc","owner":[],"postedDate":"September 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-02T16:06:00+00:00","versionOfRecord":{"articleIdentity":"rs-7327743","link":"https://doi.org/10.1007/s10633-026-10088-9","journal":{"identity":"documenta-ophthalmologica","isVorOnly":false,"title":"Documenta Ophthalmologica"},"publishedOn":"2026-03-01 15:59:02","publishedOnDateReadable":"March 1st, 2026"},"versionCreatedAt":"2025-09-04 00:15:34","video":"","vorDoi":"10.1007/s10633-026-10088-9","vorDoiUrl":"https://doi.org/10.1007/s10633-026-10088-9","workflowStages":[]},"version":"v1","identity":"rs-7327743","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7327743","identity":"rs-7327743","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}