{"paper_id":"5bb50d19-49c3-470b-a46a-2554ef798ffb","body_text":"Robust and Reproducible Population Receptive Field Mapping in Patients with Retinal Pathologies | 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 Article Robust and Reproducible Population Receptive Field Mapping in Patients with Retinal Pathologies Markus Ritter, Maximilian Pawloff, David Linhardt, Michael Woletz, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8299947/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Purpose: Previous studies have shown high reproducibility of population receptive field (pRF) mapping in young, healthy individuals. The present study examines whether such a level of reproducibility can also be achieved in patients suffering from retinal disease. Methods: Eleven patients with Stargardt disease and eleven patients with geographic atrophy (GA) secondary to age-related macular degeneration (AMD) were examined in up to four sessions using high-resolution ultra-high field fMRI (Siemens Magnetom 7T) and microperimetry (MP, Nidek MP-3). Reproducibility of the pRF parameters within and between sessions was assessed using Spearman’s correlation coefficient. Results: Retinotopic maps calculated from ultra-high field MRI had excellent intra- and intersession reproducibility for pRF center position (median correlation between sessions for pRF center eccentricity: r = 0.91; polar angle: r = 0.90), but only modest reproducibility for pRF size (average correlation r = 0.39). Reproducibility was constant across sessions multiple weeks apart, indicating a long-term stability of the method. In addition, the results show that reproducibility is not related to the severity of retinal disease. Conclusion: The data demonstrate that retinotopic mapping of the primary visual cortex using ultra-high field MRI is a highly reproducible technique for the assessment of macular function in patients with retinal disease. The technique provides an unbiased quantification of retinal function adjunct to conventional clinical assessments and may assist the early diagnosis of retinal disease. In addition, it may be a valuable objective method for monitoring visual deficits during long-term therapeutic interventions or disease progression. Health sciences/Diseases/Eye diseases/Retinal diseases Health sciences/Diseases/Eye diseases/Hereditary eye disease Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Numerous techniques are available for the evaluation of retinal function in patients suffering from retinal disease. Subjective examination methods, such as perimetry or visual acuity testing, are most commonly used but psychophysical data may be influenced by attention levels and other subjective factors. Microperimetry (MP), for example, tests localized retinal sensitivity in the foveal, parafoveal, and peripheral macular regions. 1 Whilst MP allows for structure-function correlation and is used in clinical trials investigating new therapies, results are subject not only to patient performance and learning effects, but also to ceiling and floor effects in devices with limited luminance range. 2 , 3 Although reproducibility of mean retinal sensitivity in perimetry and MP has been demonstrated in patient populations 2 , 3 , those studies only assessed intrasession reproducibility, with a short average interval of five minutes between tests. A separate study investigating the intersession variability of MP in patients with type 2 macular telangiectasia, where authors warranted exclusion of the first session due to statistically significant training effects and a mean test-retest variability as high as 3.3 dB, further emphasized the impact of learning effects on psychophysical measurements. 4 In contrast, functional magnetic resonance imaging (fMRI) provides an objective and non-invasive method for assessing neural activity in response to visual stimuli, independent of patient attention or subjective perception. It measures changes in the amplitude of the MR signal based on variations in neuronal activity, offering an intrinsic biological marker of functional brain responses. 5 FMRI offers the possibility to map activation patterns with high spatial resolution in cortical and subcortical areas of the brain. As such, it is the optimal tool for investigating retinotopic organization, a key feature of the human visual system. Retinotopic projection of the visual field in the visual cortex ensures that neighbouring areas of the retina are encoded in adjacent cortical areas. In retinotopic fMRI scans, patients are presented with a combination of stimuli that include rotating wedges and expanding rings or moving bars to determine eccentricity and polar angle of visual field positions in the visual cortex. 6 Population retinotopic field (pRF) mapping, an extension of this method, was developed by Dumoulin and Wandell whereby neuronal receptive fields are estimated by a model-driven approach which enables detailed representations of the visual field at the cortical level to be revealed. 7 In this model, a receptive field (RF) is described as the extent of the visual field where stimulation leads to neural activity in a specific area of the visual cortex. While it is not possible to estimate RFs of single neuron, neurons with similar receptive fields are located in close proximity to each other. This leads to the representation of a population of neurons in every cortical voxel of fMRI datasets. Hence the name of the method. Several fMRI studies have explored cortical responses to visual stimuli in the context of retinal disease. Initial reports included a study of a patient with age-related macular degeneration (AMD) in which fMRI retinotopic mapping revealed a distinct unresponsive zone in the primary visual cortex, also known as visual area 1 (V1), corresponding to the retinal lesion. 8 A number of other studies demonstrated that fMRI-derived cortical \"silent zones\" closely matched perimetry-derived visual field defects in patients with retinal pathology. 9 – 13 Those studies used retinotopic fMRI at magnetic field strengths of up to 3 Tesla. The availability of MRI scanners operating at ultra-high fields of 7 Tesla and above has opened new possibilities as higher magnetic fields yield higher MR signal strengths and allow for higher resolution of the acquired activation maps. 14 In healthy participants, it has been shown that pRF results at 7 Tesla are highly reproducible 15 but no such data is available for clinical populations. The present study assesses the reproducibility of pRF mapping results at 7 Tesla in patients with Stargardt disease (STGD) or geographic atrophy (GA) secondary to AMD. Both pathologies are characterised by central macular atrophy and central visual field loss. Macular lesions may initially appear perifoveally and expand with time to involve the fovea. This distinct lesion pattern makes these patients prime cases for exploring the cortical representation of central retinal scotomata. Both intrasession and intersession reproducibility were investigated. Methods Subjects Eleven patients with genetically confirmed variants in ABCA4 (STGD; 7 male, 4 female; age: 29.3 ± 8.8 years) and eleven patients with GA (7 male, 4 female; age: 72.6 ± 5.0 years) participated. All had a secure clinical diagnosis supported by optical coherence tomography (OCT). Inclusion criteria for STGD and GA patients consisted of (1) a well-demarcated central atrophic macular lesion with or without foveal sparing, not exceeding 15° visual angle diameter and (2) fixation stability classified as stable or relatively unstable as measured by MP (see below). The study was approved by the institutional review board of the Medical University of Vienna (EK1594/2018) and was conducted in accordance with the Declaration of Helsinki and the International Conference of Harmonization of Good Clinical Practice guidelines. Written informed consent was obtained from all patients before their participation. Clinical examination Patients underwent slit-lamp examination, dilated fundus examination and best-corrected visual acuity (BCVA) testing using Early Treatment Diabetic Retinopathy Study (ETDRS) charts. A Spectralis HRA & OCT system (Heidelberg Engineering, Heidelberg, Germany) provided spectral-domain OCT (SD-OCT) and blue-light fundus autofluorescence (FAF) images. Central retinal function was assessed by microperimetry (MP-3 Nidek, Padova, Italy). Stimulus intensity ranged from 0dB to 32dB in 1dB steps. The stimulus pattern consisted of a foveal 3x3 grid surrounded by three rings at a radius of 3° (8 points), 5.1° (12 points) and 7° (12 points) eccentricity. Fixation stability was assessed and classified as stable if 90% of fixations were located within a 2° circle, as relatively unstable if ≥ 80% of fixations were located within a 2° circle and as unstable if less than 80% of fixations were located within a 2° circle. Functional MRI measurements and pRF analysis Functional MRI measurements were performed on a Siemens MAGNETOM 7T scanner (Siemens Healthineers, Erlangen, Germany) utilizing a 32-channel head coil. Subjects participated in up to four scanning sessions, on average 23 days apart. Each MRI session lasted approximately 1 hour and followed the clinical examination. The subjects completed two functional runs within each session using the CMRR EPI sequence 11 with the following parameters: isotropic spatial resolution of 1mm, TE = 25.2 ms, TR = 2000 ms, field-of-view 128 × 128 mm, flip angle = 70°, GRAPPA acceleration = 2, slice spacing = 10%. Functional data comprised thirty-two slices placed perpendicular to the calcarine sulcus and covering the patients’ early visual areas. An additional functional scan with inverted phase encoding readout polarity was measured for later distortion correction using fsl topup. Within every session, a full-brain structural image was acquired using a magnetization-prepared rapid gradient-echo (MPRAGE) sequence (0.7 mm isotropic resolution, TE = 3.66 ms, TR = 1960 ms, flip angle = 9°, matrix size 320 x 310, field of view (FoV) = 217 × 224 mm, 224 slices) which was later used for tissue segmentation. Subjects were able to view the back of the bore through a mirror mounted inside the head coil. Stimuli were presented on a custom-built back-projection screen attached to the patient bed. To minimize reflections in the bore, the screen was mounted as close to the subject as possible, resulting in a mean screen-to-eye distance of approximately 62cm. The non-study eye was patched. Motion was minimized through extensive padding. Data processing included brain tissue segmentation performed on the anatomical data using Freesurfer ( https://surfer.nmr.mgh.harvard.edu ). The automated segmentation result was manually corrected for topological errors. Based on these segmentation results, all further analysis was restricted to voxels located within the grey matter. Functional data was pre-processed using a custom pipeline including slice-timing, realignment, distortion correction and co-registration to the anatomical image. Spatial smoothing was applied on the volume data using an isotropic 2mm FWHM Gaussian kernel. To reduce expected biases, the data was analyzed in volume space and projected to the surface only for visualization purposes. Retinotopic pRF analysis was performed in MATLAB, facilitating vistasoft ( github.com/vistalab/vistasoft ), using the 2D Gaussian model. Independently for each voxel, the corresponding visual field location (x, y) and size of the receptive field (σ) were estimated in a two-stage fitting procedure. 7 This analysis establishes a discrete mapping between positions in the early visual cortex and locations in the visual field. The two functional runs acquired in each session were analyzed independently as well as averaged and analyzed as session average. This allows for the analysis of intra- as well as inter-session reproducibility. Based on the resulting polar angle maps the primary visual cortex was manually delineated. Analyses were restricted to V1, as it offers the most direct cortical representation of retinal input and the most reliable basis for mapping scotomata. Stimuli Stimulation patterns during the fMRI scan covered the central 14° of visual angle and were presented using mrVista (Vista Lab, Stanford University, California) within the Matlab programming environment (The MathWorks, Inc., Natick, Massachusetts). The visual stimulus involved a bar moving across a screen, upon which was displayed an isoluminant reversing checkerboard pattern at a frequency of 16 reversals/sec. The bar width was 1.75°, representing 12.5% of the total stimulus area, and it traversed the screen in 18 discrete steps, each separated by 0.8° of visual angle in space, with a repetition time (TR) of 2 seconds. The bar moved in 8 different directions per run, and after each pass, the bar and checkerboard were rotated by 45°. Following each diagonal pass, a 12-second pause displayed a blank grey screen of similar mean luminance. Each run lasted 5 minutes and 36 seconds, corresponding to 168 volumes. Participants were instructed to fixate on a small central dot (12 pixels or 0.22° visual angle diameter). Since accurate fixation was critical, thin diagonal lines (5 pixels or 0.09° visual angle diameter) intersecting at the fixation dot were displayed to aid patients in maintaining stable fixation. To further ensure fixation compliance and attention during the experiment, the fixation dot color changed pseudo-randomly and subjects were asked to report these changes via button press. The rate of correct detections is referred to as fixation performance. Reproducibility analyses By realigning all runs within each session into the same space, direct voxel-to-voxel comparisons were possible. Before computing correlations, we applied a 20% explained-variance threshold to each run to restrict analyses to well-fitted voxels. Correlations were calculated only for voxels present in both compared datasets and runs with fewer than 300 overlapping voxels were excluded. Reproducibility was assessed by computing Spearman’s correlation coefficient (SCC) for pRF eccentricity and size, and circular correlation coefficient 16 for polar angle across all voxels within each subject’s V1. For the intrasession comparison, the correlation was calculated between two independently analyzed runs within each session. For the intersession comparison, the two runs of each session were first averaged, and maps from session 1 were correlated with those from sessions 2–4. Sessions were excluded if fixation performance in any run fell below 50% or if the mean frame-wise displacement exceeded 1 mm. For the comparison of mean microperimetry (MP) intensity and pRF reproducibility, each subject’s between-session pRF reproducibility values were averaged across all included sessions. MP intensity was averaged across the entire visual field and across sessions. The relationship between mean MP intensity and pRF reproducibility was then assessed across subjects using linear regression. Whenever correlation coefficients were averaged, values were first Fisher z-transformed and converted back after averaging to ensure proper statistical weighting and to correct for the nonlinearity of the correlation scale. Results The reproducibility of fMRI was investigated as an objective tool for visual field-predictions in 22 patients with central visual field defects. Clinical characteristics of all patients are shown in Table 1 . Table 1 Patient data and microperimetry fixation stability Patient number Sex Age Eye VA logMAR % MP1 fixation 2° % MP1 fixation 4° STGD01 m 34 OD 0.699 99.3 99.6 STGD02 m 23 OD 0.903 70.6 95.4 STGD03 m 36 OS 0.204 94.9 96.7 STGD04 f 31 OS 0.796 73.5 97.2 STGD05 m 22 OD 1 48.2 90.6 STGD06 f 21 OD 0.602 95.7 96.6 STGD07 f 24 OD 0.097 99.2 99.8 STGD08 m 25 OD 0.204 94.5 97.0 STGD09 m 34 OD 0.498 95.1 97.3 STGD10 f 22 OS 0.097 96.6 100 STGD11 m 52 OS 0.097 90 96.3 GA01 f 73 OD 0.204 81.2 90.8 GA02 f 66 OS 0.097 94.8 97.5 GA03 m 71 OS 0.398 88.8 98.3 GA04 m 74 OD 0.204 93.4 99.3 GA05 m 68 OS 0.498 100 100 GA06 m 77 OS 0.204 87.9 97.9 GA07 f 73 OD 0.301 85.9 95.7 GA08 m 77 OD 0.301 88.6 98.1 GA09 f 64 OS 0.204 93.7 97.1 GA10 m 79 OD 0 97.4 99.6 GA11 m 69 OS 0.097 82.7 95 Reproducibility Reproducibility was assessed using 59 sessions of 17 unique subjects (9 GA, 8 STGD) after application of exclusion criteria (see Fig. 2 .), by calculating Spearman’s correlation for eccentricity and pRF size and circular correlation for polar angle. 16 Intra- and intersession reproducibility were evaluated separately. Within sessions, median reproducibility was high for polar angle (GA: r = 0.93; STGD: r = 0.95) and eccentricity (GA: r = 0.91; STGD: r = 0.82), while pRF size showed lower reproducibility (GA: r = 0.36; STGD: r = 0.34). No significant group differences were observed for polar angle (p = 0.75) or pRF size (p = 0.77), whereas eccentricity reproducibility was higher in GA than in STGD (p = 0.008). Between sessions, eccentricity reproducibility remained high (GA: r = 0.92; STGD: r = 0.85). Polar-angle reproducibility was substantially lower in GA than in STGD (GA: r = 0.74; STGD: r = 0.95), while pRF size reproducibility was modest in both groups (GA: r = 0.38; STGD: r = 0.42). No significant differences were found between groups for eccentricity (p = 0.39) or pRF size (p = 0.16), whereas polar-angle reproducibility was slightly lower in GA than in STGD (p = 0.033). Correlation coefficients for eccentricity, polar angle, and pRF size across various intra- and intersessional comparisons are detailed in Figs. 3 and 4 , with corresponding values provided in Table 2 . Table 2 Group-median correlation coefficients for eccentricity, polar angle and pRF size across sessions and runs. eccentricity polar angle pRF size GA S 1 R 1 vs R 2 0.94 0.95 0.35 S 2 R 1 vs R 2 0.91 0.91 0.26 S 3 R 1 vs R 2 0.91 0.86 0.28 S 4 R 1 vs R 2 0.90 0.94 0.37 S 1 vs S 2 averaged runs 0.90 0.77 0.33 S 1 vs S 3 averaged runs 0.92 0.62 0.36 S 1 vs S 4 averaged runs 0.91 0.82 0.44 STGD S 1 R 1 vs R 2 0.88 0.96 0.43 S 2 R 1 vs R 2 0.81 0.88 0.30 S 3 R 1 vs R 2 0.86 0.96 0.33 S 4 R 1 vs R 2 0.68 0.97 0.27 S 1 vs S 2 averaged runs 0.92 0.92 0.44 S 1 vs S 3 averaged runs 0.79 0.97 0.40 S 1 vs S 4 averaged runs 0.90 0.95 0.46 Reproducibility was further examined across the severity of retinal deficits. Mean MP values were used as measures for the extent of their respective pathology. Reproducibility of both pRF eccentricity and polar angle remained high across all scotoma sizes (see Fig. 5 ). The lower reproducibility of pRF size was also consistent across the range of mean MP values. Since there were no significant differences in reproducibility between visits, no training effects were detected in pRF measurements. Discussion This study assesses intra- and intersession reproducibility of pRF mapping results in a clinical setting using ultra-high field MRI. Twenty two patients suffering from either geographic atrophy (GA) or Stargardt disease (STGD) completed up to four fMRI scanning sessions. We observed high reproducibility for pRF position parameters (eccentricity, polar angle) and lower reproducibility for pRF size. Within-session reproducibility values were not substantially worse than in healthy participants without visual field loss 12 , 15 , 17 – 19 and in individual with simulated scotomata 20 . Our results underscore that even substantial deviations from the assumed smoothness of pRF centre distributions do not necessarily compromise the stability of position estimates and support the potential applicability of pRF mapping in clinical ophthalmology. A recent study reported higher reproducibility, especially for pRF sizes due to methodological improvements. 21 The study used a logarithmically warped bar stimulus which was locally optimized to match the receptive field sizes of the corresponding region of cortical space. This approach yielded more reliable pRF estimates than a standard bar stimulus with constant width, especially for pRFs located near the central visual field (for comparison see Linhardt et al. 22 ; Alvarez et al. 23 ). These results highlight that small adaptations in the stimulation paradigm could potentially boost pRF mapping reproducibility significantly. In future pRF mapping, stimuli could be further advanced to optimally map scotomata, thus increasing the clinical relevance of the method. Our findings acknowledge a systematic shift of pRF centers from inside the lesion toward functional retinal regions. This shift arises from the modelling approach itself and does not necessarily reflect cortical reorganization 24 . Although explicit modelling of the scotoma, as proposed by Binda et al. 24 , can partly mitigate this effect, such approaches are not feasible in patients with irregular or poorly defined scotoma borders. Moreover, recent work has shown that even when the scotoma is explicitly modelled, pRF estimates can still be biased 25 , underscoring that this issue warrants further investigation. Therefore, we used a naïve modelling approach without explicit scotoma masking and focused on reproducibility rather than absolute retinotopic accuracy. Thus, the reported reproducibility reflects the stability of the pRF mapping method, including its systematic modelling biases under conditions of partial visual-field loss, rather than the reproducibility of the true retinotopic map itself. The relationship between pRF reproducibility and mean MP threshold suggests that reduced retinal sensitivity only has a modest impact on the stability of pRF estimates (see Fig. 5 .). Subjects with better-preserved visual sensitivity showed slightly higher reproducibility, particularly for polar-angle and pRF-size parameters, yet even individuals with extensive central field loss exhibited robust correlations across sessions. Outlierts, mainly in the polar-angle data, reflect subjects with isolated sessions of low between-session reproducibility, as apparent in Figs. 4 . and 5., which slightly lowered the overall subject average. These cases likely represent session-specific variability rather than systematic instability, and the overall pattern still supports the robustness of pRF mapping for longitudinal assessment in patients with macular degeneration. While conventional flickering checkerboard tasks presented as full-field stimuli are much simpler than population receptive field (pRF) stimuli and have been utilized since the very early days of fMRI 26 , they cannot be used for scotoma mapping on the retina, as they do not allow for mapping visual field position to visual cortex activation. For patients with unknown scotoma layout, estimation of simulated scotomata using pRF mapping, or retinotopic mapping in general, offers the opportunity simultaneously to investigate the effects of scotomata on visual cortex activation and link these effects to visual field positions. This method thus allows for a comprehensive understanding of how visual field defects affect cortical representations, providing valuable insights into the relationship between retinal pathology and cortical activation. Our analyses focused on V1 because it provides the most direct and spatially precise cortical representation of retinal input. Higher visual areas (V2–V3) are more strongly influenced by feedback and integrative processing, which may confound the interpretation of pRF changes in patients. In this clinical setting, polar angle and eccentricity yielded very high reproducibility values (r = 0.90 and 0.91) on par with previously reported values in healthy cohorts (r = > 0.98 and > 0.87) 22 , whereas size showed low correlation values. Our findings further substantiate that among the parameters utilized in pRF mapping, the pRF size parameter demonstrates notably lower reproducibility. 12 , 15 , 17 – 19 , 21 This underscores the need for further advancements in this technique. Consequently, emphasis should be placed on the pRF center position rather than the size parameter for the interpretation of pRF data, given its greater reliability and stability. Notably, GA patients showed slightly lower between-session reproducibility for the polar-angle parameter compared with their within-session estimates, whereas STGD patients exhibited comparable values across sessions. This difference might reflect subtle changes in the scotoma border or local adaptation processes in GA patients, though this interpretation remains speculative. While inside the scanner, patients were instructed to focus strictly on the central fixation dot, and those with insufficient adherence to the fixation task were excluded from formal analysis. Some runs still appeared to exhibit activation in the areas of outer retinal atrophy, possibly due to unstable fixation. A possible solution might be the implementation of fixation tracking using an eye-tracking and gaze stability correction system, as implemented by Hummer et al. (2016). 27 Future studies would greatly benefit from integrating standardized online eye-tracking in 7T MRI scanners. In a previous study, it was demonstrated that retinotopic mapping using fMRI is a valuable objective tool for assessing therapeutic responses in neovascular AMD patients undergoing anti-vascular endothelial growth factor therapy, emphasizing its capability to evaluate functional recovery at the cortical level 13 . Consistent with those findings, this study shows that pRF mapping remains highly stable in patients under a constant disease state. This stability implies that any observed change at the visual cortex level genuinely reflects the disease progression itself, rather than being attributable to random methodological artifacts. Consequently, this technique holds promise for use in long-term studies involving patient populations. This is particularly relevant as recent studies on inherited retinal diseases have begun to explore the impact of retinal gene therapy on brain activity related to vision. It was reported that patients with Leber congenital amaurosis exhibited improved visual processing responses in the lateral geniculate nucleus and primary visual cortex on fMRI following treatment. The improvements, reflecting partial restoration of normal visual processing through the geniculostriate pathway, correlated with enhanced light sensitivity in clinical tests. 28 In conclusion, the data demonstrates that mapping population receptive field (pRF) centers (i.e. polar angle and eccentricity) yields highly reproducible results, whilst the width of the pRF, as estimated by the pRF size, is less reproducible using this approach. The pRF technique implemented herein provides a valuable adjunct to conventional clinical assessments and may help in the early diagnosis and monitoring of retinal diseases and holds potential for broader application in evaluating therapeutic interventions, such as gene therapy or cell replacement therapy, in other degenerative macular diseases apart from geographic atrophy and Stargardt disease. Declarations Ethics approval and consent to participate / Consent for publication: The study was approved by the institutional review board of the Medical University of Vienna (EK1594/2018) and was conducted in accordance with the Declaration of Helsinki and the International Conference of Harmonization of Good Clinical Practice guidelines. Written informed consent was obtained from all patients before their participation. Competing interests: There are no financial or non-financial competing interests to be disclosed. Funding: Funding was granted by the Austrian Science Fund (FWF); KLI 670-B30; P35583 Authors' contributions: Maximilian Pawloff: substantial contributions to the acquisition, analysis, interpretation of data and draft of the work. David Linhardt: substantial contributions to the acquisition, analysis, interpretation of data and revision of the work. Michael Woletz: substantial contributions to the analysis and interpretation of data Marlene Hollaus: substantial contributions to the draft of the work. Georgios Mylonas: substantial contributions to the acquisition of data. Graham E. Holder: substantial contributions to the draft and revision of the work. Stefan Sacu: : substantial contributions to the conception and revision of the work. Christian Windischberger: substantial contributions to the conception and design and revision of the work. Markus Ritter: substantial contributions to the conception and design and revision of the work. Acknowledgements: The authors acknowledge that artificial intelligence tools (ChatGPT) were used for text editing, and proofreading. References Hanout M, Horan N, Do D V. Introduction to microperimetry and its use in analysis of geographic atrophy in age-related macular degeneration. Curr Opin Ophthalmol. 2015;26(3):149–156. doi: 10.1097/ICU.0000000000000153 Wu Z, Ayton LN, Guymer RH, Luu CD. 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Additional Declarations There is no conflict of interest Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: revise 13 Jan, 2026 Review # 1 received at journal 10 Jan, 2026 Reviewer # 1 agreed at journal 09 Jan, 2026 Reviewers invited by journal 09 Jan, 2026 Editor assigned by journal 17 Dec, 2025 Submission checks completed at journal 08 Dec, 2025 First submitted to journal 07 Dec, 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. We do this by developing innovative software and high quality services for the global research community. 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11:39:05\",\"extension\":\"xml\",\"order_by\":31,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"acdc-reference\",\"size\":106560,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"EYE2534760structuring.xml\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8299947/v1/b9d0b7f589dd4a9b69afc752.xml\"},{\"id\":100395659,\"identity\":\"28cb2b72-8209-4bd7-8901-733228eeddbf\",\"added_by\":\"auto\",\"created_at\":\"2026-01-16 11:39:17\",\"extension\":\"html\",\"order_by\":32,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"acdc-reference\",\"size\":120952,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"earlyproof.html\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8299947/v1/ec5f921f49e6c858116846e3.html\"},{\"id\":100395838,\"identity\":\"165dbf26-a0a3-47b2-8258-c5496b535143\",\"added_by\":\"auto\",\"created_at\":\"2026-01-16 11:39:27\",\"extension\":\"jpg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":203717,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eComparison of MP, FAF, OCT and pRF mapping results for an example GA and STGD patient each. PRF Coverage Map comparison of session 1 and session 4 show pRF coverage maps. The Coverage Maps show the coverage plots where each dot corresponds to a detected pRF center, while the bottom half shows eccentricity values overlaid on the visual cortex surface.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8299947/v1/8480af3ed052fff1fbe3a3ef.jpg\"},{\"id\":100395441,\"identity\":\"dd16aaaa-7533-44c8-9782-1c0c1448cb6c\",\"added_by\":\"auto\",\"created_at\":\"2026-01-16 11:39:02\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":51786,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eFlowchart of the exclusion process. Six pRF sessions of GA patients and 17 pRF sessions of STGD patients were excluded due to low fixation performance, insufficient data quality or movement artifacts, resulting in 59 sessions from 17 patients to be included for analysis.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8299947/v1/0dac0c33bba5fe563969f2e3.png\"},{\"id\":100406109,\"identity\":\"3493ff6a-629d-49c2-8540-d238ab49ff32\",\"added_by\":\"auto\",\"created_at\":\"2026-01-16 12:40:40\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":131217,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003epRF reproducibility of STGD patients. Spearman’s correlation coefficients are shown for pRF eccentricity and pRF size and circular correlation for polar angle. Columns 1–4 display intrasession comparisons, and columns 5–7 intersession comparisons. Each box represents the distribution across all included subjects within the patient group, and circles indicate identified outliers for each parameter and comparison type.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8299947/v1/7f9689a331f43c37f69868e0.png\"},{\"id\":100395956,\"identity\":\"c7f0a759-c41a-42df-8ad1-21d1e0c955e1\",\"added_by\":\"auto\",\"created_at\":\"2026-01-16 11:39:39\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":130270,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003epRF reproducibility in GA patients. Spearman’s correlation coefficients are shown for pRF eccentricity and pRF size and circular correlation for polar angle. Columns 1–4 display intrasession comparisons, and columns 5–7 intersession comparisons. Each box represents the distribution across all included subjects within the patient group, and circles indicate identified outliers for each parameter and comparison type.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8299947/v1/7fe27dcbe092ccc62137f9de.png\"},{\"id\":100395845,\"identity\":\"09d9a825-e22d-4b3b-82f7-6aa439a5cbc1\",\"added_by\":\"auto\",\"created_at\":\"2026-01-16 11:39:28\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":231892,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eCorrelation of between-session pRF reproducibility with mean MP intensity. For each subject, pRF reproducibility was computed between sessions using run-averaged maps, and both pRF reproducibility and MP intensities were averaged across the entire visual field and all available data for the respective subject. Each dot represents one subject. The grey line indicates the best-fit linear regression across all subjects, and the shaded area shows the 95% confidence interval. Reproducibility of pRF position parameters (eccentricity, polar angle) remains high across the full range of mean MP values, whereas pRF size shows lower reproducibility and a slight reduction in subjects with larger scotomata (lower mean MP values).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8299947/v1/b2d0004a229b4afc18d55185.png\"},{\"id\":100413565,\"identity\":\"f5364dc7-ff4b-497f-bad3-055204ebc3c7\",\"added_by\":\"auto\",\"created_at\":\"2026-01-16 13:17:39\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1457987,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8299947/v1/35683c47-c711-4c1b-afe9-70286ccfd1a4.pdf\"}],\"financialInterests\":\"There is no conflict of interest\",\"formattedTitle\":\"Robust and Reproducible Population Receptive Field Mapping in Patients with Retinal Pathologies\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eNumerous techniques are available for the evaluation of retinal function in patients suffering from retinal disease. Subjective examination methods, such as perimetry or visual acuity testing, are most commonly used but psychophysical data may be influenced by attention levels and other subjective factors. Microperimetry (MP), for example, tests localized retinal sensitivity in the foveal, parafoveal, and peripheral macular regions.\\u003csup\\u003e\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e\\u003c/sup\\u003e Whilst MP allows for structure-function correlation and is used in clinical trials investigating new therapies, results are subject not only to patient performance and learning effects, but also to ceiling and floor effects in devices with limited luminance range.\\u003csup\\u003e\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e\\u003c/sup\\u003e Although reproducibility of mean retinal sensitivity in perimetry and MP has been demonstrated in patient populations \\u003csup\\u003e\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e\\u003c/sup\\u003e, those studies only assessed intrasession reproducibility, with a short average interval of five minutes between tests. A separate study investigating the intersession variability of MP in patients with type 2 macular telangiectasia, where authors warranted exclusion of the first session due to statistically significant training effects and a mean test-retest variability as high as 3.3 dB, further emphasized the impact of learning effects on psychophysical measurements.\\u003csup\\u003e\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e \\u003cp\\u003eIn contrast, functional magnetic resonance imaging (fMRI) provides an objective and non-invasive method for assessing neural activity in response to visual stimuli, independent of patient attention or subjective perception. It measures changes in the amplitude of the MR signal based on variations in neuronal activity, offering an intrinsic biological marker of functional brain responses.\\u003csup\\u003e\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e\\u003c/sup\\u003e FMRI offers the possibility to map activation patterns with high spatial resolution in cortical and subcortical areas of the brain. As such, it is the optimal tool for investigating retinotopic organization, a key feature of the human visual system. Retinotopic projection of the visual field in the visual cortex ensures that neighbouring areas of the retina are encoded in adjacent cortical areas.\\u003c/p\\u003e \\u003cp\\u003eIn retinotopic fMRI scans, patients are presented with a combination of stimuli that include rotating wedges and expanding rings or moving bars to determine eccentricity and polar angle of visual field positions in the visual cortex.\\u003csup\\u003e\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e\\u003c/sup\\u003e Population retinotopic field (pRF) mapping, an extension of this method, was developed by Dumoulin and Wandell whereby neuronal receptive fields are estimated by a model-driven approach which enables detailed representations of the visual field at the cortical level to be revealed.\\u003csup\\u003e\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u003c/sup\\u003e In this model, a receptive field (RF) is described as the extent of the visual field where stimulation leads to neural activity in a specific area of the visual cortex. While it is not possible to estimate RFs of single neuron, neurons with similar receptive fields are located in close proximity to each other. This leads to the representation of a population of neurons in every cortical voxel of fMRI datasets. Hence the name of the method.\\u003c/p\\u003e \\u003cp\\u003eSeveral fMRI studies have explored cortical responses to visual stimuli in the context of retinal disease. Initial reports included a study of a patient with age-related macular degeneration (AMD) in which fMRI retinotopic mapping revealed a distinct unresponsive zone in the primary visual cortex, also known as visual area 1 (V1), corresponding to the retinal lesion. \\u003csup\\u003e8\\u003c/sup\\u003e A number of other studies demonstrated that fMRI-derived cortical \\\"silent zones\\\" closely matched perimetry-derived visual field defects in patients with retinal pathology.\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR10 CR11 CR12\\\" citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e\\u003c/sup\\u003eThose studies used retinotopic fMRI at magnetic field strengths of up to 3 Tesla. The availability of MRI scanners operating at ultra-high fields of 7 Tesla and above has opened new possibilities as higher magnetic fields yield higher MR signal strengths and allow for higher resolution of the acquired activation maps.\\u003csup\\u003e\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e\\u003c/sup\\u003e In healthy participants, it has been shown that pRF results at 7 Tesla are highly reproducible\\u003csup\\u003e\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e\\u003c/sup\\u003e but no such data is available for clinical populations.\\u003c/p\\u003e \\u003cp\\u003eThe present study assesses the reproducibility of pRF mapping results at 7 Tesla in patients with Stargardt disease (STGD) or geographic atrophy (GA) secondary to AMD. Both pathologies are characterised by central macular atrophy and central visual field loss. Macular lesions may initially appear perifoveally and expand with time to involve the fovea. This distinct lesion pattern makes these patients prime cases for exploring the cortical representation of central retinal scotomata. Both intrasession and intersession reproducibility were investigated.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eSubjects\\u003c/h2\\u003e \\u003cp\\u003eEleven patients with genetically confirmed variants in ABCA4 (STGD; 7 male, 4 female; age: 29.3\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;8.8 years) and eleven patients with GA (7 male, 4 female; age: 72.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.0 years) participated. All had a secure clinical diagnosis supported by optical coherence tomography (OCT). Inclusion criteria for STGD and GA patients consisted of (1) a well-demarcated central atrophic macular lesion with or without foveal sparing, not exceeding 15\\u0026deg; visual angle diameter and (2) fixation stability classified as stable or relatively unstable as measured by MP (see below).\\u003c/p\\u003e \\u003cp\\u003eThe study was approved by the institutional review board of the Medical University of Vienna (EK1594/2018) and was conducted in accordance with the Declaration of Helsinki and the International Conference of Harmonization of Good Clinical Practice guidelines. Written informed consent was obtained from all patients before their participation.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eClinical examination\\u003c/h3\\u003e\\n\\u003cp\\u003ePatients underwent slit-lamp examination, dilated fundus examination and best-corrected visual acuity (BCVA) testing using Early Treatment Diabetic Retinopathy Study (ETDRS) charts. A Spectralis HRA \\u0026amp; OCT system (Heidelberg Engineering, Heidelberg, Germany) provided spectral-domain OCT (SD-OCT) and blue-light fundus autofluorescence (FAF) images. Central retinal function was assessed by microperimetry (MP-3 Nidek, Padova, Italy). Stimulus intensity ranged from 0dB to 32dB in 1dB steps. The stimulus pattern consisted of a foveal 3x3 grid surrounded by three rings at a radius of 3\\u0026deg; (8 points), 5.1\\u0026deg; (12 points) and 7\\u0026deg; (12 points) eccentricity. Fixation stability was assessed and classified as stable if 90% of fixations were located within a 2\\u0026deg; circle, as relatively unstable if\\u0026thinsp;\\u0026ge;\\u0026thinsp;80% of fixations were located within a 2\\u0026deg; circle and as unstable if less than 80% of fixations were located within a 2\\u0026deg; circle.\\u003c/p\\u003e\\n\\u003ch3\\u003eFunctional MRI measurements and pRF analysis\\u003c/h3\\u003e\\n\\u003cp\\u003eFunctional MRI measurements were performed on a Siemens MAGNETOM 7T scanner (Siemens Healthineers, Erlangen, Germany) utilizing a 32-channel head coil. Subjects participated in up to four scanning sessions, on average 23 days apart. Each MRI session lasted approximately 1 hour and followed the clinical examination. The subjects completed two functional runs within each session using the CMRR EPI sequence\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003e with the following parameters: isotropic spatial resolution of 1mm, TE\\u0026thinsp;=\\u0026thinsp;25.2 ms, TR\\u0026thinsp;=\\u0026thinsp;2000 ms, field-of-view 128 \\u0026times; 128 mm, flip angle\\u0026thinsp;=\\u0026thinsp;70\\u0026deg;, GRAPPA acceleration\\u0026thinsp;=\\u0026thinsp;2, slice spacing\\u0026thinsp;=\\u0026thinsp;10%. Functional data comprised thirty-two slices placed perpendicular to the calcarine sulcus and covering the patients\\u0026rsquo; early visual areas. An additional functional scan with inverted phase encoding readout polarity was measured for later distortion correction using fsl topup. Within every session, a full-brain structural image was acquired using a magnetization-prepared rapid gradient-echo (MPRAGE) sequence (0.7 mm isotropic resolution, TE\\u0026thinsp;=\\u0026thinsp;3.66 ms, TR\\u0026thinsp;=\\u0026thinsp;1960 ms, flip angle\\u0026thinsp;=\\u0026thinsp;9\\u0026deg;, matrix size 320 x 310, field of view (FoV)\\u0026thinsp;=\\u0026thinsp;217 \\u0026times; 224 mm, 224 slices) which was later used for tissue segmentation.\\u003c/p\\u003e \\u003cp\\u003eSubjects were able to view the back of the bore through a mirror mounted inside the head coil. Stimuli were presented on a custom-built back-projection screen attached to the patient bed. To minimize reflections in the bore, the screen was mounted as close to the subject as possible, resulting in a mean screen-to-eye distance of approximately 62cm. The non-study eye was patched. Motion was minimized through extensive padding.\\u003c/p\\u003e \\u003cp\\u003eData processing included brain tissue segmentation performed on the anatomical data using Freesurfer (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://surfer.nmr.mgh.harvard.edu\\u003c/span\\u003e\\u003cspan address=\\\"https://surfer.nmr.mgh.harvard.edu\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e).\\u003c/span\\u003e The automated segmentation result was manually corrected for topological errors. Based on these segmentation results, all further analysis was restricted to voxels located within the grey matter. Functional data was pre-processed using a custom pipeline including slice-timing, realignment, distortion correction and co-registration to the anatomical image. Spatial smoothing was applied on the volume data using an isotropic 2mm FWHM Gaussian kernel. To reduce expected biases, the data was analyzed in volume space and projected to the surface only for visualization purposes.\\u003c/p\\u003e \\u003cp\\u003eRetinotopic pRF analysis was performed in MATLAB, facilitating vistasoft (\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003egithub.com/vistalab/vistasoft\\u003c/span\\u003e), using the 2D Gaussian model. Independently for each voxel, the corresponding visual field location (x, y) and size of the receptive field (σ) were estimated in a two-stage fitting procedure.\\u003csup\\u003e\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u003c/sup\\u003e This analysis establishes a discrete mapping between positions in the early visual cortex and locations in the visual field. The two functional runs acquired in each session were analyzed independently as well as averaged and analyzed as session average. This allows for the analysis of intra- as well as inter-session reproducibility. Based on the resulting polar angle maps the primary visual cortex was manually delineated. Analyses were restricted to V1, as it offers the most direct cortical representation of retinal input and the most reliable basis for mapping scotomata.\\u003c/p\\u003e\\n\\u003ch3\\u003eStimuli\\u003c/h3\\u003e\\n\\u003cp\\u003eStimulation patterns during the fMRI scan covered the central 14\\u0026deg; of visual angle and were presented using mrVista (Vista Lab, Stanford University, California) within the Matlab programming environment (The MathWorks, Inc., Natick, Massachusetts). The visual stimulus involved a bar moving across a screen, upon which was displayed an isoluminant reversing checkerboard pattern at a frequency of 16 reversals/sec. The bar width was 1.75\\u0026deg;, representing 12.5% of the total stimulus area, and it traversed the screen in 18 discrete steps, each separated by 0.8\\u0026deg; of visual angle in space, with a repetition time (TR) of 2 seconds. The bar moved in 8 different directions per run, and after each pass, the bar and checkerboard were rotated by 45\\u0026deg;. Following each diagonal pass, a 12-second pause displayed a blank grey screen of similar mean luminance. Each run lasted 5 minutes and 36 seconds, corresponding to 168 volumes.\\u003c/p\\u003e \\u003cp\\u003eParticipants were instructed to fixate on a small central dot (12 pixels or 0.22\\u0026deg; visual angle diameter). Since accurate fixation was critical, thin diagonal lines (5 pixels or 0.09\\u0026deg; visual angle diameter) intersecting at the fixation dot were displayed to aid patients in maintaining stable fixation. To further ensure fixation compliance and attention during the experiment, the fixation dot color changed pseudo-randomly and subjects were asked to report these changes via button press. The rate of correct detections is referred to as fixation performance.\\u003c/p\\u003e\\n\\u003ch3\\u003eReproducibility analyses\\u003c/h3\\u003e\\n\\u003cp\\u003eBy realigning all runs within each session into the same space, direct voxel-to-voxel comparisons were possible. Before computing correlations, we applied a 20% explained-variance threshold to each run to restrict analyses to well-fitted voxels. Correlations were calculated only for voxels present in both compared datasets and runs with fewer than 300 overlapping voxels were excluded.\\u003c/p\\u003e \\u003cp\\u003eReproducibility was assessed by computing Spearman\\u0026rsquo;s correlation coefficient (SCC) for pRF eccentricity and size, and circular correlation coefficient\\u003csup\\u003e\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e\\u003c/sup\\u003e for polar angle across all voxels within each subject\\u0026rsquo;s V1. For the intrasession comparison, the correlation was calculated between two independently analyzed runs within each session. For the intersession comparison, the two runs of each session were first averaged, and maps from session 1 were correlated with those from sessions 2\\u0026ndash;4. Sessions were excluded if fixation performance in any run fell below 50% or if the mean frame-wise displacement exceeded 1 mm.\\u003c/p\\u003e \\u003cp\\u003eFor the comparison of mean microperimetry (MP) intensity and pRF reproducibility, each subject\\u0026rsquo;s between-session pRF reproducibility values were averaged across all included sessions. MP intensity was averaged across the entire visual field and across sessions. The relationship between mean MP intensity and pRF reproducibility was then assessed across subjects using linear regression. Whenever correlation coefficients were averaged, values were first Fisher z-transformed and converted back after averaging to ensure proper statistical weighting and to correct for the nonlinearity of the correlation scale.\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003eThe reproducibility of fMRI was investigated as an objective tool for visual field-predictions in 22 patients with central visual field defects. Clinical characteristics of all patients are shown in Table \\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003ePatient data and microperimetry fixation stability\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"14\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c9\\\" colnum=\\\"9\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c10\\\" colnum=\\\"10\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c11\\\" colnum=\\\"11\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c12\\\" colnum=\\\"12\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c13\\\" colnum=\\\"13\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c14\\\" colnum=\\\"14\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003ePatient number\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003eSex\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003eAge\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eEye\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003eVA logMAR\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e% MP1 fixation 2\\u0026deg;\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c14\\\" namest=\\\"c13\\\"\\u003e \\u003cp\\u003e% MP1 fixation 4\\u0026deg;\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSTGD01\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003em\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e34\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOD\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.699\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e99.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e99.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSTGD02\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003em\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e23\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOD\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.903\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e70.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e95.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSTGD03\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003em\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e36\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOS\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.204\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e94.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e96.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSTGD04\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003ef\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e31\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOS\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.796\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e73.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e97.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSTGD05\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003em\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e22\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOD\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e48.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e90.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSTGD06\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003ef\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e21\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOD\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.602\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e95.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e96.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSTGD07\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003ef\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e24\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOD\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.097\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e99.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e99.8\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSTGD08\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003em\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e25\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOD\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.204\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e94.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e97.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSTGD09\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003em\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e34\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOD\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.498\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e95.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e97.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSTGD10\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003ef\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e22\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOS\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.097\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e96.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e100\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSTGD11\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003em\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e52\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOS\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.097\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e90\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e96.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eGA01\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003ef\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e73\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOD\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.204\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e81.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e90.8\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eGA02\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003ef\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e66\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOS\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.097\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e94.8\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e97.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eGA03\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003em\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e71\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOS\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.398\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e88.8\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e98.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eGA04\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003em\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e74\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOD\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.204\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e93.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e99.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eGA05\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003em\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e68\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOS\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.498\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e100\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e100\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eGA06\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003em\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e77\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOS\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.204\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e87.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e97.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eGA07\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003ef\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e73\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOD\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.301\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e85.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e95.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eGA08\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003em\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e77\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOD\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.301\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e88.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e98.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eGA09\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003ef\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e64\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOS\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.204\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e93.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e97.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eGA10\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003em\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e79\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOD\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e97.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e99.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eGA11\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003em\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003e69\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eOS\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c10\\\" namest=\\\"c9\\\"\\u003e \\u003cp\\u003e0.097\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c12\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003e82.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e95\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"1\\\" nameend=\\\"c14\\\" namest=\\\"c14\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e\\n\\u003ch3\\u003eReproducibility\\u003c/h3\\u003e\\n\\u003cp\\u003eReproducibility was assessed using 59 sessions of 17 unique subjects (9 GA, 8 STGD) after application of exclusion criteria (see Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e.), by calculating Spearman\\u0026rsquo;s correlation for eccentricity and pRF size and circular correlation for polar angle.\\u003csup\\u003e\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e\\u003c/sup\\u003e Intra- and intersession reproducibility were evaluated separately. Within sessions, median reproducibility was high for polar angle (GA: r\\u0026thinsp;=\\u0026thinsp;0.93; STGD: r\\u0026thinsp;=\\u0026thinsp;0.95) and eccentricity (GA: r\\u0026thinsp;=\\u0026thinsp;0.91; STGD: r\\u0026thinsp;=\\u0026thinsp;0.82), while pRF size showed lower reproducibility (GA: r\\u0026thinsp;=\\u0026thinsp;0.36; STGD: r\\u0026thinsp;=\\u0026thinsp;0.34). No significant group differences were observed for polar angle (p\\u0026thinsp;=\\u0026thinsp;0.75) or pRF size (p\\u0026thinsp;=\\u0026thinsp;0.77), whereas eccentricity reproducibility was higher in GA than in STGD (p\\u0026thinsp;=\\u0026thinsp;0.008).\\u003c/p\\u003e \\u003cp\\u003eBetween sessions, eccentricity reproducibility remained high (GA: r\\u0026thinsp;=\\u0026thinsp;0.92; STGD: r\\u0026thinsp;=\\u0026thinsp;0.85). Polar-angle reproducibility was substantially lower in GA than in STGD (GA: r\\u0026thinsp;=\\u0026thinsp;0.74; STGD: r\\u0026thinsp;=\\u0026thinsp;0.95), while pRF size reproducibility was modest in both groups (GA: r\\u0026thinsp;=\\u0026thinsp;0.38; STGD: r\\u0026thinsp;=\\u0026thinsp;0.42). No significant differences were found between groups for eccentricity (p\\u0026thinsp;=\\u0026thinsp;0.39) or pRF size (p\\u0026thinsp;=\\u0026thinsp;0.16), whereas polar-angle reproducibility was slightly lower in GA than in STGD (p\\u0026thinsp;=\\u0026thinsp;0.033).\\u003c/p\\u003e \\u003cp\\u003eCorrelation coefficients for eccentricity, polar angle, and pRF size across various intra- and intersessional comparisons are detailed in Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e, with corresponding values provided in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eGroup-median correlation coefficients for eccentricity, polar angle and pRF size across sessions and runs.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"5\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eeccentricity\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003epolar angle\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003epRF size\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"6\\\" rowspan=\\\"7\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eGA\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eS 1 R 1 vs R 2\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.94\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.95\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.35\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eS 2 R 1 vs R 2\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.91\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.91\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.26\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eS 3 R 1 vs R 2\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.91\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.86\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.28\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eS 4 R 1 vs R 2\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.90\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.94\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.37\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eS 1 vs S 2 averaged runs\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.90\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.77\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.33\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eS 1 vs S 3 averaged runs\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.92\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.62\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.36\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eS 1 vs S 4 averaged runs\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.91\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.82\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.44\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"6\\\" rowspan=\\\"7\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSTGD\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eS 1 R 1 vs R 2\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.88\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.96\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.43\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eS 2 R 1 vs R 2\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.81\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.88\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.30\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eS 3 R 1 vs R 2\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.86\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.96\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.33\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eS 4 R 1 vs R 2\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.68\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.97\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.27\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eS 1 vs S 2 averaged runs\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.92\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.92\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.44\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eS 1 vs S 3 averaged runs\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.79\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.97\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.40\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eS 1 vs S 4 averaged runs\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.90\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.95\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.46\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eReproducibility was further examined across the severity of retinal deficits. Mean MP values were used as measures for the extent of their respective pathology. Reproducibility of both pRF eccentricity and polar angle remained high across all scotoma sizes (see Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e). The lower reproducibility of pRF size was also consistent across the range of mean MP values. Since there were no significant differences in reproducibility between visits, no training effects were detected in pRF measurements.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThis study assesses intra- and intersession reproducibility of pRF mapping results in a clinical setting using ultra-high field MRI. Twenty two patients suffering from either geographic atrophy (GA) or Stargardt disease (STGD) completed up to four fMRI scanning sessions. We observed high reproducibility for pRF position parameters (eccentricity, polar angle) and lower reproducibility for pRF size. Within-session reproducibility values were not substantially worse than in healthy participants without visual field loss \\u003csup\\u003e\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e,\\u003cspan additionalcitationids=\\\"CR18\\\" citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e\\u003c/sup\\u003e and in individual with simulated scotomata \\u003csup\\u003e\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e\\u003c/sup\\u003e. Our results underscore that even substantial deviations from the assumed smoothness of pRF centre distributions do not necessarily compromise the stability of position estimates and support the potential applicability of pRF mapping in clinical ophthalmology.\\u003c/p\\u003e \\u003cp\\u003eA recent study reported higher reproducibility, especially for pRF sizes due to methodological improvements.\\u003csup\\u003e\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e\\u003c/sup\\u003e The study used a logarithmically warped bar stimulus which was locally optimized to match the receptive field sizes of the corresponding region of cortical space. This approach yielded more reliable pRF estimates than a standard bar stimulus with constant width, especially for pRFs located near the central visual field (for comparison see Linhardt et al. \\u003csup\\u003e22\\u003c/sup\\u003e; Alvarez et al. \\u003csup\\u003e23\\u003c/sup\\u003e). These results highlight that small adaptations in the stimulation paradigm could potentially boost pRF mapping reproducibility significantly. In future pRF mapping, stimuli could be further advanced to optimally map scotomata, thus increasing the clinical relevance of the method.\\u003c/p\\u003e \\u003cp\\u003eOur findings acknowledge a systematic shift of pRF centers from inside the lesion toward functional retinal regions. This shift arises from the modelling approach itself and does not necessarily reflect cortical reorganization \\u003csup\\u003e\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e\\u003c/sup\\u003e. Although explicit modelling of the scotoma, as proposed by Binda et al.\\u003csup\\u003e24\\u003c/sup\\u003e, can partly mitigate this effect, such approaches are not feasible in patients with irregular or poorly defined scotoma borders. Moreover, recent work has shown that even when the scotoma is explicitly modelled, pRF estimates can still be biased \\u003csup\\u003e\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e\\u003c/sup\\u003e, underscoring that this issue warrants further investigation. Therefore, we used a na\\u0026iuml;ve modelling approach without explicit scotoma masking and focused on reproducibility rather than absolute retinotopic accuracy. Thus, the reported reproducibility reflects the stability of the pRF mapping method, including its systematic modelling biases under conditions of partial visual-field loss, rather than the reproducibility of the true retinotopic map itself.\\u003c/p\\u003e \\u003cp\\u003eThe relationship between pRF reproducibility and mean MP threshold suggests that reduced retinal sensitivity only has a modest impact on the stability of pRF estimates (see Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e.). Subjects with better-preserved visual sensitivity showed slightly higher reproducibility, particularly for polar-angle and pRF-size parameters, yet even individuals with extensive central field loss exhibited robust correlations across sessions. Outlierts, mainly in the polar-angle data, reflect subjects with isolated sessions of low between-session reproducibility, as apparent in Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e. and 5., which slightly lowered the overall subject average. These cases likely represent session-specific variability rather than systematic instability, and the overall pattern still supports the robustness of pRF mapping for longitudinal assessment in patients with macular degeneration.\\u003c/p\\u003e \\u003cp\\u003eWhile conventional flickering checkerboard tasks presented as full-field stimuli are much simpler than population receptive field (pRF) stimuli and have been utilized since the very early days of fMRI \\u003csup\\u003e\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e\\u003c/sup\\u003e, they cannot be used for scotoma mapping on the retina, as they do not allow for mapping visual field position to visual cortex activation. For patients with unknown scotoma layout, estimation of simulated scotomata using pRF mapping, or retinotopic mapping in general, offers the opportunity simultaneously to investigate the effects of scotomata on visual cortex activation and link these effects to visual field positions. This method thus allows for a comprehensive understanding of how visual field defects affect cortical representations, providing valuable insights into the relationship between retinal pathology and cortical activation. Our analyses focused on V1 because it provides the most direct and spatially precise cortical representation of retinal input. Higher visual areas (V2\\u0026ndash;V3) are more strongly influenced by feedback and integrative processing, which may confound the interpretation of pRF changes in patients.\\u003c/p\\u003e \\u003cp\\u003eIn this clinical setting, polar angle and eccentricity yielded very high reproducibility values (r\\u0026thinsp;=\\u0026thinsp;0.90 and 0.91) on par with previously reported values in healthy cohorts (r\\u0026thinsp;=\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.98 and \\u0026gt;\\u0026thinsp;0.87)\\u003csup\\u003e22\\u003c/sup\\u003e, whereas size showed low correlation values. Our findings further substantiate that among the parameters utilized in pRF mapping, the pRF size parameter demonstrates notably lower reproducibility.\\u003csup\\u003e\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e,\\u003cspan additionalcitationids=\\\"CR18\\\" citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e\\u003c/sup\\u003e This underscores the need for further advancements in this technique. Consequently, emphasis should be placed on the pRF center position rather than the size parameter for the interpretation of pRF data, given its greater reliability and stability. Notably, GA patients showed slightly lower between-session reproducibility for the polar-angle parameter compared with their within-session estimates, whereas STGD patients exhibited comparable values across sessions. This difference might reflect subtle changes in the scotoma border or local adaptation processes in GA patients, though this interpretation remains speculative.\\u003c/p\\u003e \\u003cp\\u003eWhile inside the scanner, patients were instructed to focus strictly on the central fixation dot, and those with insufficient adherence to the fixation task were excluded from formal analysis. Some runs still appeared to exhibit activation in the areas of outer retinal atrophy, possibly due to unstable fixation. A possible solution might be the implementation of fixation tracking using an eye-tracking and gaze stability correction system, as implemented by Hummer et al. (2016).\\u003csup\\u003e\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e\\u003c/sup\\u003e Future studies would greatly benefit from integrating standardized online eye-tracking in 7T MRI scanners.\\u003c/p\\u003e \\u003cp\\u003eIn a previous study, it was demonstrated that retinotopic mapping using fMRI is a valuable objective tool for assessing therapeutic responses in neovascular AMD patients undergoing anti-vascular endothelial growth factor therapy, emphasizing its capability to evaluate functional recovery at the cortical level\\u003csup\\u003e\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e\\u003c/sup\\u003e. Consistent with those findings, this study shows that pRF mapping remains highly stable in patients under a constant disease state. This stability implies that any observed change at the visual cortex level genuinely reflects the disease progression itself, rather than being attributable to random methodological artifacts. Consequently, this technique holds promise for use in long-term studies involving patient populations. This is particularly relevant as recent studies on inherited retinal diseases have begun to explore the impact of retinal gene therapy on brain activity related to vision. It was reported that patients with Leber congenital amaurosis exhibited improved visual processing responses in the lateral geniculate nucleus and primary visual cortex on fMRI following treatment. The improvements, reflecting partial restoration of normal visual processing through the geniculostriate pathway, correlated with enhanced light sensitivity in clinical tests.\\u003csup\\u003e\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e \\u003cp\\u003eIn conclusion, the data demonstrates that mapping population receptive field (pRF) centers (i.e. polar angle and eccentricity) yields highly reproducible results, whilst the width of the pRF, as estimated by the pRF size, is less reproducible using this approach. The pRF technique implemented herein provides a valuable adjunct to conventional clinical assessments and may help in the early diagnosis and monitoring of retinal diseases and holds potential for broader application in evaluating therapeutic interventions, such as gene therapy or cell replacement therapy, in other degenerative macular diseases apart from geographic atrophy and Stargardt disease.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate / Consent for publication:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe study was approved by the institutional review board of the Medical University of Vienna (EK1594/2018) and was conducted in accordance with the Declaration of Helsinki and the International Conference of Harmonization of Good Clinical Practice guidelines. Written informed consent was obtained from all patients before their participation.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThere are no financial or non-financial competing interests to be disclosed.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eFunding was granted by the Austrian Science Fund (FWF); KLI 670-B30; P35583\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors' contributions:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eMaximilian Pawloff: substantial contributions to the acquisition, analysis, interpretation of data and draft of the work.\\u003c/p\\u003e\\n\\u003cp\\u003eDavid Linhardt: substantial contributions to the acquisition, analysis, interpretation of data and revision of the work.\\u003c/p\\u003e\\n\\u003cp\\u003eMichael Woletz: substantial contributions to the analysis and interpretation of data\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eMarlene Hollaus: substantial contributions to the draft of the work.\\u003c/p\\u003e\\n\\u003cp\\u003eGeorgios Mylonas: substantial contributions to the acquisition of data.\\u003c/p\\u003e\\n\\u003cp\\u003eGraham E. Holder: substantial contributions to the draft and revision of the work.\\u003c/p\\u003e\\n\\u003cp\\u003eStefan Sacu: : substantial contributions to the conception and revision of the work.\\u003c/p\\u003e\\n\\u003cp\\u003eChristian Windischberger: substantial contributions to the conception and design and revision of the work.\\u003c/p\\u003e\\n\\u003cp\\u003eMarkus Ritter: substantial contributions to the conception and design and revision of the work.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors acknowledge that artificial intelligence tools (ChatGPT) were used for text editing, and proofreading.\\u0026nbsp;\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eHanout M, Horan N, Do D V. Introduction to microperimetry and its use in analysis of geographic atrophy in age-related macular degeneration. 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PLoS One. 2014;9(12):e114054. doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1371/journal.pone.0114054\\u003c/span\\u003e\\u003cspan address=\\\"10.1371/journal.pone.0114054\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBenson NC, Jamison KW, Arcaro MJ, et al. The human connectome project 7 Tesla retinotopy dataset: description and population receptive field analysis. In: Journal of Vision. Vol 18.; 2018:23. doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1167/18.13.23\\u003c/span\\u003e\\u003cspan address=\\\"10.1167/18.13.23\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLage-Castellanos A, Valente G, Senden M, De Martino F. 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Published online 1992. doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1073/pnas.89.12.5675\\u003c/span\\u003e\\u003cspan address=\\\"10.1073/pnas.89.12.5675\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHummer A, Ritter M, Tik M, et al. Eyetracker-based gaze correction for robust mapping of population receptive fields. Neuroimage. 2016;142:211\\u0026ndash;224. doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1016/j.neuroimage.2016.07.003\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.neuroimage.2016.07.003\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAshtari M, Bennett J, Leopold DA. Central visual pathways affected by degenerative retinal disease before and after gene therapy. Brain. 2024;147(9):3234\\u0026ndash;3246.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"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\":\"info@researchsquare.com\",\"identity\":\"eye\",\"isNatureJournal\":false,\"hasQc\":false,\"allowDirectSubmit\":false,\"externalIdentity\":\"eye\",\"sideBox\":\"Learn more about [Eye](http://www.nature.com/eye/)\",\"snPcode\":\"41433\",\"submissionUrl\":\"https://mts-eye.nature.com/cgi-bin/main.plex\",\"title\":\"Eye\",\"twitterHandle\":\"@eye_journal\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"ejp\",\"reportingPortfolio\":\"Nature AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false},\"keywords\":\"\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-8299947/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-8299947/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003ePurpose:\\u003c/h2\\u003e \\u003cp\\u003ePrevious studies have shown high reproducibility of population receptive field (pRF) mapping in young, healthy individuals. The present study examines whether such a level of reproducibility can also be achieved in patients suffering from retinal disease.\\u003c/p\\u003e\\u003ch2\\u003eMethods:\\u003c/h2\\u003e \\u003cp\\u003eEleven patients with Stargardt disease and eleven patients with geographic atrophy (GA) secondary to age-related macular degeneration (AMD) were examined in up to four sessions using high-resolution ultra-high field fMRI (Siemens Magnetom 7T) and microperimetry (MP, Nidek MP-3). Reproducibility of the pRF parameters within and between sessions was assessed using Spearman\\u0026rsquo;s correlation coefficient.\\u003c/p\\u003e\\u003ch2\\u003eResults:\\u003c/h2\\u003e \\u003cp\\u003eRetinotopic maps calculated from ultra-high field MRI had excellent intra- and intersession reproducibility for pRF center position (median correlation between sessions for pRF center eccentricity: r\\u0026thinsp;=\\u0026thinsp;0.91; polar angle: r\\u0026thinsp;=\\u0026thinsp;0.90), but only modest reproducibility for pRF size (average correlation r\\u0026thinsp;=\\u0026thinsp;0.39). Reproducibility was constant across sessions multiple weeks apart, indicating a long-term stability of the method. In addition, the results show that reproducibility is not related to the severity of retinal disease.\\u003c/p\\u003e\\u003ch2\\u003eConclusion:\\u003c/h2\\u003e \\u003cp\\u003eThe data demonstrate that retinotopic mapping of the primary visual cortex using ultra-high field MRI is a highly reproducible technique for the assessment of macular function in patients with retinal disease. The technique provides an unbiased quantification of retinal function adjunct to conventional clinical assessments and may assist the early diagnosis of retinal disease. In addition, it may be a valuable objective method for monitoring visual deficits during long-term therapeutic interventions or disease progression.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Robust and Reproducible Population Receptive Field Mapping in Patients with Retinal Pathologies\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2026-01-16 08:19:05\",\"doi\":\"10.21203/rs.3.rs-8299947/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"revise\",\"date\":\"2026-01-13T15:02:32+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"This content is not available.\",\"date\":\"2026-01-10T21:23:22+00:00\",\"index\":1,\"fulltext\":\"This content is not available.\"},{\"type\":\"reviewerAgreed\",\"content\":\"This content is not available.\",\"date\":\"2026-01-09T09:18:50+00:00\",\"index\":1,\"fulltext\":\"This content is not available.\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2026-01-09T09:17:28+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-12-17T14:55:44+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-12-08T11:43:27+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Eye\",\"date\":\"2025-12-07T13:13:37+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"eye\",\"isNatureJournal\":false,\"hasQc\":false,\"allowDirectSubmit\":false,\"externalIdentity\":\"eye\",\"sideBox\":\"Learn more about [Eye](http://www.nature.com/eye/)\",\"snPcode\":\"41433\",\"submissionUrl\":\"https://mts-eye.nature.com/cgi-bin/main.plex\",\"title\":\"Eye\",\"twitterHandle\":\"@eye_journal\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"ejp\",\"reportingPortfolio\":\"Nature AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false}}],\"origin\":\"\",\"ownerIdentity\":\"a0023f98-3c47-4038-89d3-8ae1cbaa0121\",\"owner\":[],\"postedDate\":\"January 16th, 2026\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"under-review\",\"subjectAreas\":[{\"id\":60865643,\"name\":\"Health sciences/Diseases/Eye diseases/Retinal diseases\"},{\"id\":60865644,\"name\":\"Health sciences/Diseases/Eye diseases/Hereditary eye disease\"}],\"tags\":[],\"updatedAt\":\"2026-05-06T11:30:36+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2026-01-16 08:19:05\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-8299947\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-8299947\",\"identity\":\"rs-8299947\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}