The DOI matches its Crossref record.
Human photoreceptor topography
Abstract
We have measured the spatial density of cones and rods in eight wholemounted human retinas, obtained from seven individuals between 27 and 44 years of age, and constructed maps of photoreceptor density and between‐individual variability. The average human retina contains 4.6 million cones (4.08–5.29 million). Peak foveal cone density averages 199,000 cones/mm 2 and is highly variable between individuals (100,000–324,000 cones/mm 2). The point of highest density may be found in an area as large as 0.032 deg 2. Cone density falls steeply with increasing eccentricity and is an order of magnitude lower 1 mm away from the foveal center. Superimposed on this gradient is a streak of high cone density along the horizontal meridian. At equivalent eccentricities, cone density is 40–45% higher in nasal compared to temporal retina and slightly higher in midperipheral inferior compared to superior retina. Cone density also increases slightly in far nasal retina. The average human retina contains 92 million rods (77.9–107.3 million). In the fovea, the average horizontal diameter of the rod‐free zone is 0.350 mm (1.25°). Foveal rod density increases most rapidly superiorly and least rapidly nasally. The highest rod densities are located along an elliptical ring at the eccentricity of the optic disk and extending into nasal retina with the point of highest density typically in superior retina (5/6 eyes). Rod densities decrease by 15–25% where the ring crosses the horizontal meridian. Rod density declines slowly from the rod ring to the far periphery and is highest in nasal and superior retina. Individual variability in photoreceptor density differs with retinal region and is similar for both cones and rods. Variability is highest near the fovea, reaches a minimum in the midperiphery, and then increases with eccentricity to the ora serrata. The total number of foveal cones is similar for eyes with widely varying peak cone density, consistent with the idea that the variability reflects differences in the lateral migration of photoreceptors during development. Two fellow eyes had cone and rod numbers within 8% and similar but not identical photoreceptor topography.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Russell, S., Bennett, J., Wellman, J. A., Chung, D. C., Yu, Z.-F., Tillman, A., Wittes, J., Pappas, J., Elci, O., McCague, S., et al. (2017) · The Lancet · doi:10.1016/s0140-6736(17)31868-8 · Cited by 1,952
(2012) · neural information processing systems · Cited by 1,291
Transcriptional regulation of photoreceptor development and homeostasis in the mammalian retina
Swaroop, A., Kim, D., & Forrest, D. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2880 · Cited by 560
Heier, J. S., Lad, E. M., Holz, F. G., Rosenfeld, P. J., Guymer, R. H., Boyer, D., Grossi, F., Baumal, C. R., Korobelnik, J.-F., Slakter, J. S., et al. (2023) · The Lancet · doi:10.1016/s0140-6736(23)01520-9 · Cited by 520
Immunological and Aetiological Aspects of Macular Degeneration
Penfold, P. L., Madigan, M. C., Gillies, M. C., & Provis, J. M. (2001) · Progress in Retinal and Eye Research · doi:10.1016/s1350-9462(00)00025-2 · Cited by 460
Tactile innervation densities across the whole body
Corniani, G., & Saal, H. P. (2020) · Journal of Neurophysiology · doi:10.1152/jn.00313.2020 · Cited by 396
Curcio, C. A., Messinger, J. D., Sloan, K. R., McGwin, G., Medeiros, N. E., & Spaide, R. F. (2013) · Retina · doi:10.1097/iae.0b013e31827e25e0 · Cited by 384
Self-citationThe genetics of normal and defective color vision
Neitz, J., & Neitz, M. (2011) · Vision Research · doi:10.1016/j.visres.2010.12.002 · Cited by 377
Ratnapriya, R., Sosina, O. A., Starostik, M. R., Kwicklis, M., Kapphahn, R. J., Fritsche, L. G., Walton, A., Arvanitis, M., Gieser, L., Pietraszkiewicz, A., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0351-9 · Cited by 312
Functional connectivity in the retina at the resolution of photoreceptors
Field, G. D., Gauthier, J. L., Sher, A., Greschner, M., Machado, T. A., Jepson, L. H., Shlens, J., Gunning, D. E., Mathieson, K., Dabrowski, W., et al. (2010) · Nature · doi:10.1038/nature09424 · Cited by 332
Photoreceptor degeneration and dysfunction in aging and age-related maculopathy
Jackson, G. R., Owsley, C., & Curcio, C. A. (2002) · Ageing Research Reviews · doi:10.1016/s1568-1637(02)00007-7 · Cited by 317
Self-citationNrl knockdown by AAV-delivered CRISPR/Cas9 prevents retinal degeneration in mice
Yu, W., Mookherjee, S., Chaitankar, V., Hiriyanna, S., Kim, J.-W., Brooks, M., Ataeijannati, Y., Sun, X., Dong, L., Li, T., et al. (2017) · Nature Communications · doi:10.1038/ncomms14716 · Cited by 271
Cheng, H. (2004) · Human Molecular Genetics · doi:10.1093/hmg/ddh173 · Cited by 268
Leber congenital amaurosis due to RPE65 mutations and its treatment with gene therapy
Cideciyan, A. V. (2010) · Progress in Retinal and Eye Research · doi:10.1016/j.preteyeres.2010.04.002 · Cited by 256
The relationship between visual resolution and cone spacing in the human fovea
Rossi, E. A., & Roorda, A. (2010) · Nature Neuroscience · doi:10.1038/nn.2465 · Cited by 255
A comparison of some organizational characteristics of the mouse central retina and the human macula
Volland, S., Esteve-Rudd, J., Hoo, J., Yee, C., & Williams, D. S. (2015) · PLoS ONE · doi:10.1371/journal.pone.0125631 · Cited by 229
Watson, A. B. (2014) · Journal of Vision · doi:10.1167/14.7.15 · Cited by 197
Gene therapy rescues cone function in congenital achromatopsia
Komáromy, A. M., Alexander, J. J., Rowlan, J. S., Garcia, M. M., Chiodo, V. A., Kaya, A., Tanaka, J. C., Acland, G. M., Hauswirth, W. W., & Aguirre, G. D. (2010) · Human Molecular Genetics · doi:10.1093/hmg/ddq136 · Cited by 217
The neural bases of spatial frequency processing during scene perception
Kauffmann, L., Ramanoël, S., & Peyrin, C. (2014) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2014.00037 · Cited by 210
Retinal photoreceptor density decreases with age
Panda-Jonas, S., Jonas, J. B., & Jakobczyk-Zmija, M. (1995) · Ophthalmology · doi:10.1016/s0161-6420(95)30784-1 · Cited by 208
Functional photoreceptor loss revealed with adaptive optics: An alternate cause of color blindness
Carroll, J., Neitz, M., Hofer, H., Neitz, J., & Williams, D. R. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0401440101 · Cited by 191
Distribution and Density of Medium- and Short-wavelength Selective Cones in the Domestic Pig Retina
Hendrickson, A., & Hicks, D. (2002) · Experimental Eye Research · doi:10.1006/exer.2002.1181 · Cited by 183
Self-citationGarafalo, A. V., Cideciyan, A. V., Héon, E., Sheplock, R., Pearson, A., WeiYang Yu, C., Sumaroka, A., Aguirre, G. D., & Jacobson, S. G. (2020) · Progress in Retinal and Eye Research · doi:10.1016/j.preteyeres.2019.100827 · Cited by 173
How does the macula protect itself from oxidative stress?
Handa, J. T. (2012) · Molecular Aspects of Medicine · doi:10.1016/j.mam.2012.03.006 · Cited by 154
The role of primary cilia in the development and disease of the retina
Wheway, G., Parry, D. A., & Johnson, C. A. (2014) · Organogenesis · doi:10.4161/org.26710 · Cited by 152
Sura, A. A., Chen, L., Messinger, J. D., Swain, T. A., McGwin, G., Freund, K. B., & Curcio, C. A. (2020) · Investigative Opthalmology & Visual Science · doi:10.1167/iovs.61.13.19 · Cited by 148
Self-citationRetinal Laminar Architecture in Human Retinitis Pigmentosa Caused by Rhodopsin Gene Mutations
Aleman, T. S., Cideciyan, A. V., Sumaroka, A., Windsor, E. A. M., Herrera, W., White, D. A., Kaushal, S., Naidu, A., Roman, A. J., Schwartz, S. B., et al. (2008) · Investigative Opthalmology & Visual Science · doi:10.1167/iovs.07-1110 · Cited by 133
Zanzottera, E. C., Messinger, J. D., Ach, T., Smith, R. T., & Curcio, C. A. (2015) · Investigative Opthalmology & Visual Science · doi:10.1167/iovs.15-16432 · Cited by 110
Self-citationLipids, oxidized lipids, oxidation-specific epitopes, and Age-related macular degeneration.
Handa, J. T., Cano, M., Wang, L., Datta, S., & Liu, T. (2017) · Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids · doi:10.1016/j.bbalip.2016.07.013 · Cited by 112
Adaptive optics retinal imaging reveals S-cone dystrophy in tritan color vision deficiency
Baraas, R. C., Carroll, J., Gunther, K. L., Chung, M., Williams, D. R., Foster, D. H., & Neitz, M. (2007) · Journal of the Optical Society of America A · doi:10.1364/josaa.24.001438 · Cited by 100
Ultrastructure of the human retina in aging and various pathological states
Nag, T. C., & Wadhwa, S. (2012) · Micron · doi:10.1016/j.micron.2012.01.011 · Cited by 88
Bonnel, S., Mohand-Said, S., & Sahel, J.-A. (2003) · Experimental Gerontology · doi:10.1016/s0531-5565(03)00093-7 · Cited by 89
Wang, X., Yu, C., Tzekov, R. T., Zhu, Y., & Li, W. (2020) · Orphanet Journal of Rare Diseases · doi:10.1186/s13023-020-1304-1 · Cited by 68
A decisional account of subjective inflation of visual perception at the periphery
Solovey, G., Graney, G. G., & Lau, H. (2015) · Attention, Perception, & Psychophysics · doi:10.3758/s13414-014-0769-1 · Cited by 63
New Vision for Visual Prostheses
Farnum, A., & Pelled, G. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00036 · Cited by 58
STARNES, A. C., HUISINGH, C., MCGWIN, G., SLOAN, K. R., ABLONCZY, Z., SMITH, R. T., CURCIO, C. A., & ACH, T. (2016) · Visual Neuroscience · doi:10.1017/s0952523815000310 · Cited by 46
Self-citationCarroll, J., Rossi, E. A., Porter, J., Neitz, J., Roorda, A., Williams, D. R., & Neitz, M. (2010) · Vision Research · doi:10.1016/j.visres.2010.07.009 · Cited by 49
Unraveling the Enigma of Nonarteritic Anterior Ischemic Optic Neuropathy
Rizzo, J. F. (2019) · Journal of Neuro-Ophthalmology · doi:10.1097/wno.0000000000000870 · Cited by 34
Trinh, M., Kalloniatis, M., Alonso-Caneiro, D., & Nivison-Smith, L. (2022) · Investigative Opthalmology & Visual Science · doi:10.1167/iovs.63.5.36 · Cited by 29
Functional organization of midget and parasol ganglion cells in the human retina
Kling, A., Gogliettino, A. R., Shah, N. P., Wu, E. G., Brackbill, N., Sher, A., Litke, A. M., Silva, R. A., & Chichilnisky, E. J. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.08.07.240762 · Cited by 24
Congenital Color Blindness in Young Turkish Men
Citirik, M., Acaroglu, G., Batman, C., & Zilelioglu, O. (2005) · Ophthalmic Epidemiology · doi:10.1080/09286580590932743 · Cited by 29
Palani, H. P., & Giudice, N. A. (2017) · ACM Transactions on Accessible Computing · doi:10.1145/3035537 · Cited by 29
Caruso, R. C., Aleman, T. S., Cideciyan, A. V., Roman, A. J., Sumaroka, A., Mullins, C. L., Boye, S. L., Hauswirth, W. W., & Jacobson, S. G. (2010) · Investigative Opthalmology & Visual Science · doi:10.1167/iovs.10-5559 · Cited by 26
Advances in neuroscience, not devices, will determine the effectiveness of visual prostheses
Abbasi, B., & Rizzo, J. F. (2021) · Seminars in Ophthalmology · doi:10.1080/08820538.2021.1887902 · Cited by 19
Pig models in retinal research and retinal disease
McCall, M. A. (2024) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a041296 · Cited by 21
Fine, I., & Boynton, G. M. (2024) · Scientific Reports · doi:10.1038/s41598-024-65337-1 · Cited by 19
A machine learning framework to optimize optic nerve electrical stimulation for vision restoration
Romeni, S., Zoccolan, D., & Micera, S. (2021) · Patterns · doi:10.1016/j.patter.2021.100286 · Cited by 17
Sensitivity of mammalian cone photoreceptors to infrared light
Vinberg, F., Palczewska, G., Zhang, J., Komar, K., Wojtkowski, M., Kefalov, V. J., & Palczewski, K. (2019) · Neuroscience · doi:10.1016/j.neuroscience.2019.07.047 · Cited by 15
Trinh, M., Khou, V., Kalloniatis, M., & Nivison-Smith, L. (2021) · Investigative Opthalmology & Visual Science · doi:10.1167/iovs.62.13.13 · Cited by 14
Kiel, C., Prins, S., Foss, A. J. E., & Luthert, P. J. (2025) · PLOS ONE · doi:10.1371/journal.pone.0311169 · Cited by 6
Metadata
- Authors
- Curcio, C. A., Sloan, K. R., Kalina, R. E., & Hendrickson, A. E.
- Venue
- Journal of Comparative Neurology
- Publisher
- Wiley
- Published
- 1990-02-22
- Volume
- 292
- Issue
- 4
- Pages
- 497-523
- ISSN
- 0021-9967 (ISSN-L)
- 1096-9861
- OpenAlex
- W2087344433
- Cited by
- 2,790
- References
- 0
- FWCI
- 6.75
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
