The DOI matches its Crossref record.
In search of the visual pigment template
Open accessAbstract
Absorbance spectra were recorded by microspectrophotometry from 39 different rod and cone types representing amphibians, reptiles, and fishes, with A1- or A2-based visual pigments and λ max ranging from 357 to 620 nm. The purpose was to investigate accuracy limits of putative universal templates for visual pigment absorbance spectra, and if possible to amend the templates to overcome the limitations. It was found that (1) the absorbance spectrum of frog rhodopsin extract very precisely parallels that of rod outer segments from the same individual, with only a slight hypsochromic shift in λ max, hence templates based on extracts are valid for absorbance in situ; (2) a template based on the bovine rhodopsin extract data of Partridge and De Grip (1991) describes the absorbance of amphibian rod outer segments excellently, contrary to recent electrophysiological results; (3) the λ max/λ invariance of spectral shape fails for A1 pigments with small λ max and for A2 pigments with large λ max, but the deviations are systematic and can be readily incorporated into, for example, the Lamb (1995) template. We thus propose modified templates for the main “α-band” of A1 and A2 pigments and show that these describe both absorbance and spectral sensitivities of photoreceptors over the whole range of λ max. Subtraction of the α-band from the full absorbance spectrum leaves a “β-band” described by a λ max-dependent Gaussian. We conclude that the idea of universal templates (one for A1- and one for A2-based visual pigments) remains valid and useful at the present level of accuracy of data on photoreceptor absorbance and sensitivity. The sum of our expressions for the α- and β-band gives a good description for visual pigment spectra with λ max > 350 nm.
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
A review of the evolution of animal colour vision and visual communication signals
Osorio, D., & Vorobyev, M. (2008) · Vision Research · doi:10.1016/j.visres.2008.06.018 · Cited by 401
Bailes, H. J., & Lucas, R. J. (2013) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2012.2987 · Cited by 319
Enezi, J. A., Revell, V., Brown, T., Wynne, J., Schlangen, L., & Lucas, R. (2011) · Journal of Biological Rhythms · doi:10.1177/0748730411409719 · Cited by 278
Light and the laboratory mouse
Peirson, S. N., Brown, L. A., Pothecary, C. A., Benson, L. A., & Fisk, A. S. (2018) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2017.04.007 · Cited by 234
“…MWS cone opsin, which is the most ong-wavelength sensitive of the mouse retinal photopigments, t 580 nm, absorption is around 17% (−0.8 log units), at 600 nm bsorption is around 5% (−1.3 log units) and at 635 nm absorption s around 0.4% (−2.4 log units) (Govardovskii et al., 2000; Sun et al., 997).”
InfluentialMelanopsin-Based Brightness Discrimination in Mice and Humans
Brown, T. M., Tsujimura, S.-I., Allen, A. E., Wynne, J., Bedford, R., Vickery, G., Vugler, A., & Lucas, R. J. (2012) · Current Biology · doi:10.1016/j.cub.2012.04.039 · Cited by 256
Metadata
- Authors
- GOVARDOVSKII, V. I., FYHRQUIST, N., REUTER, T., KUZMIN, D. G., & DONNER, K.
- Venue
- Visual Neuroscience
- Publisher
- Maximum Academic Press
- Published
- 2000-07
- Volume
- 17
- Issue
- 4
- Pages
- 509-528
- ISSN
- 0952-5238 (ISSN-L)
- 1469-8714
- OpenAlex
- W2157308120
- Cited by
- 1,055
- References
- 0
- FWCI
- 4.66
- Type
- journal article
- Language
- en
- Open access
- green
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: In search of the visual pigment template. https://app.cochat.ai/papers/10.1017/s0952523800174036
- The paper
- GOVARDOVSKII, V. I., FYHRQUIST, N., REUTER, T., KUZMIN, D. G., & DONNER, K. (2000). In search of the visual pigment template. Visual Neuroscience. https://doi.org/10.1017/s0952523800174036
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.