Modeling spectral sensitivity — sensmodel • pavo

Models spectral sensitivity (with oil droplets; optional) based on peak cone sensitivity according to the models of Govardovskii et al. (2000) and Hart & Vorobyev (2005).

Usage

sensmodel(
  peaksens,
  range = c(300, 700),
  lambdacut = NULL,
  Bmid = NULL,
  oiltype = NULL,
  beta = TRUE,
  om = NULL,
  integrate = TRUE,
  sensnames = paste0("lmax", peaksens),
  template = c("govardovskii_a1", "govardovskii_a2", "ssh_a1", "ssh_a2")
)

Arguments

peaksens

(required) a vector with peak sensitivities for the cones to model.

range

a vector of length 2 for the range over which to calculate the spectral sensitivities (defaults to 300nm to 700nm).

lambdacut

a vector of same length as peaksens that lists the cut-off wavelength value for oil droplets. Needs either Bmid or oiltype to also be entered. See Hart and Vorobyev (2005).

Bmid

a vector of same length as peaksens that lists the gradient of line tangent to the absorbance spectrum of the oil droplets. See Hart and Vorobyev (2005).

oiltype

a list of same length as peaksens that lists the oil droplet types (currently accepts only "T", C", "Y", "R", "P") when Bmid is not known. Calculates Bmid based on the regression equations found in Hart ad Vorobyev (2005).

beta

logical. If TRUE the sensitivities will include the beta peak See Govardovskii et al.(2000) (defaults to TRUE).

om

a vector of same length as range1-range2 that contains ocular media transmission data. If included, cone sensitivity will be corrected for ocular media transmission. Currently accepts "bird" using values from Hart et al. (2005), or user-defined values.

integrate

logical. If TRUE, each curve is transformed to have a total area under the curve of 1 (best for visual models; defaults to TRUE). NOTE: integration is applied before any effects of ocular media are considered, for compatibility with visual model procedures.

sensnames

A vector equal in length to peaksens, specifying custom names for the resulting sensitivity curves (e.g. c('s', 'm', 'l') for short-, medium- and long-wavelength sensitive receptors.)

template

the pigment template used to generate the curves. Both the author and the chromophore are named, since a template's shape depends on both. One of:

"govardovskii_a1" (default): Govardovskii et al. (2000), vitamin A1 chromophore (rhodopsin). The most widely used template, and previously the only implemented option.
"govardovskii_a2": Govardovskii et al. (2000), vitamin A2 chromophore (porphyropsin), found in freshwater fish, amphibians, and species that switch chromophore seasonally. Fitted to microspectrophotometric data from pigments peaking between roughly 440 and 620 nm. The recommended choice for A2 pigments, and the one to pair with the default when comparing chromophores, since staying within one template family avoids confounding chromophore with template.
"ssh_a1": Stavenga, Smits and Hoenders (1993), vitamin A1. Differs from "govardovskii_a1" by only a few percent above 450 nm, but diverges in the ultraviolet, where Stavenga (2010) judges both to be unreliable.
"ssh_a2": Stavenga, Smits and Hoenders (1993), vitamin A2, calibrated on carp porphyropsin alone.

At a given peaksens an A2 band is substantially broader than the A1 equivalent, so a porphyropsin pigment is not recovered by shifting peaksens alone.

beta = FALSE is recommended with either SSH template. Their beta band has a fixed peak wavelength, rather than one that scales with peaksens as Govardovskii's does, so for short-wavelength pigments it pulls the maximum of the summed curve away from the peaksens that was asked for (by up to 8 nm for "ssh_a1" between 388 and 402 nm, and by more than 5 nm for "ssh_a2" anywhere below about 475 nm), and a warning is given wherever the shift exceeds 5 nm. Stavenga (2010) notes that a fixed beta peak is a known shortcoming of the template, the beta peak being correlated with the alpha peak in practice. Both Govardovskii beta bands scale with peaksens and do not have this problem.

Value

A data frame of class rspec containing each cone model as a column.

References

Govardovskii VI, Fyhrquist N, Reuter T, Kuzmin DG and Donner K. 2000. In search of the visual pigment template. Visual Neuroscience 17:509-528, doi:10.1017/S0952523800174036

Hart NS, and Vorobyev M. 2005. Modeling oil droplet absorption spectra and spectral sensitivities of bird cone photoreceptors. Journal of Comparative Physiology A. 191: 381-392, doi:10.1007/s00359-004-0595-3

Stavenga DG, Smits RP, Hoenders BJ. 1993. Simple exponential functions describing the absorbance bands of visual pigment spectra. Vision Research 33:1011-1017, doi:10.1016/0042-6989(93)90237-Q

Stavenga DG. 2010. On visual pigment templates and the spectral shape of invertebrate rhodopsins and metarhodopsins. Journal of Comparative Physiology A 196:869-878, doi:10.1007/s00359-010-0568-7

Hart NS, Partridge JC, Cuthill IC, Bennett AT (2000) Visual pigments, oil droplets, ocular media and cone photoreceptor distribution in two species of passerine bird: the blue tit (Parus caeruleus L.) and the blackbird (Turdus merula L.). J Comp Physiol A 186:375-387, doi:10.1007/s003590050437

Author

Pierre-Paul Bitton bittonp@uwindsor.ca

Chad Eliason cme16@zips.uakron.edu

Examples

# Blue tit visual system based on Hart et al (2000)
bluesens <- sensmodel(c(371, 448, 502, 563),
  beta = FALSE,
  lambdacut = c(330, 413, 507, 572),
  oiltype = c("T", "C", "Y", "R"), om = TRUE
)

# Danio aequipinnatus based on Govardovskii et al. (2000)
daniosens <- sensmodel(c(357, 411, 477, 569))