University of Sussex
Browse
- No file added yet -

The importance of spatial visual scene parameters in predicting optimal cone sensitivities in routinely trichromatic frugivorous old-world primates

Download (1.33 MB)
journal contribution
posted on 2023-06-09, 12:39 authored by Tristan Matthews, Daniel Colaco OsorioDaniel Colaco Osorio, Andrea Cavalaro, Lars Chittka
Computational models that predict the spectral sensitivities of primate cone photoreceptors have focussed only on the spectral, not spatial, dimensions. On the ecologically valid task of foraging for fruit, such models predict the M-cone (“green”) peak spectral sensitivity 10–20 nm further from the L-cone (“red”) sensitivity peak than it is in nature and assume their separation is limited by other visual constraints, such as the requirement of high-acuity spatial vision for closer M and L peak sensitivities. We explore the possibility that a spatio-chromatic analysis can better predict cone spectral tuning without appealing to other visual constraints. We build a computational model of the primate retina and simulate chromatic gratings of varying spatial frequencies using measured spectra. We then implement the case study of foveal processing in routinely trichromatic primates for the task of discriminating fruit and leaf spectra. We perform an exhaustive search for the configurations of M and L cone spectral sensitivities that optimally distinguish the colour patterns within these spectral images. Under such conditions, the model suggests that: (1) a long-wavelength limit is required to constrain the L cone spectral sensitivity to its natural position; (2) the optimal M cone peak spectral sensitivity occurs at ~525 nm, close to the observed position in nature (~535 nm); (3) spatial frequency has a small effect upon the spectral tuning of the cones; (4) a selective pressure toward less correlated M and L spectral sensitivities is provided by the need to reduce noise caused by the luminance variation that occurs in natural scenes.

History

Publication status

  • Published

File Version

  • Published version

Journal

Frontiers in Computational Neuroscience

ISSN

1662-5188

Publisher

Frontiers Media

Volume

12

Page range

1-13

Department affiliated with

  • Biology and Environmental Science Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2018-03-28

First Open Access (FOA) Date

2018-03-28

First Compliant Deposit (FCD) Date

2018-03-27

Usage metrics

    University of Sussex (Publications)

    Categories

    No categories selected

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC