10.5061/DRYAD.GR38V6R
Cheney, Karen L.
University of Queensland
Green, Naomi.F.
University of Queensland
Vibert, Alexander P.
University of Queensland
Vorobyev, Misha
University of Auckland
Marshall, Justin
University of Queensland
Osorio, Daniel C.
University of Sussex
Endler, John A.
Deakin University
Data from: An Ishihara-style test of animal colour vision
Dryad
dataset
2018
colour measurement
Colour Vision
2018-10-31T19:18:00Z
2018-10-31T19:18:00Z
en
https://doi.org/10.1242/jeb.189787
776669 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Colour vision mediates ecologically relevant tasks for many animals, such
as mate choice, foraging and predator avoidance. However, our
understanding of animal colour perception is largely derived from human
psychophysics, even though animal visual systems differ from our own.
Behavioural tests of non-human animals are required to understand how
colour signals are perceived by them. Here we introduce a novel test of
colour vision in animals inspired by the Ishihara colour charts, which are
widely used to identify human colour deficiencies. These charts consist of
dots that vary in colour, brightness and size, and are designed so that a
numeral or letter is distinguishable from distractor dots for humans with
normal colour vision. In our method, distractor dots have a fixed
chromaticity (hue and saturation) but vary in luminance. Animals can be
trained to find single target dots that differ from distractor dots in
chromaticity. We provide Matlab code for creating these stimuli, which can
be modified for use with different animals. We demonstrate the success of
this method with triggerfish, Rhinecanthus aculeatus, and highlight
behavioural parameters that can be measured, including success of finding
the target dot, time to detect dot and error rate. Triggerfish quickly
learnt to select target dots that differed from distractors dots
regardless of the particular hue or saturation, and proved to use acute
colour vision. We measured discrimination thresholds by testing the
detection of target colours that were of increasing colour distances (∆S)
from distractor dots in different directions of colour space. At least for
some colours, thresholds indicated better discrimination than expected
from the Receptor Noise Limited (RNL) model assuming 5% Weber fraction for
the long-wavelength cone. This methodology seems to be highly effective
because it resembles natural foraging behavior for the triggerfish and may
well be adaptable to a range of other animals, including mammals, birds,
bees and freshwater fish. Other questions may be addressed using this
methodology, including luminance thresholds, sensory bias, effects of
sensory noise in detection tasks, colour categorization and saliency
BackgroundDiskDataCircleGetRGBcombinationsIshiharaoidAndStimuliReadParamsIshiharaoidDiskGenerationIshiParametersAchromaticMakeStimuliOnGrayBackgroundReadme