A millipede compound eye mediating low-resolution vision

Kirwan, John D.; Nilsson, David

doi:10.1016/j.visres.2019.09.003

Cited by 11 publications

(5 citation statements)

References 26 publications

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“…how an animal can interact visually with its environment and the roles vision may have in different species [16,17]. Direct measurements of the image formed by the eye's optics has been a popular approach [18][19][20] in addition to behavioural measurements [9,12,13,[21][22][23][24][25] and the traditional approach with intracellular recordings of angular sensitivity in individual photoreceptors [6]. A problem with behavioural approaches is that they target specific behaviours and not the general visual abilities of the animal.…”

Section: Discussionmentioning

confidence: 99%

Modelling the visual world of a velvet worm

Ljungholm

Nilsson

2021

PLoS Comput Biol

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In many animal phyla, eyes are small and provide only low-resolution vision for general orientation in the environment. Because these primitive eyes rarely have a defined image plane, traditional visual-optics principles cannot be applied. To assess the functional capacity of such eyes we have developed modelling principles based on ray tracing in 3D reconstructions of eye morphology, where refraction on the way to the photoreceptors and absorption in the photopigment are calculated incrementally for ray bundles from all angles within the visual field. From the ray tracing, we calculate the complete angular acceptance function of each photoreceptor in the eye, revealing the visual acuity for all parts of the visual field. We then use this information to generate visual filters that can be applied to high resolution images or videos to convert them to accurate representations of the spatial information seen by the animal. The method is here applied to the 0.1 mm eyes of the velvet worm Euperipatoides rowelli (Onychophora). These eyes of these terrestrial invertebrates consist of a curved cornea covering an irregular but optically homogeneous lens directly joining a retina packed with photoreceptive rhabdoms. 3D reconstruction from histological sections revealed an asymmetric eye, where the retina is deeper in the forward-pointing direction. The calculated visual acuity also reveals performance differences across the visual field, with a maximum acuity of about 0.11 cycles/deg in the forward direction despite laterally pointing eyes. The results agree with previous behavioural measurements of visual acuity, and suggest that velvet worm vision is adequate for orientation and positioning within the habitat.

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Section: Discussionmentioning

confidence: 99%

Modelling the visual world of a velvet worm

Ljungholm

Nilsson

2021

PLoS Comput Biol

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“…how an animal can interact visually with its environment and the roles vision may have in different species [16,17]. Direct measurements of the image formed by the eye's optics has been a popular approach [18][19][20] in addition to behavioural measurements [10,12,13,[21][22][23][24][25] and the traditional approach with intracellular recordings of angular sensitivity in individual photoreceptors [6]. A problem with behavioural approaches is that they target specific behaviours and not the general visual abilities of the animal.…”

Section: Discussionmentioning

confidence: 99%

Modelling the visual world of a velvet worm

Ljungholm

Nilsson

2021

Preprint

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In many animal phyla, eyes are small and provide only low-resolution vision for general orientation in the environment. Because these primitive eyes rarely have a defined image plane, traditional visual-optics principles cannot be applied. To assess the functional capacity of such eyes we have developed modelling principles based on ray tracing in 3D reconstructions of eye morphology, were refraction on the way to the photoreceptors and absorption in the photopigment are calculated incrementally for ray bundles from all angles withing the visual field. From the ray tracing, we calculate the complete angular acceptance function of each photoreceptor in the eye, revealing the visual acuity for all parts of the visual field. We then use this information to generate visual filters that can be applied to high resolution images or videos to convert them to accurate representations of the spatial information seen by the animal. The method is here applied to the 0.1 mm eyes of the velvet worm Euperipatoides rowelli (Onychophora).These eyes of these terrestrial invertebrates consist of a curved cornea covering an irregular but optically homogeneous lens directly joining a retina packed with photoreceptive rhabdomeres. 3D reconstruction from histological sections revealed an asymmetric eye, where the retina is deeper in the forward-pointing direction. The calculated visual acuity also reveals performance differences across the visual field, with a maximum acuity of about 0.11 cycles/deg in the forward direction despite laterally pointing eyes. The results agree with previous behavioural measurements of visual acuity, and suggest that velvet worm vision is adequate for orientation and positioning within the habitat.

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“…For the psychometric Bayesian method (method ii), we applied a probabilistic model to estimate discrimination thresholds, using the Stan language (Carpenter et al, 2017; http://mc-stan.org/) via the brms package (v2.6.0; Bürkner, 2018; https://cran.r-project.org/ web/packages/brms/) within R. Here, we used a logistic regression model incorporating the psychometric function (see Kirwan and Nilsson, 2019), with success rate for random guessing (0.5) as the estimated lower asymptote and the lapse rate, found in tests with the unrewarded colours O6 and G6 in each experiment, as the upper asymptote. We reparameterised the psychometric function to directly assess the effects of conditions on the curve's inflection point (threshold T ip ) and the range of colour differences that account for 80% of the response range [threshold (m), width (w)]: the 'm,w' parameterisation (Kuss et al, 2005;Houpt and Bittner, 2018; also known as 'threshold, support': Alcalá-Quintana and García-Pérez, 2004).…”

Section: Discussionmentioning

confidence: 99%

Chicken colour discrimination depends on background colour

Olsson

Johnsson

Foster

et al. 2020

Journal of Experimental Biology

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How well can a bird discriminate between two red berries on a green background? The absolute threshold of colour discrimination is set by photoreceptor noise, but animals do not perform at this threshold; their performance can depend on additional factors. In humans and zebra finches, discrimination thresholds for colour stimuli depend on background colour, and thus the adaptive state of the visual system. We have tested how well chickens can discriminate shades of orange or green presented on orange or green backgrounds. Chickens discriminated slightly smaller colour differences between two stimuli presented on a similarly coloured background, compared to a background of very different colour. The slope of the psychometric function is steeper when stimulus and background colours are similar but shallower when they differ markedly, indicating that background colour affects the certainty with which the animals discriminate the colours. The effect we find for chickens is smaller than that shown for zebra finches. We modelled the response to stimuli using Bayesian and maximum likelihood estimation (MLE) and implemented the psychometric function to estimate the effect size. We found that the result is independent of the psychophysical method used to evaluate the effect of experimental conditions on choice performance.

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A millipede compound eye mediating low-resolution vision

Cited by 11 publications

References 26 publications

Modelling the visual world of a velvet worm

Modelling the visual world of a velvet worm

Modelling the visual world of a velvet worm

Chicken colour discrimination depends on background colour

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