Image statistics and their processing in insect vision

Dyakova, Olga; Nordström, Karin

doi:10.1016/j.cois.2017.08.002

Cited by 21 publications

(21 citation statements)

References 69 publications

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“…Surprisingly, we found that the slope constant of the photos of the ground over which the hoverflies were flying was strikingly low, with a mean of 0.78 (Fig. 2 c), much lower than what is normally reported for natural scenes (e.g., Tolhurst et al 1992 ; Dyakova and Nordström 2017 ). Close-up photos often have higher slope constants (Graham and Redies 2010 ), but this does not explain our finding as the photos of the ground over which hoverflies were hovering, taken from the same height, had more typical slope constants (mean of 1.06, blue data, Fig.…”

Section: Discussioncontrasting

confidence: 67%

“…Extracting alpha may be particularly difficult at low frequencies. We extracted alpha between 0.1 and 1 cpd, as this is most consistent with the literature and with the hoverfly optics (for justification, see Dyakova and Nordström 2017 ), thus avoiding the low-frequency part of the spectrum. However, a closer inspection of the amplitude spectra suggests that whereas the slope for the hovering photos remains similar up to about 6 cpd, the slopes for the flying images depend on the part of the spectrum examined (Figs.…”

Section: Discussionmentioning

confidence: 80%

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Image statistics of the environment surrounding freely behaving hoverflies

et al. 2019

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Natural scenes are not as random as they might appear, but are constrained in both space and time. The 2-dimensional spatial constraints can be described by quantifying the image statistics of photographs. Human observers perceive images with naturalistic image statistics as more pleasant to view, and both fly and vertebrate peripheral and higher order visual neurons are tuned to naturalistic image statistics. However, for a given animal, what is natural differs depending on the behavior, and even if we have a broad understanding of image statistics, we know less about the scenes relevant for particular behaviors. To mitigate this, we here investigate the image statistics surrounding Episyrphus balteatus hoverflies, where the males hover in sun shafts created by surrounding trees, producing a rich and dense background texture and also intricate shadow patterns on the ground. We quantified the image statistics of photographs of the ground and the surrounding panorama, as the ventral and lateral visual field is particularly important for visual flight control, and found differences in spatial statistics in photos where the hoverflies were hovering compared to where they were flying. Our results can, in the future, be used to create more naturalistic stimuli for experimenter-controlled experiments in the laboratory.

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Section: Discussioncontrasting

confidence: 67%

Section: Discussionmentioning

confidence: 80%

Image statistics of the environment surrounding freely behaving hoverflies

et al. 2019

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“…For target–background experiments in both Eristalis and Holcocephala , we used an artificially generated naturalistic background pattern with a slope constant (α) of the amplitude spectrum and rms contrast close to those of natural scenes (Dyakova and Nordström, 2017). To generate this background pattern, we used the fact that the spatial statistics of an image can be quantified by constructing a fast Fourier transform and plotting the rotationally averaged amplitude as a function of spatial frequency (Tolhurst et al, 1992).…”

Section: Methodsmentioning

confidence: 99%

Integration of Small- and Wide-Field Visual Features in Target-Selective Descending Neurons of both Predatory and Nonpredatory Dipterans

et al. 2018

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For many animals, target motion carries high ecological significance as this may be generated by a predator, prey, or potential mate. Indeed, animals whose survival depends on early target detection are often equipped with a sharply tuned visual system, yielding robust performance in challenging conditions. For example, many fast-flying insects use visual cues for identifying targets, such as prey (e.g., predatory dragonflies and robberflies) or conspecifics (e.g., nonpredatory hoverflies), and can often do so against self-generated background optic flow. Supporting these behaviors, the optic lobes of insects that pursue targets harbor neurons that respond robustly to the motion of small moving objects, even when displayed against syn-directional background clutter. However, in diptera, the encoding of target information by the descending neurons, which are more directly involved in generating the behavioral output, has received less attention. We characterized target-selective neurons by recording in the ventral nerve cord of male and female predatory Holcocephala fusca robberflies and of male nonpredatory Eristalis tenax hoverflies. We show that both species have dipteran target-selective descending neurons that only respond to target motion if the background is stationary or moving slowly, moves in the opposite direction, or has un-naturalistic spatial characteristics. The response to the target is suppressed when background and target move at similar velocities, which is strikingly different to the response of target neurons in the optic lobes. As the neurons we recorded from are premotor, our findings affect our interpretation of the neurophysiology underlying target-tracking behaviors.SIGNIFICANCE STATEMENT Many animals use sensory cues to detect moving targets that may represent predators, prey, or conspecifics. For example, birds of prey show superb sensitivity to the motion of small prey, and intercept these at high speeds. In a similar manner, predatory insects visually track moving prey, often against cluttered backgrounds. Accompanying this behavior, the brains of insects that pursue targets contain neurons that respond exclusively to target motion. We here show that dipteran insects also have target-selective descending neurons in the part of their nervous system that corresponds to the vertebrate spinal cord. Surprisingly, and in contrast to the neurons in the brain, these premotor neurons are inhibited by background patterns moving in the same direction as the target.

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“…This relationship allows us to describe a large two-dimensional amplitude spectrum with a single value (alpha) referred to as the slope constant (Dyakova & Nordström, 2017;Field & Brady, 1997), facilitating comparisons between images (Graham & Field, 2007;Pouli, Cunningham, & Reinhard, 2011;Redies, Hasenstein, & Denzler, 2007;Tolhurst et al, 1992;Torralba & Oliva, 2003).…”

Section: Introductionmentioning

confidence: 99%

“…However, even among images obtained from similar distances, the slope constant may vary: photos of fields, clouds and coasts have higher slope constants, with more signatures in the lower spatial frequencies, whereas photos of mountains or forests have lower slope constants, with more signatures in the higher frequencies (Torralba & Oliva, ). Nevertheless, the slope constants across a range of natural scenes have been found to typically be close to 1–1.2 (Dyakova & Nordström, ; Tolhurst et al., ).…”

Section: Introductionmentioning

confidence: 99%

Acute sleep loss induces signs of visual discomfort in young men

Dyakova

Rångtell

Tan

et al. 2019

Journal of Sleep Research

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Acute sleep loss influences visual processes in humans, such as recognizing facial emotions. However, to the best of our knowledge, no study till date has examined whether acute sleep loss alters visual comfort when looking at images. One image statistic that can be used to investigate the level of visual comfort experienced under visual encoding is the slope of the amplitude spectrum, also referred to as the slope constant. The slope constant describes the spatial distribution of pixel intensities and deviations from the natural slope constant can induce visual discomfort. In the present counterbalanced crossover design study, 11 young men with normal or corrected‐to‐normal vision participated in two experimental conditions: one night of sleep loss and one night of sleep. In the morning after each intervention, subjects performed a computerized psychophysics task. Specifically, they were required to adjust the slope constant of images depicting natural landscapes and close‐ups with a randomly chosen initial slope constant until they perceived each image as most natural looking. Subjects also rated the pleasantness of each selected image. Our analysis showed that following sleep loss, higher slope constants were perceived as most natural looking when viewing images of natural landscapes. Images with a higher slope constant are generally perceived as blurrier. The selected images were also rated as less pleasant after sleep loss. No such differences between the experimental conditions were noted for images of close‐ups. The results suggest that sleep loss induces signs of visual discomfort in young men. Possible implications of these findings are discussed.

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Image statistics and their processing in insect vision

Cited by 21 publications

References 69 publications

Image statistics of the environment surrounding freely behaving hoverflies

Image statistics of the environment surrounding freely behaving hoverflies

Integration of Small- and Wide-Field Visual Features in Target-Selective Descending Neurons of both Predatory and Nonpredatory Dipterans

Acute sleep loss induces signs of visual discomfort in young men

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