Insect vision: Head saccades to reset the view

2021 ◽  
Vol 31 (18) ◽  
pp. R1072-R1074
Author(s):  
Jamie Theobald
Keyword(s):  
2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Michelle T. Fountain ◽  
Amir Badiee ◽  
Sebastian Hemer ◽  
Alvaro Delgado ◽  
Michael Mangan ◽  
...  

Abstract Spotted wing drosophila, Drosophila suzukii, is a serious invasive pest impacting the production of multiple fruit crops, including soft and stone fruits such as strawberries, raspberries and cherries. Effective control is challenging and reliant on integrated pest management which includes the use of an ever decreasing number of approved insecticides. New means to reduce the impact of this pest that can be integrated into control strategies are urgently required. In many production regions, including the UK, soft fruit are typically grown inside tunnels clad with polyethylene based materials. These can be modified to filter specific wavebands of light. We investigated whether targeted spectral modifications to cladding materials that disrupt insect vision could reduce the incidence of D. suzukii. We present a novel approach that starts from a neuroscientific investigation of insect sensory systems and ends with infield testing of new cladding materials inspired by the biological data. We show D. suzukii are predominantly sensitive to wavelengths below 405 nm (ultraviolet) and above 565 nm (orange & red) and that targeted blocking of lower wavebands (up to 430 nm) using light restricting materials reduces pest populations up to 73% in field trials.


2017 ◽  
Vol 372 (1717) ◽  
pp. 20160077 ◽  
Author(s):  
Anna Honkanen ◽  
Esa-Ville Immonen ◽  
Iikka Salmela ◽  
Kyösti Heimonen ◽  
Matti Weckström

Night vision is ultimately about extracting information from a noisy visual input. Several species of nocturnal insects exhibit complex visually guided behaviour in conditions where most animals are practically blind. The compound eyes of nocturnal insects produce strong responses to single photons and process them into meaningful neural signals, which are amplified by specialized neuroanatomical structures. While a lot is known about the light responses and the anatomical structures that promote pooling of responses to increase sensitivity, there is still a dearth of knowledge on the physiology of night vision. Retinal photoreceptors form the first bottleneck for the transfer of visual information. In this review, we cover the basics of what is known about physiological adaptations of insect photoreceptors for low-light vision. We will also discuss major enigmas of some of the functional properties of nocturnal photoreceptors, and describe recent advances in methodologies that may help to solve them and broaden the field of insect vision research to new model animals. This article is part of the themed issue ‘Vision in dim light’.


2005 ◽  
Author(s):  
R. Guzinski ◽  
K. Nguyen ◽  
Z. H. Yong ◽  
S. Rajesh ◽  
D. C. O'Carroll ◽  
...  

2017 ◽  
Vol 46 (5) ◽  
pp. 689-702 ◽  
Author(s):  
Chelsea Sabo ◽  
Robert Chisholm ◽  
Adam Petterson ◽  
Alex Cope
Keyword(s):  

2020 ◽  
Author(s):  
Manfred Hartbauer

Night active insects inspired the development of image enhancement methods that uncover the information contained in dim images or movies. Here, I describe a novel bionic night vision (NV) algorithm that operates in the spatial domain to remove noise from static images. The parameters of this NV algorithm can be automatically derived from global image statistics and a primitive type of noise estimate. In a first step, luminance values were ln-transformed, and then adaptive local means’ calculations were executed to remove the remaining noise without degrading fine image details and object contours. Its performance is comparable with several popular denoising methods and can be applied to grey-scale and color images. This novel algorithm can be executed in parallel at the level of pixels on programmable hardware.


eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Steven D Wiederman ◽  
Joseph M Fabian ◽  
James R Dunbier ◽  
David C O’Carroll

When a human catches a ball, they estimate future target location based on the current trajectory. How animals, small and large, encode such predictive processes at the single neuron level is unknown. Here we describe small target-selective neurons in predatory dragonflies that exhibit localized enhanced sensitivity for targets displaced to new locations just ahead of the prior path, with suppression elsewhere in the surround. This focused region of gain modulation is driven by predictive mechanisms, with the direction tuning shifting selectively to match the target’s prior path. It involves a large local increase in contrast gain which spreads forward after a delay (e.g. an occlusion) and can even transfer between brain hemispheres, predicting trajectories moved towards the visual midline from the other eye. The tractable nature of dragonflies for physiological experiments makes this a useful model for studying the neuronal mechanisms underlying the brain’s remarkable ability to anticipate moving stimuli.


The human visual system sees an illusory contour where there is a fault line across a regular striped pattern. We demonstrate that bees respond as if they see the same illusory contour. There is also a type of neuron in the lobula of the dragonfly optic lobe which responds directionally to motion of the illusory contour as if to an edge or line. Apparently insects have a mechanism that sees illusory contours and therefore assists in the demarcation of edges and objects at places where local contrast falls to zero at an edge, or where one textured object partially obscures another. These results suggest that insect vision, although spatially crude and low in processing power, sees separate objects by similar mechanisms to our own.


2015 ◽  
Vol 282 (1799) ◽  
pp. 20142384 ◽  
Author(s):  
Aurore Avarguès-Weber ◽  
Adrian G. Dyer ◽  
Noha Ferrah ◽  
Martin Giurfa

Traditional models of insect vision have assumed that insects are only capable of low-level analysis of local cues and are incapable of global, holistic perception. However, recent studies on honeybee ( Apis mellifera ) vision have refuted this view by showing that this insect also processes complex visual information by using spatial configurations or relational rules. In the light of these findings, we asked whether bees prioritize global configurations or local cues by setting these two levels of image analysis in competition. We trained individual free-flying honeybees to discriminate hierarchical visual stimuli within a Y-maze and tested bees with novel stimuli in which local and/or global cues were manipulated. We demonstrate that even when local information is accessible, bees prefer global information, thus relying mainly on the object's spatial configuration rather than on elemental, local information. This preference can be reversed if bees are pre-trained to discriminate isolated local cues. In this case, bees prefer the hierarchical stimuli with the local elements previously primed even if they build an incorrect global configuration. Pre-training with local cues induces a generic attentional bias towards any local elements as local information is prioritized in the test, even if the local cues used in the test are different from the pre-trained ones. Our results thus underline the plasticity of visual processing in insects and provide new insights for the comparative analysis of visual recognition in humans and animals.


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