ArticleFrontiers in computational neuroscience2014
Depth information in natural environments derived from optic flow by insect motion detection system: a model analysis.
Article in Frontiers in computational neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Path integration and optic flow in flying insects: a review of current evidence.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2025Review
- Optic flow based spatial vision in insects.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2023Review
- Bioinspired figure-ground discrimination via visual motion smoothing.PLoS computational biology · 2023Article
- Contrast independent biologically inspired translational optic flow estimation.Biological cybernetics · 2022Article
- Spatial tuning of translational optic flow responses in hawkmoths of varying body size.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2022Article
- Visually guided homing of bumblebees in ambiguous situations: A behavioural and modelling study.PLoS computational biology · 2020Article
- Resource-efficient bio-inspired visual processing on the hexapod walking robot HECTOR.PloS one · 2020Article
- Image statistics of the environment surrounding freely behaving hoverflies.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2019Article
- Spatial Encoding of Translational Optic Flow in Planar Scenes by Elementary Motion Detector Arrays.Scientific reports · 2018Article
- Local motion adaptation enhances the representation of spatial structure at EMD arrays.PLoS computational biology · 2017Article
- Foraging in an unsteady world: bumblebee flight performance in field-realistic turbulence.Interface focus · 2017Article
- Asymmetry of Drosophila ON and OFF motion detectors enhances real-world velocity estimation.Nature neuroscience · 2016Article
- Peripheral Processing Facilitates Optic Flow-Based Depth Perception.Frontiers in computational neuroscience · 2016Article
- A Bio-inspired Collision Avoidance Model Based on Spatial Information Derived from Motion Detectors Leads to Common Routes.PLoS computational biology · 2015Article
- Insect-Inspired Self-Motion Estimation with Dense Flow Fields--An Adaptive Matched Filter Approach.PloS one · 2015Article
- Influence of environmental information in natural scenes and the effects of motion adaptation on a fly motion-sensitive neuron during simulated flight.Biology open · 2014Article
- Temporal statistics of natural image sequences generated by movements with insect flight characteristics.PloS one · 2014Article
- Motion as a source of environmental information: a fresh view on biological motion computation by insect brains.Frontiers in neural circuits · 2014Review
- Visual motion-sensitive neurons in the bumblebee brain convey information about landmarks during a navigational task.Frontiers in behavioral neuroscience · 2014Article
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3 authors.
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Abstract
Knowing the depth structure of the environment is crucial for moving animals in many behavioral contexts, such as collision avoidance, targeting objects, or spatial navigation. An important source of depth information is motion parallax. This powerful cue is generated on the eyes during translatory self-motion with the retinal images of nearby objects moving faster than those of distant ones. To investigate how the visual motion pathway represents motion-based depth information we analyzed its responses to image sequences recorded in natural cluttered environments with a wide range of depth structures. The analysis was done on the basis of an experimentally validated model of the visual motion pathway of insects, with its core elements being correlation-type elementary motion detectors (EMDs). It is the key result of our analysis that the absolute EMD responses, i.e., the motion energy profile, represent the contrast-weighted nearness of environmental structures during translatory self-motion at a roughly constant velocity. In other words, the output of the EMD array highlights contours of nearby objects. This conclusion is largely independent of the scale over which EMDs are spatially pooled and was corroborated by scrutinizing the motion energy profile after eliminating the depth structure from the natural image sequences. Hence, the well-established dependence of correlation-type EMDs on both velocity and textural properties of motion stimuli appears to be advantageous for representing behaviorally relevant information about the environment in a computationally parsimonious way.
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