ArticlePLoS computational biology2016
A Model for an Angular Velocity-Tuned Motion Detector Accounting for Deviations in the Corridor-Centering Response of the Bee.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- A Computationally Efficient Neuronal Model for Collision Detection with Contrast Polarity-Specific Feed-Forward Inhibition.Biomimetics (Basel, Switzerland) · 2024Article
- Finding the gap: neuromorphic motion-vision in dense environments.Nature communications · 2024Article
- Modelling Drosophila motion vision pathways for decoding the direction of translating objects against cluttered moving backgrounds.Biological cybernetics · 2020Article
- Resource-efficient bio-inspired visual processing on the hexapod walking robot HECTOR.PloS one · 2020Article
- GPUs Outperform Current HPC and Neuromorphic Solutions in Terms of Speed and Energy When Simulating a Highly-Connected Cortical Model.Frontiers in neuroscience · 2018Article
- Modeling visual-based pitch, lift and speed control strategies in hoverflies.PLoS computational biology · 2018Article
- Integrating Brain and Biomechanical Models-A New Paradigm for Understanding Neuro-muscular Control.Frontiers in neuroscience · 2018Article
- A Swarm of Bee Research.PLoS biology · 2017Article
- A computational model of the integration of landmarks and motion in the insect central complex.PloS one · 2017Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We present a novel neurally based model for estimating angular velocity (AV) in the bee brain, capable of quantitatively reproducing experimental observations of visual odometry and corridor-centering in free-flying honeybees, including previously unaccounted for manipulations of behaviour. The model is fitted using electrophysiological data, and tested using behavioural data. Based on our model we suggest that the AV response can be considered as an evolutionary extension to the optomotor response. The detector is tested behaviourally in silico with the corridor-centering paradigm, where bees navigate down a corridor with gratings (square wave or sinusoidal) on the walls. When combined with an existing flight control algorithm the detector reproduces the invariance of the average flight path to the spatial frequency and contrast of the gratings, including deviations from perfect centering behaviour as found in the real bee's behaviour. In addition, the summed response of the detector to a unit distance movement along the corridor is constant for a large range of grating spatial frequencies, demonstrating that the detector can be used as a visual odometer.
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