Skip to main content
Dryad

Regional effect of visual clutter

Cite this dataset

Theobald, Jamie; Ruiz, Carlos (2020). Regional effect of visual clutter [Dataset]. Dryad. https://doi.org/10.5061/dryad.vx0k6djq7

Abstract

Stabilizing responses to disturbances are a critical part of the flight control system in flies. While strongly mediated by mechanoreception, much of the final steering response results from the wide field motion detection system associated with vision. The accuracy of the optomotor responses is affected when the characteristics of the visual input exceed the dynamic range of the motion detecting system. This has been demonstrated for stimulus parameters such as contrast, brightness, velocity, and spatial and temporal frequencies in gratings, but less is known about the effect of variables in more complex moving stimuli. By presenting laterally-moving dotfields of different densities we found that, in Drosophila melanogaster, the amplitude of the optomotor response is significantly affected by the level of visual clutter in the stimulus. Flies countersteer strongly within a relatively low and narrow range of element densities. But this effect is exclusive to the ventral region of the eye, and dorsal stimuli elicit an unaltered and stereotypical response throughout levels of visual clutter. This highlights local specialization of the eye and suggests the lower region may play a more critical role in translational flight-stabilization.

Methods

We recorded the steering responses of Drosophila melanogaster when presented with ventral and dorsal visual stimuli in a rigid tether virtual arena. Tethered flies were illuminated from above with an infrared light, while photodiodes below measured the shadow produced by each wing beat. Since flies steer by changing the relative amplitudes of left and right wing beats, attempts to turn produce a differential voltage by the sensor pair, and is reported as the voltage difference in wing beat amplitude, ΔWBA. This information is saved in a binary file per experiment and per fly. The data stored here has not been processed. We provide a Python code that can be used to read it, analyze it and reproduce the figures we present in our paper.

Usage notes

The files are compressed as a zip file. Once unpacked they provide the file structure required by the script to read them. Feel free to contact C. Ruiz if you have any questions regarding the dataset.

The analysis is written as a Python script that can be called from the command line or imported using an interpreter such as Spyder. It is necessary to have Python installed already in the system and some basic packages. Follow these instructions in order to generate the plots used to compose the figures in the paper and examine the data:

Unpack the compressed ZIP file preserving the folder structure.

Open a terminal window or an interpreter such as Spyder and run the code
The code will load the binary files that contain the WVA values, process the data and generate the plots presented in the manuscript for publication. It will also show some lines of text at the end offering the results of the statisticts tests ran on the data.

Funding

National Science Foundation, Award: IOS-1750833