Dynamic Signal Compression for Robust Motion Vision in Flies

Drews, Michael S.; Leonhardt, Aljoscha; Pirogova, Nadezhda; Richter, Florian G.; Schuetzenberger, Anna; Braun, Lukas; Serbe, Etienne und Borst, Alexander (2020): Dynamic Signal Compression for Robust Motion Vision in Flies. In: Current Biology, Bd. 30, Nr. 2: S. 209-221

Abstract

Sensory systems need to reliably extract information from highly variable natural signals. Flies, for instance, use optic flow to guide their course and are remarkably adept at estimating image velocity regardless of image statistics. Current circuit models, however, cannot account for this robustness. Here, we demonstrate that the Drosophila visual system reduces input variability by rapidly adjusting its sensitivity to local contrast conditions. We exhaustively map functional properties of neurons in the motion detection circuit and find that local responses are compressed by surround contrast. The compressive signal is fast, integrates spatially, and derives from neural feedback. Training convolutional neural networks on estimating the velocity of natural stimuli shows that this dynamic signal compression can close the performance gap between model and organism. Overall, our work represents a comprehensive mechanistic account of how neural systems attain the robustness to carry out survival-critical tasks in challenging real-world environments.

• Dokumententyp: Zeitschriftenartikel
• Fakultätsübergreifende Einrichtungen: Graduate School of Systemic Neurosciences (GSN)
• Themengebiete: 500 Naturwissenschaften und Mathematik > 500 Naturwissenschaften
• ISSN: 0960-9822
• Sprache: Englisch