Modelling Drosophila motion vision pathways for decoding the direction of translating objects against cluttered moving backgrounds

Qinbing Fu,Shigang Yue

doi:10.1007/s00422-020-00841-x

Abstract

Decoding the direction of translating objects in front of cluttered moving backgrounds, accurately and efficiently, is still a challenging problem. In nature, lightweight and low-powered flying insects apply motion vision to detect a moving target in highly variable environments during flight, which are excellent paradigms to learn motion perception strategies. This paper investigates the fruit fly Drosophila motion vision pathways and presents computational modelling based on cutting-edge physiological researches. The proposed visual system model features bio-plausible ON and OFF pathways, wide-field horizontal-sensitive (HS) and vertical-sensitive (VS) systems. The main contributions of this research are on two aspects: (1) the proposed model articulates the forming of both direction-selective and direction-opponent responses, revealed as principal features of motion perception neural circuits, in a feed-forward manner; (2) it also shows robust direction selectivity to translating objects in front of cluttered moving backgrounds, via the modelling of spatiotemporal dynamics including combination of motion pre-filtering mechanisms and ensembles of local correlators inside both the ON and OFF pathways, which works effectively to suppress irrelevant background motion or distractors, and to improve the dynamic response. Accordingly, the direction of translating objects is decoded as global responses of both the HS and VS systems with positive or negative output indicating preferred-direction or null-direction translation. The experiments have verified the effectiveness of the proposed neural system model, and demonstrated its responsive preference to faster-moving, higher-contrast and larger-size targets embedded in cluttered moving backgrounds.

Highlights

We concisely review the related works in the areas of (1) a few categories of motion-sensitive neural models inspired by flying insects, (2) physiological research on the Drosophila motion vision pathways, (3) different combinations of the elementary motion detector (EMD) in the ON and OFF channels
This paper presents computational modelling of the Drosophila motion vision pathways accounting for how the flies decode the direction of a moving target in front of highly variable backgrounds
The emphasis is laid behind the optic flow (OF) level: the proposed model mimics the visual processing from the photoreceptors, through the parallel ON and OFF pathways, to the LPTCs in four stratified sub-layers sensitive to motion in four cardinal directions

Summary

Introduction

For the vast majority of animal species, a critically important feature of visual systems is the perception and analysis of motion that serves a wealth of daily tasks for animals (Borst and Euler 2011; Borst and Helmstaedter 2015). Direction-selective neurons, with responsive preference to specific directional visual motion, have been identified in flying insects, like locusts (Rind 1990) and flies (Borst and Euler 2011). Each group of the direction selective neurons responds selectively to a specific optic flow (OF)-field representing the spatial distribution of motion vectors on the field of vision. The visual motion cues as feedback signals provided by such neurons are applied for ego-motion control of flying insects

Results

Discussion

Conclusion