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

Abstract

<p>Decoding the direction of translating objects in front of cluttered moving backgrounds, accurately and ef?ciently, is still a challenging problem. In nature, lightweight and low-powered ?ying insects apply motion vision to detect a moving target in highly variable environments during ?ight, which are excellent paradigms to learn motion perception strategies. This paper investigates the fruit ?y Drosophila motion vision pathways and presents computational modelling based on cuttingedge physiological researches. The proposed visual system model features bio-plausible ON and OFF pathways, wide-?eld 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 principalfeaturesofmotionperceptionneuralcircuits,inafeed-forwardmanner;(2)italsoshowsrobustdirectionselectivity to translating objects in front of cluttered moving backgrounds, via the modelling of spatiotemporal dynamics including combination of motion pre-?ltering 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 ornegativeoutputindicatingpreferred-direction or null-direction translation.The experiments have veri?ed 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.</p>

Topics & Concepts