Motion as a source of environmental information: a fresh view on biological motion computation by insect brains

Abstract

Despite their miniature brains insects, such as flies, bees and wasps, are able to navigate by highly erobatic flight maneuvers in cluttered environments. They rely on spatial information that is contained in the retinal motion patterns induced on the eyes while moving around (“optic flow”) to accomplish their extraordinary performance. Thereby, they employ an active flight and gaze strategy that separates rapid saccade-like turns from translatory flight phases where the gaze direction is kept largely constant. This behavioral strategy facilitates the processing of environmental information, because information about the distance of the animal to objects in the environment is only contained in the optic flow generated by translatory motion. However, motion detectors as are widespread in biological systems do not represent veridically the velocity of the optic flow vectors, but also reflect textural information about the environment. This characteristic has often been regarded as a limitation of a biological motion detection mechanism. In contrast, we conclude from analyses challenging insect movement detectors with image flow as generated during translatory locomotion through cluttered natural environments that this mechanism represents the contours of nearby objects. Contrast borders are a main carrier of functionally relevant object information in artificial and natural sceneries. The motion detection system thus segregates in a computationally parsimonious way the environment into behaviorally relevant nearby objects and—in many behavioral contexts—less relevant distant structures. Hence, by making use of an active flight and gaze strategy, insects are capable of performing extraordinarily well even with a computationally simple motion detection mechanism.

Learning steers the ontogeny of an efficient hunting sequence in zebrafish larvae

“…During larva bouts of forward motion, parallax can provide a measure of prey distance that can be readout through the speed that the prey image is translated across the retina. Such active sensing techniques are employed by insects that have been reported to move in particular angles to objects in order to generate optic flow and discern their proximity [18]. Generally off-axis approach strategies can extend beyond vision and may represent navigational trade-offs.…”

A Bio-Inspired Model for Visual Collision Avoidance on a Hexapod Walking Robot

“…EMDs have previously been accounted for playing a key role in the processing of visual motion information in insects [3]. As could be shown, although the responses of EMDs to visual motion are entangled with the textural properties of the environment [5], the relative nearness information obtained from optic flow estimation via EMDs is sufficient to direct HECTOR to a goal location in cluttered environments without colliding with obstacles. This holds true either for artificially generated environments as well as for a reconstructed natural environment, which substantially differ in their textural pattern properties.…”

“…A characteristic property of EMDs is that the output does not exclusively depend on velocity, but also on the pattern properties of a moving stimulus, such as its contrast and spatial frequency content. Hence, nearness information can not be extracted unambiguously from EMD responses [5]. Rather, the responses of EMDs to pure translational optic flow have been concluded to resemble a representation of the relative contrast-weighted nearness to objects in the environment, or, in other words, of the contours of nearby objects [18].…”

AVDM: Angular Velocity Decoding Model Accounting for Visually Guided Flight Behaviours of the Bee

“…17 The angular velocity here is defined by the angular displacement ∆φ of the image 18 motion in a small time interval ∆t, that is ω = ∆φ ∆t . In tunnel centring and terrain 19 following scenarios, denoting v x as the forward flight speed and d as the distance to the 20 surface, the angular velocity of image motion perceived by retina can also be expressed 21 as ω = vx d . If the forward speed is maintained by a suitable constant forward thrust, 22 then the distance to the surface will change automatically either by balancing the 23 lateral angular velocities on both sides in tunnel centring, or by regulating the ventral 24 angular velocity to a constant value in terrain following.…”

“…It's also one of the reasons why their models do not perform 61 well when the angular velocity of the moving grating is low or high. This inspires us to 62 build up a model without using the ratio of two channels, but to combine the spatial 63 and temporal information from the moving gratings, based on the assumption that there 64 are mechanisms combining both environmental texture and optic flow information in 65 insect brains [21,22].…”