Dragonfly visual neurons selectively attend to features in naturalistic scenes
AbstractAerial predators, such as the dragonfly, determine the position and movement of their prey even when embedded in natural scenes. This task is likely supported by a group of optic lobe neurons with responses selective for moving targets of less than a few degrees. These Small Target Motion Detector (STMD) neurons are tuned to target velocity and show profound facilitation in responses to targets that move along continuous trajectories. When presented with a pair of targets, some STMDs
... petitively select one of the alternatives as if the other does not exist.Here we describe intracellular responses of STMD neurons to the visual presentation of many potential alternatives within cluttered environments comprised of natural scenes. We vary both target contrast and the background scene, across a range of target and background velocities. We find that background motion affects STMD responses indirectly, via the competitive selection of background features. We find that robust target discrimination is limited to scenarios when the target velocity is matched to, or greater than, background velocity. Furthermore, STMD target discriminability is modified by background direction. Backgrounds that move in the neuron's anti-preferred direction result in the least performance degradation.Significance StatementBiological brains solve the difficult problem of visually detecting and tracking moving features in cluttered environments. We investigated this neuronal processing by recording intracellularly from dragonfly visual neurons that encode the motion of small moving targets subtending less than a few degrees (e.g. prey and conspecifics). However, dragonflies live in a complex visual environment where background features may interfere with tracking by reducing target contrast or providing competitive cues. We find that selective attention towards features drives much of the neuronal response, with background clutter competing with target stimuli for selection. Moreover, the velocity of features is an important component in determining the winner in these competitive interactions.