A framework for the study of vision in active observers

Abstract

We present a framework for the study of active vision, i.e., the functioning of the visual system during actively self-generated body movements. In laboratory settings, human vision is usually studied with a static observer looking at static or, at best, dynamic stimuli. In the real world, however, humans constantly move within dynamic environments. The resulting visual inputs are thus an intertwined mixture of self- and externally-generated movements. To fill this gap, we developed a virtual environment integrated with a head-tracking system in which the influence of self- and externally-generated movements can be manipulated independently. As a proof of principle, we studied perceptual stationarity of the visual world during lateral translation or rotation of the head. The movement of the visual stimulus was thus parametrically tethered to self-generated movements. We found that estimates of object stationarity were less biased and more precise during head rotation than translation. In both cases the visual stimulus had to partially follow the head movement to be perceived as immobile. We discuss a range of possibilities for our setup among which the study of shape perception in active and passive conditions, where the same optic flow is replayed to stationary observers

Bodily action penetrates affective perception

“…Each reaching session was preceded by the same calibration procedure used in Fantoni & Gerbino (2014) , and detailed in Nicolini et al (2014) . In particular, the positions of the index tip and of the eyes (viewpoint) were calculated during were calculated during the system calibration phase using three infrared-emitting diodes firmly attached on the distal phalanx and on the back of the head.…”

Grasping in absence of feedback: systematic biases endure extensive training

“…Finally, for the thumb and index finger, three diodes were placed on metal plates and fixed on the nail of each finger. This allowed to calculate the actual position of the pad of each finger (Nicolini et al 2014). Head, wrist, index and thumb movements were acquired online at 100 Hz with submillimeter resolution by using an Optotrak 3020 Certus motion capture system with two position sensors (Northern Digital Inc., Waterloo, Ontario, Canada).…”

Effect of visual and haptic feedback on grasping movements

“…To present visual stimuli in three dimensions (3D), we used a frame interlacing technique in conjunction with liquid crystal FE-1 goggles (Cambridge Research Systems, Cambridge, UK) synchronized to the monitor frame rate. A Cϩϩ program controlled stimulus presentation and response recording (Nicolini et al 2014). All experimental sessions started with the calibration procedure.…”

“…Hence, vision of the thumb was always present during the Training sessions in all experimental conditions. In a custom-built virtual reality setup (Nicolini et al 2014) we were able to selectively provide the desired combination of haptic and visual feedback.…”