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Philipp Kreyenmeier, Jolande Fooken, Miriam Spering; Similar effects of visual context dynamics on eye and hand movements. Journal of Vision 2016;16(12):457. doi: 10.1167/16.12.457.
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The perception of visual motion and the ability to track a moving target with smooth pursuit eye movements are strongly context-dependent. Despite similar processing mechanisms and pathways, visual contexts can have opposite effects on perception and pursuit (Spering & Gegenfurtner 2007; 2008): context motion in a particular direction can speed up perception but slow down pursuit, and vice versa. By contrast, here we show that visual contexts have similar effects on pursuit and hand movements. Observers (n=11) tracked a target moving across a screen and hit it with their index finger after it had entered a "hit zone". Following brief presentation (100-300 ms) along a curved trajectory, observers had to extrapolate and intercept the target at its assumed position; feedback about actual position was given after interception. The target was either presented on a uniform grey background or on a naturalistic texture (motion cloud; Leon, Vanzetta, Masson & Perrinet, 2012), which was either static or moved in the same direction and at the same mean speed as the target. We analysed background effects on the accuracy and dynamics of tracking and interception movements. Static backgrounds significantly slowed pursuit (longer latency, lower acceleration and velocity gain) and dynamic backgrounds speeded pursuit (shorter latency, higher acceleration and gain), both in response to the visible and the invisible target trajectory. Effects of similar direction and magnitude were observed for hand movement dynamics (latency). Interestingly, position errors in eye and hand (interception accuracy) were lower for static than for dynamic backgrounds, where observers' estimates of target position overshot actual end position. Similar effects of context dynamics on eye and hand movements suggest that the eye- and hand-movement systems may rely on similar sources of information for visual-motor prediction tasks.
Meeting abstract presented at VSS 2016
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