Fast prediction in marmoset reach-to-grasp movements for dynamic prey

biorxiv(2022)

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摘要
Primates have evolved sophisticated visually guided reaching behaviors for interacting with dynamic objects, such as insects during foraging. Reaching control in dynamic natural conditions requires active prediction of the target's future position in order to compensate for visuo-motor processing delays and enhance online movement adjustments. Past reaching research in non-human primates mainly focused on seated subjects engaged in repeated ballistic arm movements to either stationary targets, or targets that step once during the movement. However, those highly constrained approaches also impose task constraints that limit the natural dynamics of reaching. A recent field study in marmoset monkeys highlights predictive aspects of visually-guided reaching during insect prey capture among wild marmoset monkeys (Ngo et. al. 2022). To examine the complementary dynamics for similar natural behavior within a laboratory context we developed an ecologically motivated unrestrained reach-to-grasp task involving live crickets. We used multiple high-speed video cameras to capture the movements of marmosets and crickets stereoscopically and applied machine vision algorithms for marker-free object and hand tracking. Contrary to estimates under traditional constrained reaching paradigms, we find that prediction for dynamic targets can operate at incredibly short visuo-motor delays, rivaling the speeds that are typical of the oculomotor systems during closed-loop visual pursuit. Multivariate linear regression modeling of the kinematic relationships between the hand and cricket velocity revealed a visuo-motor delay below 100ms. Predictive corrections for moving crickets were incorporated into hand motion especially during the latter stage of the reach-to-grasp trajectory. This approach reveals that the marmoset motor system for reaching can operate at short visuo-motor delays comparable to the oculomotor system under natural dynamic conditions. ### Competing Interest Statement The authors have declared no competing interest.
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fast prediction,reach-to-grasp
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