Internal Models of Target Motion: Expected Dynamics Overrides Measured Kinematics in Timing Manual Interceptions

Abstract

Prevailing views on how we time the interception of a moving object assume that the visual inputs are informationally sufficient to estimate the time-to-contact from the object's kinematics. Here we present evidence in favor of a different view: the brain makes the best estimate about target motion based on measured kinematics and an a priori guess about the causes of motion. According to this theory, a predictive model is used to extrapolate time-to-contact from expected dynamics (kinetics). We projected a virtual target moving vertically downward on a wide screen with different randomized laws of motion. In the first series of experiments, subjects were asked to intercept this target by punching a real ball that fell hidden behind the screen and arrived in synchrony with the visual target. Subjects systematically timed their motor responses consistent with the assumption of gravity effects on an object's mass, even when the visual target did not accelerate. With training, the gravity model was not switched off but adapted to nonaccelerating targets by shifting the time of motor activation. In the second series of experiments, there was no real ball falling behind the screen. Instead the subjects were required to intercept the visual target by clicking a mousebutton. In this case, subjects timed their responses consistent with the assumption of uniform motion in the absence of forces, even when the target actually accelerated. Overall, the results are in accord with the theory that motor responses evoked by visual kinematics are modulated by a prior of the target dynamics. The prior appears surprisingly resistant to modifications based on performance errors.

Adaptations of lateral hand movements to early and late visual occlusion in catching

“…The velocity gain may be more relevant when velocity signals are present (i.e., gain modulation of an absent signal is meaningless), while ED may be used to account for known acceleration levels, such as gravity (Lacquaniti and Maioli 1989;Indovina et al 2005;McIntyre et al 2001;Zago et al 2004Zago et al , 2005Zago et al , 2008 to fill in for absent visual information. The small leftward bias during the no occlusion block points to a more appropriate x vel and/or ED than during the late occlusion block and than during the randomized presentation (for which they apparently were too low, yielding a larger leftward bias).…”

Different Physical Intuitions Exist Between Tasks, Not Domains

“…However, it is unclear whether these representational momentum phenomena arise from object dynamics or from perceptual biases (Kerzel 2002), and therefore these findings may not be applicable to our implicit physical reasoning. Zago et al (2004) additionally suggest that our perceptual predictions do not account for gravity because people's timing to press a button in response to a falling ball passing a marker appeared to be unaffected by gravitational acceleration. Here we did not measure when participants believed that the ball might hit the bucket, which might suggest that the timing estimates in physical prediction could be distorted compared to reality.…”

“…Most research has instead focused on conceptual descriptions of how gravity influences falling objects (Shanon 1976) or how objects accelerate during their trajectory (Hecht and Bertamini 2000). While Zago et al (2004) suggest that people fail to account for gravitational acceleration in prediction, this only implies that non-physical models should predict that the ball will travel in a straight line. This account does not predict, however, the direction in which the ball should move when released.…”

“…For instance, Zago and Lacquaniti (2005) further differentiate between perceptual knowledge and motor knowledge, suggesting that we rely on different cognitive systems for, e.g., determining when a falling ball will cross a line versus catching that ball at the same point (Zago et al 2004). This is similar to the visuomotor control literature that shows that the motor system is not biased by the same illusions that affect perception (e.g., Aglioti et al 1995), suggesting a distinction between Bvision for perception^and Bvision for action ( Glover 2004;Goodale and Milner 1992).…”

“…Similarly, there may be a distinction between Bphysics for perception^and Bphysics for action,^where motor control for, e.g., grasping moving objects relies on a separate cognitive system (Zago et al 2004). The experiments in this paper involved interacting with the objects via a computer mouse rather than directly manipulating them and so would rely on a perceptual system according to this distinction; however, it will be important in future work to map out whether there is a shared or different intuitive physics engines for perception and action.…”