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Journal ArticleDOI

Internal models of target motion: expected dynamics overrides measured kinematics in timing manual interceptions.

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TLDR
The results are in accord with the theory that motor responses evoked by visual kinematics are modulated by a prior of the target dynamics, and the prior appears surprisingly resistant to modifications based on performance errors.
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.

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Citations
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Journal ArticleDOI

Representation of Visual Gravitational Motion in the Human Vestibular Cortex

TL;DR: It is found that the vestibular network was selectively engaged when acceleration was consistent with natural gravity, demonstrating that predictive mechanisms of physical laws of motion are represented in the human brain.
Journal ArticleDOI

Widespread access to predictive models in the motor system: a short review.

TL;DR: Recent studies looking at the predictive capacity of the central nervous system reveal pervasive access to forward models of the environment.
Journal ArticleDOI

Internal models direct dragonfly interception steering

TL;DR: By simultaneously tracking the position and orientation of a dragonfly’s head and body during flight, this work provides evidence that interception steering is driven by forward and inverse models of dragonfly body dynamics and by models of prey motion.
Journal ArticleDOI

Visuo-motor coordination and internal models for object interception

TL;DR: It is shown that visual cues alone are insufficient to predict the time and place of interception or avoidance, and they need to be supplemented by prior knowledge (or internal models) about several features of the dynamic interaction with the moving object.
Journal ArticleDOI

Visual prediction: Psychophysics and neurophysiology of compensation for time delays

TL;DR: It is argued that compensation is not an exclusive property of the motor system, but rather, is a pervasive feature of the central nervous system (CNS) organization, and understanding visual prediction will inform theories of sensory processes and visual perception, and will impact the notion of visual awareness.
References
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Book

The Ecological Approach to Visual Perception

TL;DR: The relationship between Stimulation and Stimulus Information for visual perception is discussed in detail in this article, where the authors also present experimental evidence for direct perception of motion in the world and movement of the self.
Book

Handbook of perception and human performance

TL;DR: This handbook covers theory and methods; basic visual processes; auditory, kinesthetic, cutaneous, and vestibular senses; and space and motion perception; and human performance.
Journal ArticleDOI

Adaptive representation of dynamics during learning of a motor task

TL;DR: The investigation of how the CNS learns to control movements in different dynamical conditions, and how this learned behavior is represented, suggests that the elements of the adaptive process represent dynamics of a motor task in terms of the intrinsic coordinate system of the sensors and actuators.
Journal ArticleDOI

Multiple paired forward and inverse models for motor control

TL;DR: A modular approach to motor learning and control based on multiple pairs of inverse (controller) and forward (predictor) models that can simultaneously learn the multiple inverse models necessary for control as well as how to select the inverse models appropriate for a given environment is proposed.
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