The visual system is poorly sensitive to arbitrary accelerations, but accurately detects the effects of gravity on a target motion. Here we review behavioral and neuroimaging data about the neural mechanisms for dealing with object motion and egomotion under gravity. The results from several experiments show that the visual estimates of a target motion under gravity depend on the combination of a prior of gravity effects with on-line visual signals on target position and velocity. These estimates are affected by vestibular inputs, and are encoded in a visual-vestibular network whose core regions lie within or around the Sylvian fissure, and are represented by the posterior insula/retroinsula/temporo-parietal junction. This network responds both to target motions coherent with gravity and to vestibular caloric stimulation in human fMRI studies. Transient inactivation of the temporo-parietal junction selectively disrupts the interception of targets accelerated by gravity.

Moving and interacting with the environment require a reference for orientation and a scale for calibration in space and time. There is a wide variety of environmental clues and calibrated frames at different locales, but the reference of gravity is ubiquitous on Earth. The pull of gravity on static objects provides a plummet which, together with the horizontal plane, defines a three-dimensional Cartesian frame for visual images. On the other hand, the gravitational acceleration of falling objects can provide a time-stamp on events, because the motion duration of an object accelerated by gravity over a given path is fixed. Indeed, since ancient times, man has been using plumb bobs for spatial surveying, and water clocks or pendulum clocks for time keeping. Here we review behavioral evidence in favor of the hypothesis that the brain is endowed with mechanisms that exploit the presence of gravity to estimate the spatial orientation and the passage of time. Several visual and non-visual (vestibular, haptic, visceral) cues are merged to estimate the orientation of the visual vertical. However, the relative weight of each cue is not fixed, but depends on the specific task. Next, we show that an internal model of the effects of gravity is combined with multisensory signals to time the interception of falling objects, to time the passage through spatial landmarks during virtual navigation, to assess the duration of a gravitational motion, and to judge the naturalness of periodic motion under gravity

Gravity is crucial for spatial perception, postural equilibrium, and movement generation. The vestibular apparatus is the main sensory system involved in monitoring gravity. Hair cells in the vestibular maculae respond to gravitoinertial forces, but they cannot distinguish between linear accelerations and changes of head orientation relative to gravity. The brain deals with this sensory ambiguity (which can cause some lethal airplane accidents) by combining several cues with the otolith signals: angular velocity signals provided by the semicircular canals, proprioceptive signals from muscles and tendons, visceral signals related to gravity, and visual signals. In particular, vision provides both static and dynamic signals about body orientation relative to the vertical, but it poorly discriminates arbitrary accelerations of moving objects. However, we are able to visually detect the specific acceleration of gravity since early infancy. This ability depends on the fact that gravity effects are stored in brain regions which integrate visual, vestibular, and neck proprioceptive signals and combine this information with an internal model of gravity effects.

A remarkable challenge our brain must face constantly when interacting with the environment is represented by ambiguous and, at times, even missing sensory information. This is particularly compelling for visual information, being the main sensory system we rely upon to gather cues about the external world. It is not uncommon, for example, that objects catching our attention may disappear temporarily from view, occluded by visual obstacles in the foreground. Nevertheless, we are often able to keep our gaze on them throughout the occlusion or even catch them on the fly in the face of the transient lack of visual motion information. This implies that the brain can fill the gaps of missing sensory information by extrapolating the object motion through the occlusion. In recent years, much experimental evidence has been accumulated that both perceptual and motor processes exploit visual motion extrapolation mechanisms. Moreover, neurophysiological and neuroimaging studies have identified brain regions potentially involved in the predictive representation of the occluded target motion. Within this framework, ocular pursuit and manual interceptive behavior have proven to be useful experimental models for investigating visual extrapolation mechanisms. Studies in these fields have pointed out that visual motion extrapolation processes depend on manifold information related to short-term memory representations of the target motion before the occlusion, as well as to longer term representations derived from previous experience with the environment. We will review recent oculomotor and manual interception literature to provide up-to-date views on the neurophysiological underpinnings of visual motion extrapolation.

Two control schemes have been hypothesized for the manual interception of fast visual targets. In the model-free on-line control, extrapolation of target motion is based on continuous visual information, without resorting to physical models. In the model-based control, instead, a prior model of target motion predicts the future spatiotemporal trajectory. To distinguish between the two hypotheses in the case of projectile motion, we asked participants to hit a ball that rolled down an incline at 0.2 g and then fell in air at 1 g along a parabola. By varying starting position, ball velocity and trajectory differed between trials. Motion on the incline was always visible, whereas parabolic motion was either visible or occluded. We found that participants were equally successful at hitting the falling ball in both visible and occluded conditions. Moreover, in different trials the intersection points were distributed along the parabolic trajectories of the ball, indicating that subjects were able to extrapolate an extended segment of the target trajectory. Remarkably, this trend was observed even at the very first repetition of movements. These results are consistent with the hypothesis of model-based control, but not with on-line control. Indeed, ball path and speed during the occlusion could not be extrapolated solely from the kinematic information obtained during the preceding visible phase. The only way to extrapolate ball motion correctly during the occlusion was to assume that the ball would fall under gravity and air drag when hidden from view. Such an assumption had to be derived from prior experience.

It is known that humans tend to misjudge the kinematics of a target rolling down an inclined plane. Because visuomotor responses are often more accurate and less prone to perceptual illusions than cognitive judgments, we asked the question of how rolling motion is extrapolated for manual interception or drawing tasks. In three experiments a ball rolled down an incline with kinematics that differed as a function of the starting position (4 different positions) and slope (30°, 45° or 60°). In Experiment 1, participants had to punch the ball as it fell off the incline. In Experiment 2, the ball rolled down the incline but was stopped at the end; participants were asked to imagine that the ball kept moving and to punch it. In Experiment 3, the ball rolled down the incline and was stopped at the end; participants were asked to draw with the hand in air the trajectory that would be described by the ball if it kept moving. We found that performance was most accurate when motion of the ball was visible until interception and haptic feedback of hand-ball contact was available (Experiment 1). However, even when participants punched an imaginary moving ball (Experiment 2) or drew in air the imaginary trajectory (Experiment 3), they were able to extrapolate to some extent global aspects of the target motion, including its path, speed and arrival time. We argue that the path and kinematics of a ball rolling down an incline can be extrapolated surprisingly well by the brain using both visual information and internal models of target motion.

We have considerable knowledge about the mechanisms underlying compensation of Earth gravity during locomotion, a knowledge obtained from physiological, biomechanical, modeling, developmental, comparative, and paleoanthropological studies. By contrast, we know much less about locomotion and movement in general under sustained hypogravity. This lack of information poses a serious problem for human space exploration. In a near future humans will walk again on the Moon and for the first time on Mars. It would be important to predict how they will move around, since we know that locomotion and mobility in general may be jeopardized in hypogravity, especially when landing after a prolonged weightlessness of the space flight. The combination of muscle weakness, of wearing a cumbersome spacesuit, and of maladaptive patterns of locomotion in hypogravity significantly increase the risk of falls and injuries. Much of what we currently know about locomotion in hypogravity derives from the video archives of the Apollo missions on the Moon, the experiments performed with parabolic flight or with body weight support on Earth, and the theoretical models. These are the topics of our review, along with the issue of the application of simulated hypogravity in rehabilitation to help patients with deambulation problems. We consider several issues that are common to the field of space science and clinical rehabilitation: the general principles governing locomotion in hypogravity, the methods used to reduce gravity effects on locomotion, the extent to which the resulting behavior is comparable across different methods, the important non-linearities of several locomotor parameters as a function of the gravity reduction, the need to use multiple methods to obtain reliable results, and the need to tailor the methods individually based on the physiology and medical history of each person.

To accurately time motor responses when intercepting falling balls we rely on an internal model of gravity. However, whether and how such a model is also used to estimate the spatial location of interception is still an open question. Here we addressed this issue by asking 25 participants to intercept balls projected from a fixed location 6 m in front of them and approaching along trajectories with different arrival locations, flight durations, and gravity accelerations (0 and 1). The trajectories were displayed in an immersive virtual reality system with a wide field of view. Participants intercepted approaching balls with a racket, and they were free to choose the time and place of interception. We found that participants often achieved a better performance with 1 than 0 balls. Moreover, the interception points were distributed along the direction of a 1 path for both 1 and 0 balls. In the latter case, interceptions tended to cluster on the upper half of the racket, indicating that participants aimed at a lower position than the actual 0 path. These results suggest that an internal model of gravity was probably used in predicting the interception locations. However, we found that the difference in performance between 1 and 0 balls was modulated by flight duration, the difference being larger for faster balls. In addition, the number of peaks in the hand speed profiles increased with flight duration, suggesting that visual information was used to adjust the motor response, correcting the prediction to some extent. Here we show that an internal model of gravity plays a key role in predicting where to intercept a fast-moving target. Participants also assumed an accelerated motion when intercepting balls approaching in a virtual environment at constant velocity. We also show that the role of visual information in guiding interceptive movement increases when more time is available.