Filling gaps in visual motion for target capture

Abstract

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.

The common rate control account of prediction motion

“…During position PM, the brain probably forms a continuously changing estimate of target position, which is updated at the right speed (Bosco et al, 2015). The eyes attempt to keep up with estimated target position, sometimes falling behind then jumping ahead de Xivry et al, 2006).…”

“…Tracking is influenced the predictable effects of gravity and characteristic object motions learned on previous trials (Bosco, Delle Monache, & Lacquaniti, 2012). It seems that the eyes are guided by naturalistic, time-varying representation of occluded moving objects (Bosco et al, 2015). Are the brain networks that construct these smart motion gestalts and time-varying representations part of the oculomotor system or not?…”

“…2. Bosco et al (2015) recently published an excellent review of PM work. They plausibly conclude that the brain can continuously update a dynamic representation of occluded moving targets, incorporating both higher-order information about target kinematics (e.g.…”

Earth-Gravity Congruent Motion Benefits Visual Gain For Parabolic Trajectories

“…Moreover, to our knowledge, this is the first time a continuous, quantitative effect of an internal model of gravity has been shown. Studies have generally focused on comparing 1g to 0g or -1g motion to tease out the impact of our knowledge of gravity (Bosco et al, 2015;La Scaleia, Zago, & Lacquaniti, 2015;McIntyre et al, 2003;Zago, Iosa, Maffei, & Lacquaniti, 2010). By analyzing the effect across a range of values (0.7/0.85/1/1.15/1.3g), we add an understanding of how our internalized representation of 1g affects coincidence timing across a range of gravity values.…”

Simultaneous mental updating in physical space and number space

“…Perhaps mindful of scientific funding priorities in the early cold war era, Gottsdanker [18] implied that this prediction-motion research would help anti-aircraft gunners track enemy warplanes flying behind clouds. More recently, studies have focused on the neurocognitive mechanisms that underpin prediction-motion, as well as documenting several additional influences on performance [19][20][21][22][23][24][25][26][27][28][29]. attempted to synthesise the fragmented prediction-motion literature.…”