Kalman filtering naturally accounts for visually guided and predictive smooth pursuit dynamics.

The brain makes use of noisy sensory inputs to produce eye, head, or arm motion. In most instances, the brain combines this sensory information with predictions about future events. Here, we propose that Kalman filtering can account for the dynamics of both visually guided and predictive motor behaviors within one simple unifying mechanism.

Dramatic impairment of prediction due to frontal lobe degeneration.

Prediction is essential for motor function in everyday life. For instance, predictive mechanisms improve the perception of a moving target by increasing eye speed anticipatively, thus reducing motion blur on the retina. Subregions of the frontal lobes play a key role in eye movements in general and in smooth pursuit in particular, but their precise function is not firmly established.

Biological motion influences the visuomotor transformation for smooth pursuit eye movements.

Humans are very sensitive to the presence of other living persons or animals in their surrounding. Human actions can readily be perceived, even in a noisy environment. We recently demonstrated that biological motion, which schematically represents human motion, influences smooth pursuit eye movements during the initiation period (Orban de Xivry, Coppe, Lefèvre, & Missal, 2010).

Biological motion drives perception and action.

Presenting a few dots moving coherently on a screen can yield to the perception of human motion. This perception is based on a specific network that is segregated from the traditional motion perception network and that includes the superior temporal sulcus (STS). In this study, we investigate whether this biological motion perception network could influence the smooth pursuit response evoked by a point-light walker.