The time-course of prediction formation and revision in human visual motion processing

Abstract

Establishing the real-time position of a moving object poses a challenge to the visual system due to neural processing delays. While sensory information is travelling through the visual hierarchy, the object continues moving and information about its position becomes outdated. By extrapolating the position of a moving object along its trajectory, predictive mechanisms might effectively decrease the processing time associated with these objects. Here, we use time-resolved decoding of electroencephalographic (EEG) data from an apparent motion paradigm to demonstrate the interaction of two separate predictive mechanisms. First, we reveal predictive latency advantages for position representation..