Neural mechanisms for integrating time and visual velocity cues in a prediction motion task: An fNIRS study

Abstract

AbstractHuman beings use accurate estimates of the time‐to‐collision of moving objects effortlessly in everyday life. In the laboratory, researchers typically apply prediction motion (PM) tasks to investigate motion processing. In the PM tasks, time structure refers to the ratio of travel time between the visible segment (first segment) and occluded segment (second segment). The condition of T = 1.0, which indicates that the time spent moving is the same across the two segments, is called equal time structure. The present study investigated the neural mechanisms of time and visual velocity information in prediction motion using functional near‐infrared spectroscopy (fNIRS). Experiment 1 showed that when visual velocity was not available, participants performed better in equal time structure conditions than in unequal time structure conditions. Moreover, the left inferior parietal lobe (IPL) showed higher activation under equal time structure conditions. Experiment 2 showed that participants also performed better in equal time structure conditions when visual velocity was available. Both the left IPL and superior parietal lobe (SPL) exhibited stronger activation under equal time structure conditions in Experiment 2. A comparison between the two experiments showed that participants integrated time structure and visual velocity to estimate arrival time of the moving object. The fNIRS data indicated that the left SPL could be involved in information integration when judging arrival time.