Integration of Position and Predictive Motion Signals in Aging Vision

Abstract

We examined the effect of aging on the integration of position and motion signals, which is essential for tracking visual objects, using the motion-induced position shift (MIPS) phenomenon. We first measured the MIPS and bias in speed perception at three eccentricities. Both young and older adults showed the increasing MIPS and decreasing perceived speed as the eccentricity increased, which is consistent with previous literature. More importantly, we found that the mean MIPS was 2.87 times larger in older adults, and the response variability in position tasks showed a larger difference between age groups compared with the difference in speed tasks. We then measured the MIPS across stimulus durations. Temporal changes in the MIPS showed similar patterns in young and older adults in that the MIPS initially peaked at around 60 ms and approached an asymptote. We further analyzed the changes in response variability across stimulus durations to estimate sensory noise and propagation noise separately and found that only sensory noise was significantly larger in older adults. The overall results suggest that the increased MIPS in older adults is due to the increased dependency on predictive motion signals to compensate for the relatively imprecise position signals, which in turn implies that older adults would depend more on the motion signals to track objects.

Exploring the Common Mechanisms of Motion-Based Visual Prediction

“…After this time point the dynamic system is essentially in a stationary mode in that the stimulus velocity and the consequent spatial shift are approximately constant as indeed will be the relationship between motion-based spatial prediction and the sensory input. We note that the magnitude of the shift can reduce at longer durations and higher speeds ( Chung et al, 2007 ; Jeon et al, 2020 ), however, this may reflect rapid motion adaptation, or better segmentation of the window from the moving carrier. The spatial jitter in MISC also implies a shift of spatial pattern, however, the shift changes too quickly to be directly measured.…”

“…Motion-based shifts are dynamic and take time to establish. MIPS increases rapidly over the first roughly 80 ms of stimulus presentation with a well-defined rate and then plateaus or reduces to some degree ( Arnold et al, 2007 ; Chung et al, 2007 ; Jeon et al, 2020 ). It is therefore natural to ask if the time to establish a spatial shift (MIPS) and the time interval at which the shift and prediction diverge significantly, thought to determine MISC frequency, are related.…”

The perceived position of a moving object is reset by temporal, not spatial limits

“…For example, the "flash-grab" illusion shows integration period of only about 80 to 100 ms (Cavanagh & Anstis, 2013). The motion drag illusion (R. L. De Valois & De Valois, 1991;Eagleman & Sejnowski, 2007) shows an increase in the perceived offset that grows with presentation duration up to 50 or 60 ms (Kosovicheva et al, 2014;Jeon et al, 2020;Chung, Patel, Bedell, & Yilmaz, 2007). Unlike these other motion-induced position shifts, the double-drift stimulus involves a second-long accumulation of position errors.…”