Sensory uncertainty influences motor learning differently in blocked versus interleaved trial contexts when both feedforward and feedback processes are engaged

Abstract

Theories of human motor learning commonly assume that the degree to which movement plans are adjusted in response to movement errors scales with the precision of sensory feedback received regarding their success. However, support for such error-scaling models has mainly come from experiments that limit the amount of correction that can occur within an ongoing movement. In contrast, we have recently shown that when this restriction is relaxed, and both within-movement and between-movement corrections co-occur, movement plans undergo large and abrupt changes that are strongly correlated with the degree of sensory uncertainty present on the previous trial and are insensitive to the magnitude and direction of the experienced movement error. Here, we show that the presence of these abrupt and error-insensitive changes can only be reliably detected when different levels of sensory precision are interleaved pseudo randomly on a trial-by-trial basis. These results augment our earlier findings and suggest that the co-occurrence of within-movement and between-movement corrections is not the only important aspect of our earlier study that challenged the error-scaling models of motor learning under uncertainty. Author summaryA large body of literature shows that sensory uncertainty inversely scales the degree of error-driven corrections made to motor plans from one trial to the next. However, by limiting sensory feedback to the endpoint of movements, these studies prevent corrections from taking place during the movement. We have recently shown that when such corrections are promoted, sensory uncertainty punctuates between-trial movement corrections with abrupt changes that closely track the degree of sensory uncertainty but are insensitive to the magnitude and direction of movement error. Here, we show that this result requires different levels of sensory uncertainty to be mixed on a trial-by-trial basis. This carries important implications for how previous studies of motor learning under uncertainty are interpreted, and what future studies will likely constitute progress for the field.