Task difficulty and expertise mediate the effects of roving on perceptual performance

Abstract

Experience-dependent improvement of perception, known as perceptual learning, is possible in the absence of feedback, but feedback enables faster progress as demonstrated by both unsupervised and supervised learning mechanisms. Perceptual learning models have shown that mixing these two learning mechanisms may potentially cause synaptic drift and disruption of learning. Models predict this disruption in simultaneously learning two tasks with differing difficulty levels, but not for tasks of equal difficulty. The roving, randomly intermingling of two different tasks, has thus sometimes been found to disrupt learning, but not always. Interestingly, the deleterious effect of roving may occur not only during learning but also even after a task has been learned. In this study, we examine roving's effects based on task difficulty as a function of expertise level. Subjects were trained with a vertical line bisection task, where they were asked to decide if the central line was offset to the left or right outer lines. Following training, the trained stimulus was roved with a narrower untrained bisection stimulus; half of the subjects were exposed to the roved stimuli, which were equated for difficulty using an adaptive staircase method, while other half were exposed to stimuli made to differ in difficulty levels using different staircase procedures for each. We demonstrated that performances improved with training. Moreover, roving deteriorated performance for the trained task under mixed difficulty conditions but not under matched difficulty conditions. Training participants over multiple days further revealed that roving's deleterious effects decreased with increasing expertise levels.