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Updated: May 27, 2026

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss
Published on: April 11, 2025
Co-learning analysis of two perceptual learning tasks with identical input stimuli supports the reweighting
Chang-Bing Huang1, Zhong-Lin Lu, Barbara A Dosher
1Laboratory of Brain Processes (LOBES), Departments of Psychology, University of Southern California, Los Angeles, CA 90089, USA.
Abstract:
Perceptual learning, even when it exhibits significant specificity to basic stimulus features such as retinal location or spatial frequency, may cause discrimination performance to improve either through enhancement of early sensory representations or through selective re-weighting of connections from the sensory representations to specific responses, or both. For most experiments in the literature, the two forms of plasticity make similar predictions (Dosher & Lu, 2009; Petrov, Dosher, & Lu, 2005). The strongest test of the two hypotheses must use training and transfer tasks that rely on the same sensory representation with different task-dependent decision structures. If training changes sensory representations, transfer (or interference) must occur since the (changed) sensory representations are common. If instead training re-weights a separate set of task connections to decision, then performance in the two tasks may still be independent. Here, we performed a co-learning analysis of two perceptual learning tasks based on identical input stimuli, following a very interesting study of Fahle and Morgan (1996) who used nearly identical input stimuli (a three dot pattern) in training bisection and vernier tasks. Two important modifications were made: (1) identical input stimuli were used in the two tasks, and (2) subjects practiced both tasks in multiple alternating blocks (800 trials/block). Two groups of subjects with counter-balanced order of training participated in the experiments. We found significant and independent learning of the two tasks. The pattern of results is consistent with the reweighting hypothesis of perceptual learning.
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