Purchase this article with an account.
Shahab Bakhtiari, Asmara Awada, Christopher C. Pack; Influence of stimulus complexity on the specificity of visual perceptual learning. Journal of Vision 2020;20(6):13. doi: https://doi.org/10.1167/jov.20.6.13.
Download citation file:
© ARVO (1962-2015); The Authors (2016-present)
Although the structure and function of the human visual system are determined in large part during early development, there is ample evidence for adult plasticity as well. Such plasticity has important consequences for restoring vision after cortical damage and for improving function in healthy people. Although these applications have shown promising results, they are often limited by pathological specificity: improvements obtained through perceptual training fail to generalize beyond the trained stimulus feature or location. Efforts to reduce specificity have focused on the design of training tasks, but less is known about the effects of stimulus structure on the specificity of perceptual learning. Here, we leverage physiological findings from the dorsal visual pathway of the primate brain to explore the hypothesis that learning specificity is related to the complexity of the training stimulus. Specifically, because neurons in higher-level structures of the dorsal visual pathway exhibit little stimulus specificity, we reasoned that training with more complex stimuli would reduce the specificity of learning. We trained human observers on stimuli of varying complexity, ranging from simple sinewave gratings to complex optic flow fields. Our results show that training with more complex stimuli reduces specificity for spatial position and stimulus features. Such changes are associated with increased spatial integration. These findings were captured by a computational “reweighting” model that decoded the outputs of simulated neurons in areas middle temporal (MT) and medial superior temporal (MST) of the primate visual cortex. Our results suggest that the addition of more complex stimuli into perceptual learning paradigms provides a simple and effective way to minimize specificity in learning.
This PDF is available to Subscribers Only