Abstract

Neurons in the early visual cortex are finely tuned to different low-level visual features, forming a multi-channel system analysing the visual image formed on the retina in a parallel manner. However, little is known about the potential ‘cross-talk’ among these channels. Here, we systematically investigated whether stereoacuity, over a large range of target spatial frequencies, can be enhanced by perceptual learning. Using narrow-band visual stimuli, we found that practice with coarse (low spatial frequency) targets substantially improves performance, and that the improvement spreads from coarse to fine (high spatial frequency) three-dimensional perception, generalizing broadly across untrained spatial frequencies and orientations. Notably, we observed an asymmetric transfer of learning across the spatial frequency spectrum. The bandwidth of transfer was broader when training was at a high spatial frequency than at a low spatial frequency. Stereoacuity training is most beneficial when trained with fine targets. This broad transfer of stereoacuity learning contrasts with the highly specific learning reported for other basic visual functions. We also revealed strategies to boost learning outcomes ‘beyond-the-plateau’. Our investigations contribute to understanding the functional properties of the network subserving stereovision. The ability to generalize may provide a key principle for restoring impaired binocular vision in clinical situations.

Highlights

  • IntroductionStereopsis, resulting from the horizontal displacement of the two eyes (i.e. binocular disparity), adds a rich third dimension to2016 The Authors

  • Stereopsis, resulting from the horizontal displacement of the two eyes, adds a rich third dimension to2016 The Authors

  • The neural computations involved in extracting the binocular disparity information from the two monocular images are largely based on cortical processing at multiple levels [2,3]

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Summary

Introduction

Stereopsis, resulting from the horizontal displacement of the two eyes (i.e. binocular disparity), adds a rich third dimension to2016 The Authors. The neural computations involved in extracting the binocular disparity information from the two monocular images are largely based on cortical processing at multiple levels [2,3]. It appears that the neuronal mechanisms supporting stereoscopic vision are not hard-wired, but may be modifiable through experience [2,4,5]. There is still much debate about the mechanisms of perceptual learning for stereopsis and where the alternations may occur in the visual brain [15,16,17,18,19,20,21]

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