Perceptual learning improves contrast sensitivity,visual acuity,and foveal crowding in amblyopia

Abstract

Background:

Amblyopic observers present abnormal spatial interactions between a low-contrast sinusoidal target and high-contrast collinear flankers. It has been demonstrated that perceptual learning (PL) can modulate these low-level lateral interactions, resulting in improved visual acuity and contrast sensitivity.

Objective:

We measured the extent and duration of generalization effects to various spatial tasks (i.e., visual acuity, Vernier acuity, and foveal crowding) through PL on the target’s contrast detection.

Methods:

Amblyopic observers were trained on a contrast-detection task for a central target (i.e., a Gabor patch) flanked above and below by two high-contrast Gabor patches. The pre- and post-learning tasks included lateral interactions at different target-to-flankers separations (i.e., 2, 3, 4, 8λ) and included a range of spatial frequencies and stimulus durations as well as visual acuity, Vernier acuity, contrast-sensitivity function, and foveal crowding.

Results:

The results showed that perceptual training reduced the target’s contrast-detection thresholds more for the longest target-to-flanker separation (i.e., 8λ). We also found generalization of PL to different stimuli and tasks: contrast sensitivity for both trained and untrained spatial frequencies, visual acuity for Sloan letters, and foveal crowding, and partially for Vernier acuity. Follow-ups after 5–7 months showed not only complete maintenance of PL effects on visual acuity and contrast sensitivity function but also further improvement in these tasks.

Conclusion:

These results suggest that PL improves facilitatory lateral interactions in amblyopic observers, which usually extend over larger separations than in typical foveal vision. The improvement in these basic visual spatial operations leads to a more efficient capability of performing spatial tasks involving high levels of visual processing, possibly due to the refinement of bottom-up and top-down networks of visual areas.