Prolonged perceptual learning of positional acuity in adult amblyopia: perceptual template retuning dynamics

Abstract

Amblyopia is a developmental abnormality that results in physiological alterations in the visual cortex and impairs form vision. It is often successfully treated by patching the sound eye in infants and young children, but is generally considered to be untreatable in adults. However, a number of recent studies suggest that repetitive practice of a visual task using the amblyopic eye results in improved performance in both children and adults with amblyopia. These perceptual learning studies have used relatively brief periods of practice; however, clinical studies have shown that the time-constant for successful patching is long. The time-constant for perceptual learning in amblyopia is still unknown. Here we show that the time-constant for perceptual learning depends on the degree of amblyopia. Severe amblyopia requires >50 h (approximately equal to 35,000 trials) to reach plateau, yielding as much as a five-fold improvement in performance at a rate of approximately equal to 1.5%/h. There is significant transfer of learning from the amblyopic to the dominant eye, suggesting that the learning reflects alterations in higher decision stages of processing. Using a reverse correlation technique, we document, for the first time, a dynamic retuning of the amblyopic perceptual decision template and a substantial reduction in internal spatial distortion. These results show that the mature amblyopic brain is surprisingly malleable, and point to more intensive treatment methods for amblyopia.

Figures

Figure 1.

Prolonged perceptual learning of position discrimination in adult amblyopia. A, Visual stimulus. The observers' task was to identify the location of the right test segment relative to the left reference segment. Positional noise was added to the right segment by jittering the vertical position of each of the five Gabor patches (either up or down). B, Learning profile. Each data point represents one session consisting of 960 trials in ∼1.5 h. It is worth noting that it took as many as ≈35 sessions (≈35,000 trials) to improve and reach a stable performance plateau (prolonged learning). Observer VC withdrew from the study after 19 sessions (open symbols in this and subsequent figures) and did not finish the experiment according to our end-point criterion. Gray symbols indicate the mean data of two normal observers for comparison. C, The number of hours needed to reach stable plateau performance as a function of pretraining positional threshold. D, Acuity improvement (pre/post ratio) as a function of pretraining positional threshold. The data of two children (black symbols in panels C and D) with amblyopia who underwent intensive perceptual learning are replotted here (Li et al., 2007). E, Comparison of positional acuity between the two eyes, nonamblyopic (NAE) and amblyopic (AE). The posttraining performance (filled symbols) is much closer to (or even better than) the gray 1:1 reference line. The amount of plateau improvement, as indicated by the length of colored lines, is considerably larger for those observers with much elevated baseline pretraining threshold (open symbols). F, Interocular transfer (from the trained AE to the nontrained fellow NAE) versus phase II direct training (on the previously untrained NAE). G, Improvement in visual acuity and positional acuity. The amount of improvement in visual acuity is not dependent on that in positional acuity (slope = −0.0015 ± 0.04, t = −0.04, p = 0.97).

Figure 2.

Neural mechanisms involved in learning position discrimination. A, Inset, Ideal versus human template. In human observers (n = 2), the averaging computation mostly relied on a few stimulus samples; much higher weights were given to the selected samples than to the others (red line). Following practice, the retuned template (blue line) is closer to resembling the ideal template (black line). A, The enhancement of template efficiency after perceptual learning. In four deeply amblyopic observers, the posttraining efficiency is much higher than the pretraining efficiency. Nevertheless, the other three mild amblyopes (ED, JS, and AA) did not show any significant retuning, as shown by similar pretraining and posttraining efficiency along a 1:1 reference line. B, Template retuning. A red line illustrates the pretraining template and a blue line illustrates the posttraining template instead. The retuned template is more similar to the ideal template in shape (black line). For comparison, the data of the nonamblyopic eye (NAE) is plotted as a gray line. C, Perceptual learning results in a decrease in random internal (int.) noise. It appears that the amount of decrement is directly proportional to the baseline noise level. Note that observer VC (open symbols) did not complete the experiment according to our plateau criterion.

Figure 3.

Retuning dynamics of behavioral receptive fields. A, Summary of changes in template efficiency and internal random noise. Template efficiency is expressed as post/pre ratio, while internal noise is expressed as pre/post ratio. B, Threshold components. The squared sum of all threshold components (ideal template, human template, random noise, and systematic noise) is quite close to the squared human threshold, although our modeling tends to slightly overestimate human performance, as indicated by a black line. In agreement with our earlier study with normal observers (Li et al., 2006), systematic noise (like the systematic template error, but related to a higher-order nonlinearity) is negligible in this positional task.