Zhong-Lin Lu

Purpose.: One critical concern about using perceptual learning to treat amblyopia is whether training with one particular stimulus and task generalizes to other stimuli and tasks. In the spatial domain, it has been found that the bandwidth of contrast sensitivity improvement is much broader in amblyopes than in normals. Because previous studies suggested the local motion deficits in amblyopia are explained by the spatial vision deficits, the hypothesis for this study was that training in the spatial domain could benefit motion perception of sinewave gratings. Methods.: Nine adult amblyopes (mean age, 22.1 ± 5.6 years) were trained in a contrast detection task in the amblyopic eye for 10 days. Visual acuity, spatial contrast sensitivity functions, and temporal modulation transfer functions (MTF) for sinewave motion detection and discrimination were measured for each eye before and after training. Eight adult amblyopes (mean age, 22.6 ± 6.7 years) served as control subjects. Results.: In the amblyopic eye, training improved (1) contrast sensitivity by 6.6 dB (or 113.8%) across spatial frequencies, with a bandwidth of 4.4 octaves; (2) sensitivity of motion detection and discrimination by 3.2 dB (or 44.5%) and 3.7 dB (or 53.1%) across temporal frequencies, with bandwidths of 3.9 and 3.1 octaves, respectively; (3) visual acuity by 3.2 dB (or 44.5%). The fellow eye also showed a small amount of improvement in contrast sensitivities and no significant change in motion perception. Control subjects who received no training demonstrated no obvious improvement in any measure. Conclusions.: The results demonstrate substantial plasticity in the amblyopic visual system, and provide additional empirical support for perceptual learning as a potential treatment for amblyopia.

Amblyopia is a developmental disorder that results in deficits of monocular and binocular vision. It is presently unclear whether these deficits result from attenuation of signals in the amblyopic eye, inhibition by signals in the fellow eye, or both. In this study, we characterize mechanisms underlying anisometropic amblyopia using a binocular phase and contrast combination paradigm and a contrast gain control model. Subjects dichoptically viewed two slightly different images and reported the perceived contrast and phase of the resulting cyclopean percept. We found that the properties of binocular combination were abnormal in many aspects in amblyopic vision. The observed abnormalities can be explained by a combination of (1) attenuated monocular signal in the amblyopic eye, (2) stronger interocular contrast gain control from the fellow eye to the signal in the amblyopic eye (direct interocular inhibition), and (3) stronger interocular contrast gain control from the fellow eye to the contrast gain control signal from the amblyopic eye (indirect interocular inhibition). We conclude that anisometropic amblyopia led to both monocular and interocular deficits. A complete understanding of the mechanisms underlying amblyopia requires studies of both monocular deficits and binocular interactions.

On the basis of results from behavioral studies that spatial attention improves the exclusion of external noise in the target region, we predicted that attending to a spatial region would reduce the impact of external noise on the BOLD response in corresponding cortical areas, seen as reduced BOLD responses in conditions with large amounts of external noise but relatively low signal, and increased dynamic range of the BOLD response to variations in signal contrast. We found that, in the presence of external noise, covert attention reduced the trial-by-trial BOLD response by 15.5–18.9% in low signal contrast conditions in V1. It also increased the BOLD dynamic range in V1, V2, V3, V3A/B, and V4 by a factor of at least three. Overall, covert attention reduced the impact of external noise by about 73–85% in these early visual areas. It also increased the contrast gain by a factor of 2.6–3.8.

How the visual system combines information from the two eyes to form a unitary binocular representation of the external world is a fundamental question in vision science that has been the focus of many psychophysical and physiological investigations. Ding & Sperling (2006) measured perceived phase of the cyclopean image, and developed a binocular combination model in which each eye exerts gain control on the other eye's signal and over the other eye's gain control. Critically, the relative phase of the monocular sine-waves plays a central role. We used the Ding-Sperling paradigm but measured both the perceived contrast and phase of cyclopean images in three hundred and eighty combinations of base contrast, interocular contrast ratio, eye origin of the probe, and interocular phase difference. We found that the perceived contrast of the cyclopean image was independent of the relative phase of the two monocular gratings, although the perceived phase depended on the relative phase and contrast ratio of the monocular images. We developed a new multi-pathway contrast-gain control model (MCM) that elaborates the Ding-Sperling binocular combination model in two ways: (1) phase and contrast of the cyclopean images are computed in separate pathways, although with shared cross-eye contrast-gain control; and (2) phase-independent local energy from the two monocular images are used in binocular contrast combination. With three free parameters, the model yielded an excellent account of data from all the experimental conditions. Binocular phase combination depends on the relative phase and contrast ratio of the monocular images but binocular contrast combination is phase-invariant. Our findings suggest the involvement of at least two separate pathways in binocular combination.

Purpose.: The qCSF method is a novel procedure for rapid measurement of spatial contrast sensitivity functions (CSFs). It combines Bayesian adaptive inference with a trial-to-trial information gain strategy, to directly estimate four parameters defining the observer's CSF. In the present study, the suitability of the qCSF method for clinical application was examined. Methods.: The qCSF method was applied to rapidly assess spatial CSFs in 10 normal and 8 amblyopic participants. The qCSF was evaluated for accuracy, precision, test–retest reliability, suitability of CSF model assumptions, and accuracy of amblyopia screening. Results.: qCSF estimates obtained with as few as 50 trials matched those obtained with 300 Ψ trials. The precision of qCSF estimates obtained with 120 and 130 trials, in normal subjects and amblyopes, matched the precision of 300 Ψ trials. For both groups and both methods, test–retest sensitivity estimates were well matched (all R > 0.94). The qCSF model assumptions were valid for 8 of 10 normal participants and all amblyopic participants. Measures of the area under log CSF (AULCSF) and the cutoff spatial frequency (cutSF) were lower in the amblyopia group; these differences were captured within 50 qCSF trials. Amblyopia was detected at an approximately 80% correct rate in 50 trials, when a logistic regression model was used with AULCSF and cutSF as predictors. Conclusions.: The qCSF method is sufficiently rapid, accurate, and precise in measuring CSFs in normal and amblyopic persons. It has great potential for clinical practice.

Feedback plays an interesting role in perceptual learning. The complex pattern of empirical results concerning the role of feedback in perceptual learning rules out both a pure supervised mode and a pure unsupervised mode of learning and leads some researchers to the proposal that feedback may change the learning rate through top-down control but does not act as a teaching signal in perceptual learning (M. H. Herzog & M. Fahle, 1998). In this study, we tested the predictions of an augmented Hebbian reweighting model (AHRM) of perceptual learning (A. Petrov, B. A. Dosher, & Z.-L. Lu, 2005), in which feedback influences the effective rate of learning by serving as an additional input and not as a direct teaching signal. We investigated the interactions between feedback and training accuracy in a Gabor orientation identification task over six training days. The accelerated stochastic approximation method was used to track threshold contrasts at particular performance accuracy levels throughout training. Subjects were divided into 4 groups: high training accuracy (85% correct) with and without feedback, and low training accuracy (65%) with and without feedback. Contrast thresholds improved in the high training accuracy condition, independent of the feedback condition. However, thresholds improved in the low training accuracy condition only in the presence of feedback but not in the absence of feedback. The results are both qualitatively and quantitatively consistent with the predictions of the augmented Hebbian learning model and are not consistent with pure supervised error correction or pure Hebbian learning models.