Broad-based visual benefits from training with an integrated perceptual-learning video game

Abstract

Perception is the window through which we understand all information about our environment, and therefore deficits in perception due to disease, injury, stroke or aging can have significant negative impacts on individuals' lives. Research in the field of perceptual learning has demonstrated that vision can be improved in both normally seeing and visually impaired individuals, however, a limitation of most perceptual learning approaches is their emphasis on isolating particular mechanisms. In the current study, we adopted an integrative approach where the goal is not to achieve highly specific learning but instead to achieve general improvements to vision. We combined multiple perceptual learning approaches that have individually contributed to increasing the speed, magnitude and generality of learning into a perceptual-learning based video-game. Our results demonstrate broad-based benefits of vision in a healthy adult population. Transfer from the game includes; improvements in acuity (measured with self-paced standard eye-charts), improvement along the full contrast sensitivity function, and improvements in peripheral acuity and contrast thresholds. The use of this type of this custom video game framework built up from psychophysical approaches takes advantage of the benefits found from video game training while maintaining a tight link to psychophysical designs that enable understanding of mechanisms of perceptual learning and has great potential both as a scientific tool and as therapy to help improve vision.

Keywords: Applied vision; Mechanisms of learning; Perceptual learning; Vision therapy.

Copyright © 2014 Elsevier B.V. All rights reserved.

Figures

Figure 1

Game screenshot - Static search with distractors. Participants should select the targets, and ignore the distractors. As levels progress distractors will look more and more like targets. Of note, both targets and distractors are typically much lower contrast than they appear here.

Figure 2

Central acuity. Each point represents one subject in the trained group (blue) or control group (red). Values are based upon the 20/20 acuity scale.

Figure 3

Contrast Sensitivity Function. Average CSF on pretest (blue) and posttest (red) for experimental (A) and control group (B). Error bars represent within subject standard error. C, scatter plot of average of log (CSF) where, each point represents one subject in the trained group (blue) or control group (red).

Figure 4

Peripheral Acuity. Average acuity thresholds (based on 20/20 values) on pretest (blue) and posttest (red) for experimental (A) and control group (B). Error bars represent within subject standard error. C, scatter plot of individual performance where, each point represents one subject in the trained group (blue) or control group (red) at each eccentricity (x=2, O=5, and +=10).

Figure 5

Peripheral Contrast Sensitivity. Average contrast thresholds on pretest (blue) and posttest (red) for experimental (A) and control group (B). Error bars represent within subject standard error. C, scatter plot of individual performance where, each point represents one subject in the trained group (blue) or control group (red) at each eccentricity (x=2, O=5, and +=10).