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Review
. 2017 Oct;14(5):051003.
doi: 10.1088/1741-2552/aa795e. Epub 2017 Jun 14.

Learning to see again: biological constraints on cortical plasticity and the implications for sight restoration technologies

Michael Beyeler  1 , Ariel Rokem, Geoffrey M Boynton, Ione Fine
Affiliations
Review

Learning to see again: biological constraints on cortical plasticity and the implications for sight restoration technologies

Michael Beyeler et al. J Neural Eng. 2017 Oct.

Abstract

The 'bionic eye'-so long a dream of the future-is finally becoming a reality with retinal prostheses available to patients in both the US and Europe. However, clinical experience with these implants has made it apparent that the visual information provided by these devices differs substantially from normal sight. Consequently, the ability of patients to learn to make use of this abnormal retinal input plays a critical role in whether or not some functional vision is successfully regained. The goal of the present review is to summarize the vast basic science literature on developmental and adult cortical plasticity with an emphasis on how this literature might relate to the field of prosthetic vision. We begin with describing the distortion and information loss likely to be experienced by visual prosthesis users. We then define cortical plasticity and perceptual learning, and describe what is known, and what is unknown, about visual plasticity across the hierarchy of brain regions involved in visual processing, and across different stages of life. We close by discussing what is known about brain plasticity in sight restoration patients and discuss biological mechanisms that might eventually be harnessed to improve visual learning in these patients.

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Figures

Figure 1
Figure 1
Example simulations demonstrating potential perceptual distortions and information loss for different sight recovery technologies. All images are based on the central 12° region of a movie and a 1000×1000 array (A.) Original image. (B.) Simulation of sub-retinal electrical stimulation, based on simultaneously stimulating ON and OFF pathways with no axonal stimulation. (C.) Simulation of epiretinal electrical stimulation, based on simultaneously stimulating ON and OFF pathways with axonal stimulation resulting in visual ‘comets’. (D.) One frame in a movie showing simulation of optogenetic stimulation, based on a model of simulating ON pathways with an optogenetic protein with temporal dynamics based on ReaChR (Sengupta et al. 2016). Motion streaks are the result of the sluggish temporal dynamics of ReaChR. Modified figure based on Fine and Boynton (2015).
Figure 2
Figure 2
Quantifying loss of information in epiretinal devices. (A.) The retinal location of a simulated Argus II array (6×10 electrodes) and the predicted percepts generated by stimulating single electrodes both without (left) and with (right) axonal stimulation. (B) The retinal location of a simulated high-resolution array (30×50 electrodes) with analogous percepts. (C, D.) Spatial distortions result in a reduced number of effective electrodes (i.e., the number of principal components needed to explain 95% of the variance) as a function of the number of physical electrodes in the array, excluding (C.) and including (D.) axonal stimulation.
Figure 3
Figure 3
Performance improvement as a function of practice over time for 16 different perceptual tasks (ordered according to the estimated learning slope). For all studies, performance on each session was converted into d′ (Green and Swets 1966). The learning index, L, measures improvements in performance with practice, Ls=ds′/d1′, where s is the session number. A learning index remaining near 1 implies that observers showed no improvement in performance with practice. Reprinted with permission (Fine and Jacobs 2002).
Figure 4
Figure 4
Two examples of a dining table under conditions of simulated prosthetic vision. Under ‘laboratory’ conditions the plate, cup, napkin and fork are easily differentiable. Real-world conditions for Dr. Fine’s dining table include multiple additional and unexpected objects. Finding the fork is challenging, even for an individual with normal vision.
See this image and copyright information in PMC

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