sampling frequency, each black and white bar falls directly on one row of electrodes. The resolution was, therefore, directly limited by the spacing of the electrodes.

Taken together, these data suggest that the visual resolution of a blind patient implanted with a SSMP A16 retinal prosthesis is limited only by the spacing of the electrodes in the array.

14.6  Models to Guide Electrical Stimulation Protocols

Achieving useful percepts via electrical stimulation requires satisfying a variety of safety and engineering constraints. Useful percepts will require stimulation at frequencies higher than subjects’ perception of visible flicker (frequencies above the “critical flicker frequency”). Second, safety concerns dictate relatively stringent charge density limits, since high charge densities have the potential to compromise the integrity of electrode material [12, 13] and cause damage to stimulated neural cells [48, 49, 67]. Third, the maximum current amplitude that can be produced may in some cases be limited by the compliance voltage of the stimulator. A final set of constraints include limits in the amount of power available to the implant given the need for a long battery life, and power limits inherent in transmitting power inductively, resulting in a need to minimize overall charge.

The models described in this chapter provides an example of how the optimal stimulation pattern needed to produce a percept of a given brightness level can be determined given a set of constraints. A particular example is given in Fig. 14.14, which shows example predictions of threshold current amplitude (graph a), charge density (graph b), and overall charge (graph c) for a 500 ms pulse train presented on an electrode of typical sensitivity across a range of pulse widths and frequencies. The dashed lines represent examples of safety and engineering constraints that might restrict the potential set of stimulation patterns. In the example shown here, a current amplitude limit of 200 mA, and a charge density limit of 0.35 mC/cm2. Given these example constraints, our model predicts that the most charge efficient stimulation pattern, for the conditions and prosthetic device tested here, is a 50 Hz pulse train consisting of 0.089 ms pulses. Similarly, for a given compliance voltage, the most efficient operation (in terms of energy delivered to the electrodes vs. energy dissipated in the current regulator) is when the voltage drop across the electrodes is near this compliance voltage. These engineering constraints may result in the most efficient pulse being at the highest current that can be supplied, making it advantageous to manipulate brightness using either frequency or pulse width. These models can also be used to calculate the most energy efficient pulse width (chronaxie) [17, 26]. Depending on the assumed constraints of the stimulation protocol, models such as these can estimate the best stimulation protocol.

Of course this ability to evaluate engineering and safety trade-offs across different pulse patterns need not be restricted to the simple stimulation patterns used in this example. Our hope is that this model (or similar models) can be generalized

Fig. 14.14  Efficiency predictions for a 500 ms pulse train. In each panel the x-axis represents pulse width on a logarithmic axis, and the y-axis represents frequency. Red dashed lines represent a current amplitude limit of 200 mA, yellow dashed lines represent the constraint that stimulation must occur above the critical flicker frequency of 50 Hz, and blue dashed lines represent the constraint of a charge density limit of 0.35 mC/cm2. Light shading represents pulse widths and frequencies that fall outside these constraints. The z-axis represents current (a), charge density (b), and overall charge across the entire pulse train (c). Given these example constraints, our model predicts that the most charge efficient stimulation pattern is a 50 Hz pulse train consisting of 0.089 ms pulses, as shown by an asterisk in (c). (Please see online version for full-color representation). Reprinted from [33], with permission

to describe percepts over a wide range of brightness levels, across multiple electrodes. It is also to be hoped that models such of these will generalize to other devices, though it is of course quite likely that the models needed to explain subretinal stimulation will differ substantially from those developed to explain epiretinal stimulation. While models such as these may always be a crude approximation of

perceptual effects, without them developing stimulation protocol procedures will remain an ad hoc procedure of trial and error.

14.7  Conclusions

The possibility of restoring sight through electrical stimulation has captured the interest of laymen and scientists for many years [11, 22, 24, 35, 37, 42, 44, 45, 50, 53, 54, 61, 62, 75, 77]. As we make progress, the goals associated with restoring sight in blind patients (as well as our appreciation of the difficulties that must be overcome to reach that goal) have become more sophisticated. In more recent studies, the effort has not been simply to create phosphenes, but to create images that are predictable over both space and time.

Over the last 5 years it has become apparent that maintaining close proximity between the electrode array and the retinal surface will be critical in developing a successful retinal implant. In addition to affecting threshold, separation between the array and the retina is likely to compromise the ability to produce small localized percepts. As thinner electrode array structures are developed and improved methods are developed for attaching the array to the to the retina [29, 71] it should be possible to maintain electrodes that remain flush with retinal tissue for indefinite periods, resulting in impedance and threshold values that are stable over time. A successful prosthesis will require arrays which are stable on the retina, map to predictable locations in space, and are of high enough resolution to provide the quality of visual information needed to perform useful real world tasks. With the use of electrode arrays that meet these criteria, it is likely that the influence of other factors such as progression of retinal degeneration and subject age will become more apparent both within threshold measurements, and within more complex measures of perception.

Over the last 5 years, work by a number of groups including ours has demonstrated that simple visual percepts generated by direct retinal electrical stimulation on a single electrode can be modeled relatively simply. This is true both for amplitude coding [28] and for manipulations of pulse timing within an electrode (frequency encoding).

Of course a wide variety of challenges remain, even in understanding the effects of stimulating a single electrode. For example, apparent brightness is not the only perceptual quality that needs to be considered. It is possible that different temporal patterns stimulate slightly different subpopulations of neurons, resulting in distinct percepts. Moreover, the experiments described here only considered pulse trains or stimulation periods of relatively short duration (a maximum of a few seconds). Longer periods of continuous stimulation (minutes or hours) may result in longterm adaptation, sensitization, and/or retinal rewiring. It is quite likely that frequent electrical stimulation over a time scale of weeks and months may result in changes in retinal connectivity and responsivity [46].

More importantly, it is of critical importance to better understand how neighboring electrodes interact in the spatiotemporal domain. The models described in Sects. 14.3

and 14.4 simply predict sensitivity at the single electrode level, the extension of models such as ours to the spatial domain is an obvious next step.

While preliminary results with “natural tasks” show promise, it is still not entirely clear what kind of spatial resolution is mediated by current prosthetic devices. One concern is that, to date, most (though not all) data have come from constrained two or four alternative forced choice tasks with training and/or feedback so the subject is performing a constrained discrimination task, not an identification task. A subject may be able to discriminate “horizontal” from “vertical” without the horizontal line appearing as a horizontal line, and the vertical line appearing as a vertical line – all that is necessary is for the two stimuli to be perceptually distinct. A second concern is the extent of variability across subjects – to date no group has reported successful performance across a wide range of tasks within all (or even a majority) of implanted subjects. A third concern is that there is still some doubt as to whether all electrodes in these arrays map neatly to the expected perceptual location in space. As described in this chapter, progress over the last 5 years has been rapid, and progress over the next five is likely to bring us still closer to a useful prosthetic array. While it is unlikely that we will be able to build devices that resemble “natural” vision in the next 5 years, it is possible that, even if with some “jumbling” of the sensory input (as is found in cochlear implants for hearing) the brain will learn to understand the new sensory representation (analogous to learning to interpret modern art sketches for people with normal vision). However, we will probably not know the full capacity of the human visual system to adapt to make use of retinal implants until these devices are in more common use.

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Chapter 15

Findings from Chronic Optic Nerve and Cortical Stimulation

Edward M. Schmidt

Abstract  This chapter reviews the experiments that have produced visual sensations in humans through electrical stimulation of the central nervous system. Initially, surface stimulation of the visual cortex, provided insight into how electrical stimulation of V1 could possibly provide a visual prosthesis for the blind. Intracortical microstimulation was then investigated that would allow lower power stimulation and increased density of microelectrodes. The stimulation of the optic nerve has also been investigated as a possible site for a visual prosthesis.

The next section is dedicated to what is known and what needs to be done for the development of a visual prosthesis.

The following section examines current research efforts directed towards the development of a visual prosthesis. They include optic nerve stimulation, cortical surface stimulation and intracortical stimulation of visual cortex. The CORTIVIS Program is a comprehensive development of an intracortical visual prosthesis. The lateral geniculate nucleus is also being studied as a site for a visual prosthesis.

The final section of this chapter deals with the developments that are needed for a functional visual prosthesis. They include microelectrode arrays, stimulation hardware, and low power image sensing and processing circuitry that can control the stimulators.