These results can be qualitatively described using a simple model based on estimates of the spread of current from a metal disc in a semi-infinite medium (based on electrophysiological spatial threshold data)
36 and the perceptual sensitivity model by Horsager et al.,
25 previously used by our group to predict the perceptual sensitivity of the retina to electrical stimulation in human subjects. As described previously, this model bears a strong resemblance to models used to describe both temporal sensitivity for normal vision and retinal sensitivity to electrical stimulation, as measured neurophysiologically,
37 –40 and can predict both absolute thresholds and suprathreshold brightness matching across a wide variety of pulse trains. A schematic of the model is shown in
Figure 6.
We began by applying a spatial attenuation function to the temporal input stimulus pulse train to produce
b1(r,t), a spatiotemporal stimulus profile:
where
f(
t) is the electrical stimulation input pattern,
t is the time (in milliseconds),
r is the distance from the center of the stimulating electrode (in micrometers), and
I(
r) is the current attenuation from a disc electrode. The function used to model the spatial attenuation of current is given by
where
r is the distance from the center of the stimulating disc electrode, and
a is the radius of the electrode (
Fig. 6, BOX 1). The
I(
r) function was obtained by inverting the relationship between threshold and distance from the edge of a 200-μm diameter platinum disc electrode (previously reported in Ahuja et al.
36). In that paper, thresholds from salamander retina were shown to increase with distance
r from the stimulating electrode. We assumed that current attenuation at distance
r was inversely proportional to the increase in threshold at
r.
We then passed this spatiotemporal stimulus through the perceptual sensitivity model. In brief, the stimulus was convolved with a temporal low-pass filter that had a one-stage gamma function with a time constant τ
1 = 0.42 ms as its impulse response (
Fig. 6, BOX 2). We then assumed that the system became less sensitive as a function of accumulated charge and calculated the amount of accumulated cathodic charge over time, and convolving this accumulation with a second one-stage gamma function with time constant τ
2 = 45.25 ms (
Fig. 6, BOX 3). The output of this convolution was scaled (by a factor ε = 8.73) and subtracted from the output of the first convolution. The resulting time course was half rectified.
The previous instantiation of this model determined the amplitude or frequency required to reach threshold or a fixed brightness level. To do this, the half-rectified output,
b 3(
r,
t), was passed through a power nonlinearity of β = 3.4 at threshold and β = 0.8 at suprathreshold. For our purposes a continuous mapping of amplitude/frequency to brightness was required. We therefore replaced β with a continuous function that nonlinearly rescaled
b 3(
r,
t), across space and time, based on a sigmoidal function dependent on the maximum value of
b 3(
r,
t;
Fig. 6, BOX 4):
The parameter values of a (asymptote) = 14, s (slope) = 3, and i (shift) = 16 were chosen to match the observed psychophysical data. Interestingly, for parameter values that reproduced the observed behavior, we found that the sigmoidal function had an accelerating slope near threshold and a compressive slope when amplitude values were at suprathreshold levels: properties very similar to those demonstrated by parameter β in the original Horsager model. These were the only free parameters used to develop this model. All other parameters were based on those of the original Horsager data and model.
Finally, as in the Horsager model, the output,
b 4(
r,
t) was convolved with a low-pass filter described using a three-stage gamma function with time constant τ
3 = 26.25 ms (
Fig. 6, BOX 5). The maximum value of the output from this slow integration over time was used to represent the brightness response for each location in space,
B(
r). For a given stimulus, the brightness of a phosphene was assumed to be linearly related to the maximum brightness of the
B(
r) plot. We estimated the size of the phosphene by calculating the area where
B(
r) > ϴ, where ϴ was fixed as the maximum brightness elicited by a threshold stimulus.
Thus, most of the parameters in this model (τ1, τ2, τ3, and ε) were fixed on the basis of previous work or separate measurements of threshold. Only the parameters of the sigmoid function (a, s, and i) were varied to match our psychophysical results.
Phosphene predictions generated with this model are shown in
Figure 7. The top row shows the effect of increasing amplitude and the bottom row shows the effect of increasing frequency. Note that the 1.25× threshold with a 20-Hz stimulus (outlined images) is common to both the amplitude modulation and the frequency modulation conditions. The maximum value of
B(
r), representing the brightness of the phosphene, is reported below each simulated phosphene. Analogous to our psychophysical data, the model replicates the finding that increasing current amplitude results in increases in both brightness and size, whereas increasing frequency results in an increase in apparent brightness, but little increase in size. The model also replicates the finding that larger increases in apparent brightness can be elicited by changes in frequency than by changes in current amplitude.
Because our model assumes uniform current spread from a disc electrode and equal sensitivity across the retina, all predictions are of a round, symmetric percept. Although our subject did occasionally draw circular percepts, the majority of his percepts resembled elongated ellipses, such as those shown in
Figure 3. This result is probably due to unequal sensitivity across the retinal surface. It is possible that retinal stimulation activates not only the neural tissue directly below the electrode but also the passing axon fibers tracts.
28,41 –44