Basic Quantitative Assessment of Visual Performance ...

Visual Psychophysics and Physiological Optics

Basic Quantitative Assessment of Visual Performance in Patients with Very Low Vision Michael Bach,1 Michaela Wilke,2 Barbara Wilhelm,3 Eberhart Zrenner,4 and Robert Wilke4 PURPOSE. A variety of approaches to developing visual prostheses are being pursued: subretinal, epiretinal, via the optic nerve, or via the visual cortex. This report presents a method of comparing their efficacy at genuinely improving visual function, starting at no light perception (NLP). METHODS. A test battery (a computer program, Basic Assessment of Light and Motion [BaLM]) was developed in four basic visual dimensions: (1) light perception (light/no light), with an unstructured large-field stimulus; (2) temporal resolution, with single versus double flash discrimination; (3) localization of light, where a wedge extends from the center into four possible directions; and (4) motion, with a coarse pattern moving in one of four directions. Two- or four-alternative, forced-choice paradigms were used. The participants’ responses were selfpaced and delivered with a keypad. RESULTS. The feasibility of the BaLM was tested in 73 eyes of 51 patients with low vision. The light and time test modules discriminated between NLP and light perception (LP). The localization and motion modules showed no significant response for NLP but discriminated between LP and hand movement (HM). All four modules reached their ceilings in the acuity categories higher than HM. CONCLUSIONS. BaLM results systematically differed between the very-low-acuity categories NLP, LP, and HM. Light and time yielded similar results, as did localization and motion; still, for assessing the visual prostheses with differing temporal characteristics, they are not redundant. The results suggest that this simple test battery provides a quantitative assessment of visual function in the very-low-vision range from NLP to HM. (Invest Ophthalmol Vis Sci. 2010;51:1255–1260) DOI:10.1167/iovs.093512

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everal groups worldwide are currently using various approaches in the development of visual prostheses. Retinal prostheses have been designed to restore lost visual function due to degenerative retinal diseases, such as retinitis pigmentosa (RP) and age-related macular degeneration (AMD).1–13

From the 1Sektion Funktionelle Sehforschung, University Eye Hospital Freiburg, Freiburg, Germany; the 2University Eye Hospital, Ludwig-Maximilians University, Munich, Germany; the 3Steinbeis Transfer Center eyetrial at the Center for Ophthalmology, and the 4Institute for Ophthalmic Research, Center for Ophthalmology, University of Tu ¨bingen, Tu ¨ bingen, Germany. Supported by German Federal Ministry of Education and Research (BMBF) Grants 01IN502A-D and 01KP0008-12, the Kerstan-Foundation, and Retina Implant AG, Ru ¨ tlingen, Germany (MB). Submitted for publication February 3, 2009; revised July 30 and September 10, 2009; accepted September 21, 2009. Disclosure: M. Bach, Retina Implant AG (C); M. Wilke, None; B. Wilhelm, Retina Implant AG (I); E. Zrenner, Retina Implant AG (I); R. Wilke, None Corresponding author: Michael Bach, Universita¨ts-Augenklinik, Killianstrasse 5, 79106 Freiburg, Germany; [email protected]. Investigative Ophthalmology & Visual Science, February 2010, Vol. 51, No. 2 Copyright © Association for Research in Vision and Ophthalmology

These conditions cause a gradual loss of photoreceptor cells, yet a substantial fraction of the neural pathways from the retina to the visual cortex remain functional. Approaches involving optic nerve electrode cuffs or cortical electrode arrays are aimed at restoring visual function along the retinal processing stream, which can be lost due to many different blinding conditions.14 –16 The current arsenal of visual assessment protocols is not effective for quantitatively evaluating the efficacy of visual prostheses for two main reasons: (1) In the first-phase human trials, only patients can be included for whom no other means of prevention or therapy is available and whose visual function is below counting fingers (CF) and/or hand movement (HM) detection; and (2) even after successful interventions, we cannot foresee to what extent and how well these devices will restore vision in an individual patient. There is therefore a need to test various visual functions, from mere light perception (LP) over crude temporal and spatial resolution toward combined spatiotemporal functions such as motion recognition. The test battery Basic Assessment of Light, Location, Time, and Motion (BaLM) was designed to meet these requirements. This report presents the implementation details and results in patients in the very-low-vision range.

METHODS Guiding Principles and Design Visual acuity is just one of several dimensions of vision. To assemble a gradually ascending series of tasks, we developed a test battery targeting the following visual dimensions: luminance, time-resolution of luminance, and localization of light and motion. The choice of visual dimensions was based on results in visual search and texture segregation as a basic mechanism of gestalt perception.17–21 Although grating stimuli almost instinctively come to mind in vision testing, we specifically did not implement grating tests, as they are already available in various versions22; a grating stimulus does not resemble natural visual environments; and, given the finite spatial sampling of the prostheses, aliasing would have to be dealt with. Our main goal was to provide objective and reliable evidence as to whether substantial vision is present and to provide longitudinal data on visual function in future clinical trials. Thus, we chose to start with go/no-go (g-n-g) tasks (seen/not seen23) rather than threshold estimation. Tasks of the g-n-g type are faster, easier on the patient (as the test does not spend most of its time in the uncomfortable threshold region), and easier to communicate to the patients. All test modules employ a two-, four- or eight-alternative, forced-choice scheme, reducing effects of the observer criterion.24 On the other hand, a g-n-g task has an implicit threshold, which we will later use for coarse quantification. When specific performance criteria are reached with BaLM, one can progress to threshold assessment (e.g., with the Freiburg Visual Acuity and Contrast test [FrACT]),25 which has been shown to reliably quantify acuity down to HM levels,26,27 or the BaGA (Basic Grating Acuity) test, which allows estimation of spatial resolution independent of exact fixation ability.22

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Implementation

⬎99%. Ambient light was set at 3 cd/m2. Spatial calibration is performed by measuring a ruler line on the “preferences” screen of BaLM and inputting its length in millimeters; the observation distance is also entered. The correct angular dimensions of the stimuli are calculated by BaLM from these values.

Since blind subjects are usually good at hearing and somatosensing, BaLM communicates with sounds, and the patients use a standard numerical keypad to input responses themselves. Feedback tones can also relay information about response accuracy. A test sequence, once started, runs automatically (self-paced) to reduce operator influence. At the end of each run, results are compiled and documented by direct printout or PDF filing. BaLM was implemented in a commercial programming environment (Flash with the ActionScript 2 language; Adobe Systems, Inc., San Jose, CA). Common Aspects of All Test Modules. The basic procedure after subject training is as follows: One of the four test modules is selected. The stimulus is presented, accompanied by an auditory cue. The participant responds by pressing a key, and an auditory signal provides feedback on the correctness of the response. After an intertrial interval of 1.5 seconds, the next trial follows. When the preset number of trials (typically 24) is reached, a gong sound announces the end of that run. Then, the next BaLM module is started. All test results (hit rates, reaction times, test parameters, subject and examiner identification, and time and date) are accumulated across all tests and can be printed out on paper or saved to PDF for documentation. A “clear results” button deletes this history, so as to prepare for a new session. The modules are arranged roughly in a hierarchical order of visual difficulty. As an obvious example, when a patient fails the light module, it is unlikely that the time module will be passed, because in the time module, the patient must discriminate between one or two of the flashes involved in the light module. The next step, the module for localization of light, is regarded as more difficult in the clinical examination of low vision also. Light Module. This test module, the simplest module of all four, tests basic light perception. The subjects’ task is to decide whether they see light appear after the warning tone or not. The main parameters that can be manipulated are luminance (via neutral density filters) and flash duration (default, 200 ms). When a large range (more than one order of magnitude) is targeted, it is best achieved with neutraldensity filters in a trial frame (or in front of the computer projector, which we used in place of a visual display unit). This luminance parameter applies to all four test modules. A two-alternative, forcedchoice (2AFC) scheme is used. As some visual prosthetic devices may perform better with patterned stimulation, the flashes can be set to a pattern rather than being spatially homogeneous. Time Module. This module assesses one basic aspect of time resolution—namely, whether one or two flashes occur after an indicator beep. Since many prosthetic devices use some kind of scanning or multiplexing and the visual environment changes over time, this visual dimension is relevant. In addition to luminance, the time interval can be manipulated (default, 200 ms); the time-integrated light energy is identical for both flash alternatives. A 2AFC scheme is used. Location Module. This module effectively tests light projection. A light disc appears that the subject must center in the, probably limited, visual field. After a preset delay, simultaneously with a warning tone, a wedge appears directed up, down, right, or left from the fixation disc (Fig. 1). The subject indicates the direction of the wedge. Free parameters are the number of directions (four or eight), diameter of the initial fixation disc (default, 5°), and the eccentricity spanned by the wedge, thus also defining its width (default, 15°). Motion Module. A random hexagonal pattern of light and dark elements appears. After an acoustic signal, it begins to move in one of four or eight directions. The subject indicates the motion’s direction. Free parameters are the number of directions (four or eight) and the visual angle spanned by a hexagon (default, 3.3°). Calibration. Calibration is necessary in intensity and space. We measured stimulus luminance with a photometer (IL1700; International Light, Peabody, MA), and the projector was adjusted to the desired screen luminance of 5100 cd/m2 and a Michelson contrast of

The First Clinical Application Subjects. Patients were recruited from the low-vision department of the University Eye Hospital Munich. The research adhered to the tenets of the Declaration of Helsinki28; informed consent was obtained from the subjects after explanation of the nature and possible consequences of the study. We tested 73 eyes in 51 patients with acuities ranging from no light perception to 0.2decimal ⫽ 0.7logMAR. Patient ages ranged from 20 to 87 years, with a median of 50 years. Inclusion criteria were willingness to participate and severely reduced acuity. Several disease conditions were examined: retinitis pigmentosa (n ⫽ 23), cone–rod dystrophy (n ⫽ 10), choroideremia (n ⫽ 6), LCA (n ⫽ 2), ROP (n ⫽ 5), AMD (n ⫽ 5), myopic macular degeneration (n ⫽ 1), macular dystrophy (n ⫽ 2), glaucoma (n ⫽ 11), optic atrophy (n ⫽ 6), and trauma (n ⫽ 2). Table 1 summarizes the participants’ visual function. Response Box. To prevent errors in communication, we trained the subjects to enter their responses via a keypad, which could be operated by blind participants or in darkness. The keypad was a commercial USB-connected 3 ⫻ 3 numerical entry pad. The central key (5) initiated a test run, and four keys at left, right, top, and bottom coded the test response: one flash, left key; two flashes, right key. For location and motion, the keys corresponded geographically to the direction observed. If the subject was uncomfortable with the keypad, he or she could use verbal responses, which are then entered by the investigator. Procedure. BaLM can be performed by stimulus presentation (1) on a computer screen or (2) via computer projector, which provides a larger stimulus-intensity range. The latter setup was used in this first clinical application. The subjects sat in a chair that was adjustable in height to allow for a comfortable fit in a chin- and headrest. With appropriate correction, they viewed a projection screen at 57 cm distance (at this distance, 1° ⫽ 1 cm), on which a computer projector, mounted above the subjects’ head, projected the stimuli. One hand rested on the response keypad. A computer with a double video output was used. Most current laptops can mirror their built-in display on a video-out socket, which was connected to the projector. Since the main BaLM screen is laid out in dark gray colors, there was no need to switch off the projector for operator entry. The number of trials was set to 24 for all the tests. The light and time test modules had 2AFC. The location and motion test modules had four response alternatives (4AFC). Table 2 describes the psychometric characteristics depending on the number of alternatives. As usual, the positive test outcome criterion was set at the steepest point of the psychometric function, which is the center between chance rate and 100% correct. As can be seen, the probability of exceeding the criterion by chance in 24 runs is ⬃1% for 2AFC and miniscule for 4AFC and 8AFC. The subjects were instructed to look straight at the middle of the screen. At the beginning of each session, they were guided to touch the middle of the screen to obtain a tactile impression of the screen’s position. Before the start of each module, the subjects were informed about that module’s function and the valid choices. They were encouraged to respond within the time limit, even when uncertain. No head or eye tracking was used during the testing to account for fixation. Each session always began with the light test module. This module started with the densest filter (d ⫽ 4.6) in front of the projector, resulting in a luminance of 0.13 cd/m2. When the criterion was not reached, the filter density was reduced in roughly half-log units until it was reached or the no-filter condition was reached. The last filter level was recorded as the threshold in module light. For the three subsequent test modules (time, location, and motion), we reduced the threshold filter by 0.5 log units so that the tests operated in the suprathreshold range.


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FIGURE 1. Schematic overview of BaLM. The main screen (middle left, dark gray) has buttons to indicate preferences (top left, light gray), the printing interface (bottom left), and the four test modules (right). The test screens show a schematic sequence with alternatives: for light, the sequence starts with a dark screen, and with an audible beep, the screen lights up (top path) or stays dark (bottom path), and ends with the dark screen, waiting for the response. For time, the sequence emits 1 or 2 flashes. For location, a fixation disc forms a wedge into one of four directions (only two shown here). For motion, a random pattern moves briefly in one of four directions (only two shown).

RESULTS All patients readily understood the tasks and had no difficulty in operating the response keypad after training. The results are summarized in Figure 2 for all eyes and all test modules. These are now discussed in detail by going through Figure 2 in the sequence light, time, location, and motion. Four box plot panes are depicted in which the median is indicated by the horizontal thick lines, the box covers the 25% to 75% percentile range, the whiskers indicate the range, and the circles indicate outliers.

Light Module The ordinate represents the neutral density of the strongest filter where the criterion was reached; filter setting 0 also includes

those who failed to reach criterion. In the no light perception (NLP) group, 3 of 17 eyes reached criterion with a neutral-density filter setting of 1.0 or higher, indicating some residual LP. Progressing to better visual perception, there is a transition toward dimmer flashes (higher neutral-density values) required for criterion recognition from NLP to HM, saturation for the higher acuity categories CF and better than CF (CF⫹).

Time Module The ordinate depicts the percentage correct responses; the chance rate is 50% with 2AFC and the criterion is 75%. In this test module (double-flash discrimination) the NLP eyes remained near chance level. In patients with LP, the median hit rate rose to 70% and reached 100% for HM through CF⫹.

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TABLE 1. Distribution of the Tested Eyes among the Clinical Visual Acuity Categories

battery for each of the four test modules. The Appendix lists starting values, which we arrived at after several pilot trials.

Visual Acuity Category

Abbreviation

n

Percentage of Eyes

First Clinical Application in Patients with Low Vision

NLP LP HM CF CF⫹

NLP LP HM CF CF⫹

17 26 17 2 11

23.3% 35.6% 23.3% 2.7% 15.1%

Location Module The ordinate depicts the percentage correct; the chance rate is 25%, with the 4AFC criterion 62.5%. In this test module, both NLP and LP performed at chance level, whereas HM through CF⫹ eyes reached hit rates above 90%.

Motion Module The ordinate depicts the percentage correct, with the 4AFC chance rate 25% and criterion 62.5%. As in the location module, both NLP and LP performed at chance level, while HM through CF⫹ eyes reached hit rates above 90%.

Comparison across Test Modules All four test modules reached their ceiling at HM. Thus, none of the modules discriminated between HM, CF, and CF⫹. The light and time modules discriminated between NLP and LP. For the location and motion test modules, no NLP eye exceeded 75% criterion, but both modules discriminated between LP and HM (and better). There was a marked rise in the median for chance response at LP to nearly 100% performance at HM and better, whereas the quartile boxes indicate that there was some overlap in performance between some LP and HM eyes.

DISCUSSION Implementation Aspects The software implementation environment flash was chosen in 2003 and proved adequate, one major advantage being its platform independence. One disadvantage is that there is no means of synchronizing graphic changes to the cyclic screen update (be it 60 Hz for LCDs or higher rates with CRTs); thus, the temporal granularity is limited to approximately 20 ms. Given the current state of the art in visual prostheses, this limitation did not prove to be a problem. To ensure adaptability for unexpected findings with patients wearing prostheses, we included many free parameters in the test

BaLM was designed to quantitatively assess visual function in patients with very low vision (below CF). We validated BaLM by testing 73 eyes in 51 patients in the following visual categories, arranged in order of increasing visual function: NLP, LP, HM, CF, and CF⫹. Of the four test modules in BaLM, the light and time test pair behaved similarly and showed the steepest rise in detection between categories NLP and LP. The test pair location and motion also behaved similarly and showed the steepest rise in detection between the categories LP and HM. In terms of a sensitivity/ specificity analysis (Table 3), both location and motion showed 100% specificity to detect vision above NLP. In other words, there are no false positives in detecting vision above NLP. The observation that the time test’s specificity was only 88% and not 100% suggests that the patients with NLP had some residual vision, which is also evident from the light test results. A completely blind subject (e.g., simulated by switching off the display) would perform at chance level, which has a mere 0.8% chance of exceeding the criterion in 24 trials (see Table 1). By increasing the number of trials to, for instance, 40, this chance can be reduced to below 0.1%. In fact, the 4AFC modules location and motion possess such a chance rate, below 0.01% with 24 trials. The light and time, and location and motion test modules yielded very similar results in our patients. We do not view the time and motion modules as superfluous; however, they are more challenging to the visual system as they additionally assess a different dimension of vision—namely, the temporal domain. Time discrimination and temporal resolution are important and, in principle, are possible without pattern vision. The motion module requires both spatial and temporal resolution. These aspects will be useful to assess actual visual prostheses, as these often invoke time multiplexing, thus limiting temporal resolution and possibly resulting in temporal aliasing. In line with these considerations, preliminary results from patients wearing subretinal visual prostheses indicate that in these patients there may be bigger discrepancies between the light/time and location/motion modules results, respectively. In addition, if BaLM is to mimic clinical examination with the advantage of providing quantitative data while avoiding examiner bias, the motion module must be regarded as the equivalent of HM. We noted a ceiling effect in all four test modules for acuity categories above HM. In other words, the tests become too easy for subjects with vision approaching normal. We do not view this ceiling effect as a shortcoming,

TABLE 2. Psychometric Characteristics of Two-, Four-, and Eight-Alternative, Forced-Choice Tasks Probability of Reaching or Exceeding Criterion by Chance 24 Trials

Alternatives (n)

Chance Rate (1/n ⴛ 100%)

Criterion [(100 ⴚ Chance Rate)/ 2 ⴙ Chance Rate]

2 4 8

50% 25% 12.5%

75% 62.5% 56.25%

30 Trials

(Binomial [cumulative] Depending on n, Chance Rate, and Criterion) 1.1% 0.011% 0.000013%

0.26% 0.001% 0.000001%

The second row of the heading describes the formulas used. The data show the resulting values assuming 24 or 30 trials.

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FIGURE 2. Results of the patients grouped by acuity categories from NLP to CF⫹, in the four BaLM test modules. Box plot details: the thick horizontal bars indicate the median; the box indicates the interquartile range (from 25% to 75%); the whiskers indicate the range; the circles indicate data more than 1.5 times the interquartile range away from the box, considered outliers. The numbers at the bottom of the times panel indicate the number of eyes per category. For the light module, the ordinate provides the neutral density of the strongest filter where the subject reached criterion; filter 0 also includes those who did not reach criterion. We observed a progression toward dimmer flashes being required for criterion recognition from NLP to HM and saturation for higher acuity categories. In the other three modules, the ordinate depicts the correct percentage for the acuity categories. Patients with NLP remained at chance level for time (double flash discrimination, ⬇59%) and location and motion (⬇25%). Those with LP surpassed chance for time, but not for location and motion, while patients with HM and better passed location and motion by a ⬎90% hit rate.

TABLE 3. Sensitivity/Specificity Analysis of the Three Test Modules with a Fixed Criterion Test Module/ Detecting Vision Time ⬎NLP ⬎LP ⬎HM Location ⬎NLP ⬎LP ⬎HM Motion ⬎NLP ⬎LP ⬎HM

Sensitivity (%)

Specificity (%)

77.0 (67.2–85.7) 97.0 (90.3–100) 100 (100–100)

88.2 (73.7–100) 62.8 (50.1–74.5) 45.2 (36.5–57.6)

45.0 (33.3–55.2) 73.0 (59.1–86.1) 85.0 (66.7–100)

100 (100–100) 93.0 (86.0–98.0) 76.7 (68.3–86.0)

48.0 (36.8–58.8) 87.0 (75.0–96.4) 92.0 (77.8–100)

100 (100–100) 97.7 (93.2–100) 75.0 (66.1–84.5)

Confidence intervals for the sensitivity/specificity estimates were obtained by bootstrapping28 (generating 300,000 new sample populations from the original population with replacing). This method creates a distribution for the sensitivity/specificity values, allowing estimation of their confidence limits (the 5% and 95% percentile is given in parenthesis). If the NLP eyes really had no light perception at all, the specificity for the time module to detect vision better than NLP should be 100%. The lower value suggests that some eyes did have residual light perception. The Location and Motion modules do not have false positives at NLP. It is not surprising that the sensitivity rises near to 100% for all modules; any normal subject would easily pass all test modules.

because starting with HM and above, other acuity tests can take over. For instance, the FrACT25,27 is also a computerized automated test that can reproducibly estimate visual acuity starting with HM (2.3 logMAR),19,26 ETDRS (Early Treatment of Diabetic Retinopathy Study) charts can be applied starting with CF.26 Spatial resolution of gratings without requiring fixation ability can be assessed by using BaGA,22 for example. All subjects in this feasibility study performed all tests. For applications assessing implant efficacy, failure to reach criterion on the light module renders the rest of the test battery unnecessary. This recommendation is based on our observation in this study that the patients with NLP, almost none of whom passed the light criterion, performed at chance levels in the remaining test modules. Our results indicate that the test battery allows quantitative assessment of visual function in the targeted very-low-vision range from NLP over LP to HM. We are not aware of any other test that systematically and quantitatively discriminates among NLP, LP, and HM, and we have already found it useful in patients wearing visual prostheses.

Acknowledgments The authors thank Walter-Gerhard Wrobel (CEO, Retina Implant AG), for financing the development of the test battery BaLM, which Retina Implant AG now offers as a commercial product; Wilhelm Durst for technical support; and Carolin Kuttenkeuler, Thomas Zabel, Anna Bruckmann, Johannes Koch, and Katarina Porubska for contributing to patient examinations in the first pilot trial of a subretinal implant.

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References 1. Zrenner E. Will retinal implants restore vision? Science. 2002;295: 1022–1025. 2. Besch D, Sachs H, Szurman P, et al. Extraocular surgery for implantation of an active subretinal visual prosthesis with external connections: feasibility and outcome in seven patients. Br J Ophthalmol. 2008;92:1361–1368. 3. Yanai D, Weiland JD, Mahadevappa M, Greenberg RJ, Fine I, Humayun MS. Visual performance using a retinal prosthesis in three subjects with retinitis pigmentosa. Am J Ophthalmol. 2007; 143:820 – 827. 4. Zhou JA, Woo SJ, Park SI, et al. A suprachoroidal electrical retinal stimulator design for long-term animal experiments and in vivo assessment of its feasibility and biocompatibility in rabbits. J Biomed Biotechnol. 2008;2008:54742. 5. Wong YT, Dommel N, Preston P, et al. Retinal neurostimulator for a multifocal vision prosthesis. IEEE Trans Neural Syst Rehabil Eng. 2007;15:425– 434. 6. Hornig R, Zehnder T, Velikay-Parel M, Laube T, Feucht M, Richard G. The IMI Retinal Implant System. In: Humayun MS, Weiland JD, Chader G, Greenbaum E, eds. Artificial Sight. New York: Springer; 2007:111–128. 7. Gerding H, Benner FP, Taneri S. Experimental implantation of epiretinal retina implants (EPI-RET) with an IOL-type receiver unit. J Neural Eng. 2007;4:S38 –S49. 8. Winter JO, Cogan SF, Rizzo JF 3rd. Retinal prostheses: current challenges and future outlook. J Biomater Sci Polym Ed. 2007;18:1031– 1055. 9. Terasawa Y, Tashiro H, Uehara A, et al. The development of a multichannel electrode array for retinal prostheses. J Artif Organs. 2006;9:263–266. 10. Nakauchi K, Fujikado T, Kanda H, et al. Transretinal electrical stimulation by an intrascleral multichannel electrode array in rabbit eyes. Graefes Arch Clin Exp Ophthalmol. 2005;243:169 –174. 11. Walter P, Kisvarday ZF, Gortz M, et al. Cortical activation via an implanted wireless retinal prosthesis. Invest Ophthalmol Vis Sci. 2005;46:1780 –1785. 12. Palanker D, Vankov A, Huie P, Baccus S. Design of a high-resolution optoelectronic retinal prosthesis. J Neural Eng. 2005;2:S105–S120. 13. Rizzo JF 3rd, Wyatt J, Loewenstein J, Kelly S, Shire D. Perceptual efficacy of electrical stimulation of human retina with a microelectrode array during short-term surgical trials. Invest Ophthalmol Vis Sci. 2003;44:5362–5369.

14. Brelen ME, Duret F, Gerard B, Delbeke J, Veraart C. Creating a meaningful visual perception in blind volunteers by optic nerve stimulation. J Neural Eng. 2005;2:S22–S28. 15. Cohen ED. Prosthetic interfaces with the visual system: biological issues. J Neural Eng. 2007;4:R14 –R31. 16. Fernandez E, Pelayo F, Romero S, et al. Development of a cortical visual neuroprosthesis for the blind: the relevance of neuroplasticity. J Neural Eng. 2005;2:R1–R12. 17. Treisman A, Gormican S. Feature analysis in early vision: evidence from search asymmetries. Psychol Rev. 1988;95:15– 48. 18. Treisman A. Preattentive processing in vision. Comput Vis Graph Image Proc. 1985;31:156 –177. 19. Bach M, Meigen T. Similar electrophysiological correlates of texture segregation induced by luminance, orientation, motion and stereo. Vision Res. 1997;37:1409 –1414. 20. Nothdurft H-C. Salience from feature contrast: additivity across dimensions. Vision Res. 2000;40:1179 –1182. 21. Wolfe JM. Visual search. In: Pashler H, ed. Attention. London, UK: University College London Press; 1998:22–118. 22. Wilke R, Bach M, Wilhelm B, Durst W, Trauzettel-Klosinski S, Zrenner E. Testing visual functions in patients with visual prostheses. In: Humayun MS, Weiland JD, Chader G, Greenbaum E, eds. Artificial Sight. New York: Springer; 2007:91–110. 23. Pashler H, Yantis S. Stevens’ Handbook of Experimental Psychology. 3rd ed. New York: Johnn Wiley & Sons; 2002:816. 24. Green DM, Swets JA. Signal Detection Theory and Psychophysics. New York: John Wiley & Sons; 1966. 25. Bach M. The Freiburg Visual Acuity Test: automatic measurement of visual acuity. Optom Vis Sci. 1996;73:49 –53. 26. Schulze-Bonsel K, Feltgen N, Burau H, Hansen LL, Bach M. Visual acuities “hand motion” and “counting fingers” can be quantified using the Freiburg Visual Acuity Test. Invest Ophthalmol Vis Sci. 2006;47:1236 –1240. 27. Lange C, Feltgen N, Junker B, Schulze-Bonsel K, Bach M. Resolving the clinical acuity categories “hand motion” and “counting fingers” using the Freiburg Visual Acuity Test (FrACT). Graefes Arch Clin Exp Ophthalmol. 2009;247:137–142. 28. World Medical Association. Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA 2000; 284:3043–3045. 29. Wikipedia. Bootstrapping (statistics). 2009. http://en.wikipedia. org/wiki/Bootstrapping.

APPENDIX TABLE A1. Suggested Default Parameters for BaLM Test Module/Parameter All Auditory stimuli Auditory feedback Timeout Intertest interval Number of trials Light Time on Flash type Time Time on Time off Location Number of directions Eccentricity Diameter Motion Number of directions Hexagon size Velocity Contrast

Value

False Always 100 s 1500 ms 24 200 ms Homogenous

Comment

Intended for auditory practice runs, which proved unnecessary; not fully implemented. With “always‘, the type of sound indicates correct versus incorrect responses. An incorrect response is recorded after this interval. Lower numbers reduce the test’s specificity. Some prosthetic devices may be optimized for our patterned environment, if so choose “checkerboard.”

200 ms 200 ms

The interstimulus interval, ISI

4 15° 5°

4AFC Indicates what eccentricity the oriented wedge reaches. The diameter of the fixation disc before the wedge appears.

4 3.3° 3.3°/s 100%

4AFC Reducing this parameter may allow discrimination in higher acuity categories.