這里的結果來自隨機、盲法對照研究。包括病人有斜視性和屈光參差性弱視，年齡在9~55歲（常沒有接受過治療）。弱視眼最佳矯正視力測量在6/9到6/30，用糖尿病視網膜病變早期治療研究視力表，ETDRS。每一個受試者（或父母/法定監護人）均簽知情同意書，并經過Institutional Review Board的認可。總共77名弱視病人（分為2組）和16名正常視力受試者（對照組）參加這次研究。
他們的臨床資料和治療史在表1和圖2中描述。最佳矯正視力是通過三個隨機選擇的ETDRS視力表來檢測（[LogMAR (最小分辨角的對數) 視力表]，這是由對受檢者分配的亞組是不知道的臨床醫生來進行.每個研究中參加者在2~4周中每個治療節為30分鐘，總共45 ±15個節（平均標準差）。
每個患者均進行一系列全面的評估，包括與弱視相關因素的具體眼病史，如弱視診斷年齡、治療史、家族史等。也進行了詳細的眼科檢查，包括睫狀體麻痹散瞳驗光。眼球運動同樣也檢查，通過遮蓋試驗檢查眼球位置，通過Worth4點法和Titmus立體圖檢測雙眼視覺功能。根據收集的基礎數據，弱視的類型被詳細分類。CSF以基線檢測，它是在治療過程中和治療后隨訪中進行檢查，是通過3m遠的一個貼在墻上的表實現(S.W.C.T.,Stereo Optical Company, Chicago)。室內照度被人為控制（≈140cd/m,人為控制在68~240cd/m）。這些條柵在所有頻率的視角都在1.4°。用于治療的是空間頻率在1.5~12周/度的灰度條柵（GS）刺激，并受到背景灰度為40cd/m2調制。在所有的試驗中GS的標準差等于其波長（σ=λ）。刺激呈現在一臺Philips107P多媒體顯示器上，顯示器屏幕的有效大小為24·32cm，在150cm的地方觀看，視角為9×12°。受試者在一間小暗室里，周圍只有來至于屏幕的光照.。
第一治療組（n ＝40 of 44，開口方形）最初用3到12cpd的一系列空間頻率進行檢測(mean ＝ 5.9, SD ＝ 2.8 across participants)，第二治療組(n ＝ 19;三角形)用1.5到6cpd低范圍空間頻率測試(mean ＝ 2.7, SD ＝ 1.6),第二組正常者(n ＝ 16)空間頻率的范圍根第一治療組一樣(3–12 cpd; mean ＝ 7.7, SD ＝ 3.6)。數據清晰顯示出弱視者易化作用的缺失，跟正常（第一弱視組）相比前者在高空間頻率的抑制范圍更大。這種抑制作用是我們聯想到弱視者典型的擁擠現象。
低空間頻率（第二弱視組）的結果顯示接近于正常的易化作用，與弱視者在低空間頻率刺激下的視力正常是一致的。其次，個人閾值升高，平均范圍是2-6，被用于量化易化作用，其分布顯示在圖2b中。弱視第一組的平均閾值（均數+標準差）升高是0.18 ＋－ 0.1對數單位(抑制, n ＝ 40)，弱視第二組是－0.11 ＋－ 0.02(易化, n ＝ 19)，正常組是－0.12 ＋－ 0.03。這些結果顯示弱視者的空間交互異常與敏感度的降低是相關的，而且能解釋這里和別處觀察到的一些個體差異。
標準訓練節是察覺在有或沒有側翼共線高對比度斑時小的條柵條紋的對比度(a GS; see Fig. 1)，在訓練的過程中（達到80次），改變大小（空間頻率）和刺激方向，從低空間頻率開始逐漸增至高頻率，每個空間頻率有4個方向。另外，在訓練前或后用標準對比敏感度表測量弱視者對比敏感度。比正常者表現出高閾值（低敏感性），在低空間頻率時在正常低限范圍內（跟正常沒有明顯不同），在高空間頻率時顯示高敏感度缺失。訓練的結果是所有空間頻率下敏感度提高，在高空間頻率范圍內提高到正常范圍內。（圖3a）
CSF曲線在1.5, 3, 6, 12, and 18 cpd的空間頻率，每個頻率下閾值分別提高2.21, 2.12, 2.93,4.23, and 2.05（紫線，治療后12個月），均達到統計學差異。此外，如圖2顯示的，側向抑制作用在訓練后顯著降低，如圖3b（22個弱視患者，第二組，6cpd），在學習后顯示沒有抑制（提高0.15個對數單位，40%）。易化的提高（抑制的降低）和VA之間的相關系數r是0。68。意味著側向易化的提高能夠解釋VA增加了46%。
VA，相似于字母辨別，要求受試者把圖形映射成已知類型。因為在視皮層的空間濾過器濾過任何視覺信息的輸入，估計也限制字母分辨的能力。特別地，上面描述的側向抑制的增加會降低字母分辨性（擁擠效應），就像在標準VA測試中，當要辨認的字母周圍有其他字母時。因此，可以預估訓練引起的抑制交互作用的降低能改善視力。這種預計通過訓練期間測試者常規的視力測試加以證實。圖4a顯示3個病人的數據，顯示28次訓練后，空間分辨率得到顯著提高，達到了正常的視力表現(如小于等于6/7.6, Snellen equivalent)。控制組（安慰劑）用高對比度視標，并沒有側翼訓練，顯示沒有提高。在圖4b中我們展示治療組（63人）和控制組（14人）在4個訓練階段的間隔期的組視力分數。
相對于初始閾值，根據空間分辨率的增加是有所記錄的。聯合治療組在頭8次訓練后快速提高35%，隨后相對緩慢的學習速度，在訓練48次后達到78%的增加(0.25 log units)。沒有用側翼視標訓練的控制組分數穩定。用高對比度視標和側翼進行訓練的兩個控制組視力沒有提高。在12次訓練（第一控制組的最后一次試驗）后作兩個獨立組的t-檢驗，顯示對于相應治療組的控制組受試者得出的結果是_0.2% (P _ 0.002)，可能是偶然的。當考慮治療的病人時，在第一治療組44人中只有2人（4.5%有_0.05 LogMAR (0.5 ETDRS lines)的提高，而第一控制組10人中有7人（70%）在這范圍內。控制組有一人提高了0.08 LogMAR，有兩人提高了0.06 LogMAR。在12次訓練后，對兩個治療組（63人）平均提高0.15 _ 0.01 (mean _ SE) LogMAR，而控制組（14人）平均提高0.01 _ 0.02，這差別很明顯（獨立組t-檢驗，P _ 0.0001）。3個控制組受試者（第二組）再訓練12次。治療組的病人在12次到24次中顯著提高30%(from 0.15 _ 0.01 to 0.2 _ 0.01)，三個控制組受試者幾乎沒有提高(from 0.03 _ 0.04 to 0.02 _ 0.04)。
另外，在非訓練任務（如視力）的提高排除了由于訓練任務的特別性的訓練效應引起提高的可能性。這個研究說明了成年弱視者對比度檢測閾值的進步。這種進步只在治療組獲得，他們都是訓練的具有側翼的信號，然而對照組 (n ＝14)在沒有側翼的高和低對比度的GS訓練時沒有一點進步。對于象調節和眼球運動這樣的‘‘front-end’’資源可能是由我們的學習效應引起的假設是不太可能的。弱視眼的視力檢查是在遠視全矯的情況下進行的，這是通過睫狀肌麻痹劑而實現的。而且，視力檢查是在3m距離進行的，這時調節只有1/3屈光度，所以作用是很小的。我們的病人中多數是在調節幅度受到限制的年齡階段（40歲后的弱視患者幾乎就沒有這種能力了）。注視功能的提高也不太能解釋視力的提高，因為偏中心注視的病人是被排除了的。
知覺學習有望成為一種治療成人弱視的主流方法。在年輕的兒童，弱視可以通過早期的遮蓋來治療，這樣通過遮蓋視力較好眼強迫弱視眼發揮作用。通過延長遮蓋好眼的治療被認為在成年弱視是不切實際的。在治療中遮蓋的作用是與年齡呈負相關的。在11~20歲的人群失敗的幾率是0~3歲兒童的7.9倍。治療的成功率有點難估計，因為缺乏公認的定義，但通常在年輕兒童是60%~70%，可以同這里發現的成人成功率比較。這個結果支持使用一個構造的方法來提高成年弱視的視力，目的在于針對弱視者的特別缺損。這里的知覺學習方法有可能可以推廣應用與其他的感覺或非感覺的由于發育問題造成的大腦模塊。Improving Reading Speed for People with Central Vision Loss through Perceptual Learning（原文PDF下載）
From the School of Optometry, University of California, Berkeley, Berkeley, California.
Corresponding author: Susana T. L. Chung, 360 Minor Hall, #2020 Berkeley, CA 94720-2020; [email protected] Abstract
Purpose. Perceptual learning has been shown to be effective in improving visual functions in the normal adult visual system, as well as in adults with amblyopia. In this study, the feasibility of applying perceptual learning to enhance reading speed in people with long-standing central vision loss was evaluated.
Methods. Six observers (mean age, 73.8) with long-standing central vision loss practiced an oral sentence-reading task, with words presented sequentially using rapid serial visual presentation (RSVP). A pre-test consisted of measurements of visual acuities, RSVP reading speeds for six print sizes, the location of the preferred retinal locus for fixation (fPRL), and fixation stability. Training consisted of six weekly sessions of RSVP reading, with 300 sentences presented per session. A post-test, identical with the pre-test, followed the training.
Results. All observers showed improved RSVP reading speed after training. The improvement averaged 53% (range, 34–70%). Comparisons of pre- and post-test measurements revealed little changes in visual acuity, critical print size, location of the fPRL, and fixation stability.
Conclusions. The specificity of the learning effect, and the lack of changes to the fPRL location and fixation stability suggest that the improvements are not due to observers adopting a retinal location with better visual capability, or an improvement in fixation. Rather, the improvements are likely to represent genuine plasticity of the visual system despite the older ages of the observers, coupled with long-standing sensory deficits. Perceptual learning might be an effective way of enhancing visual performance for people with central vision loss.
Previous SectionNext SectionIntroduction
Reading is difficult and slow for many low vision patients, especially those with central vision loss who are obligated to use their peripheral retina to read. The leading cause of visual impairment in developed countries is age-related macular degeneration (AMD),1–3 which is also the leading cause of central vision loss. Because reading is the most common clinical complaint as well as the primary goal for patients with central vision loss seeking visual rehabilitation,1,4,5 improving the reading performance for these patients is a key challenge facing low vision rehabilitation.
Previous studies have examined a number of ways to improve reading performance in people with central vision loss. For instance, in low vision clinics, patients are routinely prescribed with magnifiers for reading tasks. However, even with magnification, reading speed in people with central vision loss is still lower than that at the normal fovea.5–8 Substantial effort has been invested to determine the mode of text presentation that offers people with central vision loss the fastest reading speed, including page format, scrolling-text in the horizontal or the vertical direction, and rapid serial visual presentation (RSVP), where words are presented one at a time on a display. Most studies found no significant differences in reading speed for different text presentation modes for people with central vision loss.9–11 A handful of studies found a small advantage of using RSVP,12 especially if the word presentation rate varied with word length13 or when observers were allowed to adjust their own presentation rate.14 Other attempts have explored whether simple manipulation of text typography and typesetting such as increasing letter spacing15,16 and line spacing,17 which presumably reduces the crowding effect among text, could improve reading speed. Unfortunately, none of these simple manipulations of text typography or typesetting improve reading speed for people with central vision loss.16,17
In this study, I explored the feasibility of using perceptual learning, a method that has proven to be effective in improving visual functions in normal and amblyopic visual systems, to improve reading speed for people with central vision loss. Perceptual learning is defined as “any relatively permanent and consistent change in the perception of a stimulus array, after practice or experience with this array”.18 Practically, perceptual learning is synonymous with “training” or “practice.”19 Previous studies have shown that visual performance improves with practice for a variety of tasks,19–25 in younger as well as in older adults,26,27 and in the normal fovea and periphery alike.19,27–31 In addition, perceptual learning has also shown effectiveness in improving visual functions in adults with amblyopia (monocular sensory loss of vision in the absence of an organic origin).32–38 In many cases, adults with amblyopia improved not only on the trained task, but their visual acuities (an untrained task) also improved as a result of training.33–37 Considering the effectiveness of perceptual learning in improving visual functions in the normal visual system and in adults with amblyopia, I asked whether perceptual learning would also be effective in improving reading performance for people with central vision loss. Clearly, there are many challenges facing the use of perceptual learning in improving visual functions in people with central vision loss. Specifically, the most common cause of central vision loss is AMD,1–3 which primarily afflicts people older than 65 years of age. It is well known that even though visual performance of older adults can improve with practice, more training may be required before the improvement reaches a plateau26 and that there may be more day-to-day lapses in improvement, which would lead to an overall reduction in the amount of learning.27 Also, in contrast to amblyopia, the majority of people with central vision loss suffer from bilateral vision loss and their functioning retina may not be healthy; whether these would impact the effectiveness of perceptual learning for people with central vision loss is unknown. Hence, despite the promising benefits that perceptual learning can deliver, it remains unclear if people with central vision loss can benefit from it. To my knowledge, there exists no published paper on using perceptual learning to improve visual functions in people with central vision loss, although previous studies have examined whether or not reading performance could be improved by training comprehension,39 or training patients to use a CCTV or stand magnifier to read.40,41 Comprehension training is a cognitive task, and the use of a CCTV or stand magnifier requires motor skills, making it unclear that any improvement from these training represents genuine improvement in the sensory system, which is the basis of perceptual learning. The goal of this study was to determine the feasibility of using perceptual learning to improve reading speed for people with central vision loss.
Previous works have established that reading performance in the normal periphery benefits from perceptual learning based on the following training tasks: identifying random sequences of three letters at various positions across the visual field,19,27,31 performing a lexical decision task,31 and reading.31 The greatest improvement in reading speed was obtained using reading as the training task.31 Consequently, reading was used as the training task in this study.
Previous SectionNext SectionMethods
Six observers with central vision loss, including four with AMD and two with Stargardt disease, participated in this study. All had long-standing central vision loss (minimum 7 years, see Table 1). Entering visual acuities and other characteristics of the observers are given in Table 1. Although all were avid readers or had the need to read constantly before their vision loss, all observers had stopped reading on a regular basis long before their participation in this study because of their visual deficits. Subjects (S)1 through S3 had previously participated in another study in the laboratory (2–3 hours) in which RSVP was used to measure how reading speed changed with some text manipulation; while S4–S6 had no prior exposure to RSVP reading. All observers gave written informed consent before the commencement of data collection. This research followed the tenets of the Declaration of Helsinki and was approved by the Committee for Protection of Human Subjects at the University of California, Berkeley.
The basic experimental design consisted of a pre-test, six sessions of training, followed by a post-test. The pre-test consisted of measurements of monocular visual acuities, the location of the preferred retinal locus for fixation (fPRL) and fixation stability, and measurements of reading speed as a function of print size using the rapid serial visual presentation (RSVP) paradigm. Details of these procedures are given below. From the reading speed versus print size data obtained at the pre-test, the critical print size, the smallest print size at which maximum reading speed could still be attained, was determined.42 The print size used for training corresponded to 1.4× the critical print size.19 For S1–S5, training consisted of six weekly sessions of RSVP reading. It was shown previously that in the normal periphery, the improvement after perceptual learning was not different whether observers were trained on a daily or a weekly basis,43 justifying my choice of a weekly training schedule in this study, which was more convenient for observers with central vision loss. In each session, observers read a total of 300 sentences, divided into 10 blocks of 30 trials each. Reading speed was determined for each block of 30 trials (average number of words presented per block = 326.3 ± 8.7 [SD]). S6 could complete only seven blocks in the first training session, and eight in each of the subsequent sessions, for a total of 47 blocks over the course of six training sessions. Also, because of his work schedule and illness, he had a three-week gap between training sessions 3 and 4. The post-test, identical with the pre-test except that all measurements were conducted in reversed order, took place a week after the last training session.
Visual Acuity Measurements
Visual acuity was measured monocularly using the Bailey-Lovie high-contrast letter acuity chart.44 Acuities were scored on a letter-by-letter basis, with each letter scoring 0.02 log units.45 All observers were tested at a distance of 10 ft, except for S6 who was tested at 5 ft because of his poorer acuities.
Location of fPRL and Fixation Stability Measurements
The retinal locations used for fixation, and fixation stability of each observer were determined using a scanning laser ophthalmoscope (Rodenstock 101; Rodenstock, Munich, Germany). Observers were asked to look at the center of a fixation cross subtending 1° (2° for observer S6) using their preferred eye. Fundus images were captured continuously for 30 s at a frame rate of 30 Hz. Offline analyses were performed using custom-written software in MATLAB (Mathworks, Natick, MA), and included a frame-by-frame analysis of the retinal locations that the observer used to fixate the cross, and the variability of eye position from frame to frame. To quantify fixation stability, I adopted the conventional method of calculating the bivariate contour ellipse area (BCEA, in deg2)46–49 over each trial of 30 s, which refers to the area of the retinal surface on which the fixation target was imaged 68% of the time. The BCEA value reported in this article, for each observer and for the pre- or post-test, represents the averaged values of two or three trials, collected a few minutes apart.
Reading Speed Measurements
Oral reading speed for single sentences was measured binocularly using the RSVP paradigm. The procedures were very similar to those used in previous studies.15,19,30,42 In brief, on each trial, a single sentence was chosen randomly from a pool of 2630 sentences. Each sentence contained between 8 and 14 words (mean, 10.9 ± 1.7 [SD]) and included only words that were among the 5000 most frequently used words in written English, according to word-frequency tables derived from the British National Corpus.50 Words were rendered in Times Roman font and were presented left-justified on the display, one word at a time in rapid succession, each for a fixed exposure duration. For each block of trials, the Method of Constant Stimuli was used to present sentences at five or six word exposure durations (five for all training sessions, five or six for pre-tests and post-tests depending on observers). The number of words read correctly was recorded for each sentence. A cumulative-Gaussian function was used to fit each set of data (based on 30–36 sentences presented) relating the percentage of words read correctly as a function of exposure duration, from which the reading speed based on the word exposure duration that yielded 80% of the words read correctly was derived.
For the pre- and post-tests, reading speeds were determined for six print sizes spanning 0.75 log units in range, for each observer. A two-line fit (on log-log axes) was used to fit each set of reading speed versus print size data,15,19,30,42 with the slope of the second line constrained to zero. The intersection of the two lines represents the critical print size. The height of the second line (slope = 0) gives the maximum reading speed.
Text stimuli were generated using a Visual Stimulus Generator graphics board (VSG 2/5; Cambridge Research Ltd, Rochester, UK) controlled by a workstation (Dell Precision 650; Dell, Austin, TX) and presented on a 24-inch color graphics display monitor (Model# GDM-FW900; Sony, New York, NY). The resolution of the display was 1280 × 960 pixels, at a frame rate of 80 Hz. The temporal dynamics of the display were verified using a photo-detector and an oscilloscope. Stimuli were black text (2 cd/m2) presented on a white background (144 cd/m2).
Previous SectionNext SectionResults
Reading speed (words per minute, wpm) measured using RSVP, is plotted as a function of training block in Figure 1 for each observer. All observers showed improved reading speed with training, although there was substantial individual observer variability. In particular, while the improvement of observer S1 reached a plateau after the first training session, observer S4 continued to improve over the course of the training. The change in reading speed with training can be described by an exponential function of the form (smooth line drawn through each set of data in Fig. 1): where y0 is the asymptotic reading speed with sufficient training, A is the maximum improvement in reading speed due to training and τ is the time constant. To quantify the improvement, the ratio of reading speed between the last and the first block of training was calculated based on the fitted values. Across the six observers, this ratio ranges between 1.34 and 1.70, with an average of 1.53. In other words, the average improvement in reading speed after six sessions of training was 53% (paired t-test on log reading speed: t(5) = 12.46, P < 0.0001).
An alternative way to quantify the improvement in reading speed due to training is to compare the maximum reading speed derived from the reading speed versus print size plots before and after training. Such plots are shown in Figure 2 for all six observers. The straight lines in each plot represent the two-line fit. The ratio of the maximum reading speed (the plateau of the two-line fit) after and before training averages 1.55, representing a significant improvement in reading speed (paired t-test on log reading speed: t(5) = 8.24, P = 0.0004). This improvement can also be visualized in Figure 3A, in which the pre- and post-maximum reading speeds are compared for all observers. The dashed line represents the 1:1 line, indicating no change in the maximum reading speed before and after training. All the data points lie above the 1:1 line, implying that the maximum reading speeds improved after training for all observers.
A characteristic of perceptual learning is its specificity.20,21,23,30 To examine if the training effect transfers to an improvement in critical print size and/or visual acuity, the pre- and post-test critical print size and visual acuities were compared in Figures 3B and 3D were compared. Clearly, all data points fall very close to the 1:1 line, implying that neither the critical print size (averaged post/pre ratio = 1.0; paired t(5) = 0.95, P = 0.38) nor the visual acuity (averaged post/pre ratio = 0.99; paired t(11) = 1.17, P = 0.27) changed after training.
To determine whether the improvement in reading speed was due to observers adopting a different PRL with better visual capabilities, or that observers learned to maintain steadier fixation, the location of the fPRL and fixation stability of each observer before and after training were compared. Figure 4 shows the fixation frequency distribution—the frequency distribution of the retinal locations used for fixation—superimposed on the fundus image, for each observer, before and after training. Clearly, the region over which most of the fixation occurred (roughly representing the fPRL), and the spread of the region, did not change substantially before and after training. To quantify the fixation stability, the conventional measurement of BCEA was adopted.46–49 Figure 3C shows that the BCEA (in deg2) of the observers was practically the same before and after training (paired t(5) = 0.13, P = 0.90), suggesting that the improvement in reading speed after training cannot be attributed to the adoption of a different PRL with better visual capabilities or the oculomotor system becoming more stable.Discussion
After six weekly sessions of repeated training on an RSVP reading task, observers with central vision loss were able to improve their reading speeds by an average of 53%. This improvement did not transfer to visual acuity and critical print size measurements, implying that even though observers were able to read faster, they were not able to read smaller letters on an acuity chart or text of smaller sizes. The improvement cannot be attributed to a change in the location of the fPRL or better oculomotor control (steadier fixation). These results provide evidence for neural plasticity in human adults with long-standing central vision loss.
Neural plasticity in adults with sensory visual deficits is not at all a new concept. For over a decade, many studies have reported that human adults with amblyopia benefit from perceptual learning, in that many visual functions, including visual acuity, can improve through training.32–38 Because of the substantial benefits, perceptual learning has recently been proposed as a treatment for adult amblyopia.37,38 With respect to people with central vision loss, it is well known that after the loss of central vision, many of these individuals eventually adopt a retinal location (sometimes more than one) outside the afflicted macular area to serve as the PRL.51–58 This in itself is strong evidence that even for people with central vision loss, many of whom are elderly suffering from AMD, the visual cortex is still malleable and able to adapt to unfavorable visual experience. Therefore, it is not surprising that these people can benefit from perceptual learning.
Perceptual learning is known for its specificity,20,21,23,30 a characteristic that distinguishes itself from general practicing of a task. In this study, the specific improvements related to reading speed, but not to visual acuity or fixation stability, lend support to the argument that the observed improvements are indeed the consequence of perceptual learning, rather than to general training, the continued adaptation to the vision loss, or recent changes in central vision. Given the specificity of the improvements, an important and practical question that follows is whether the improvement in RSVP reading speed would generalize to the conventional page-reading task. Because page-reading requires more eye movements (inter-word saccades and return sweeps) than RSVP reading, it is possible that improvements in RSVP reading speed may not generalize to page-reading if eye-movement control is the primary limiting factor on page-reading. However, compared with people with intact central vision, patients with central vision loss do not benefit as much from RSVP reading, suggesting that the limitation of eye movements on reading may not be as important for people with central vision loss as for people with intact central fields. Further, there is evidence that RSVP and page-format reading show similar dependence on certain text parameters such as letter spacing.59 Therefore, it would be interesting to test in future studies whether improvements after RSVP training would transfer to page-reading, and whether RSVP training and page-reading training are equally effective in improving reading speed for patients with central vision loss.
Another characteristic of perceptual learning is the substantial individual observer variability with respect to the time course and the amount of improvement. In fact, it has been shown that up to 25–50% of observers failed to show improvement after training.29,60 In the present study, the six observers demonstrated variability in their time course of improvement (Fig. 1), arguing that a tailored amount of training for individual observers may be more appropriate than a one-size-fits-all approach. This is an important issue to resolve, not only from a scientific point of view, but also because the results may directly influence policy-makers in deciding on the number of training sessions that should be covered by health care plans, should perceptual learning be adopted as a rehabilitative option for patients with central vision loss.
Given these results, a logical question to ask is what underlies the improvements. A psychophysical approach to answer this question is to evaluate how observer performance is affected by the presence of different amount of external noise superimposed on the stimulus. The basis of this approach is to attribute the limitation in human performance to (1) the presence of internal noise in the visual system that limits the precision of perceptual responses and (2) the inability of the visual system to make full use of the information available in the stimulus.24,25,29,61,62 The mechanism underlying perceptual learning can then be inferred, by tracking how performance changes with different levels of external noise with time. In this study, because reading performance in the presence of external noise was not measured, the functional mechanism that underlies learning could not be inferred. However, based on previous studies for a variety of training tasks, the improvement after training is most likely due to the visual system being more capable of extracting the crucial information from the stimulus.24,25,29,61,62
A few caveats should be kept in mind while evaluating the interpretations presented here. First, I showed that the location of the fPRL did not change substantially after training. Because people with central vision loss can adopt different PRLs for different tasks,51–58 the data presented in this study cannot convincingly rule out the possibility that observers adopt an alternative retinal location that has better visual capability for the reading task. Currently, a larger-scale perceptual learning study is being designed. It will include the PRL for reading as a pre-post comparison measurement. Note that the measurements of fPRL were made monocularly, while the training was performed binocularly; therefore, it is also plausible that the characteristics of the binocular PRL could have changed as a result of training. Unfortunately, there is currently no known method to measure the binocular PRL. Second, considering that this was a feasibility study, a no-training control group was not included. However, it is easy to envision that a no-training control group is unlikely to show improvement because in real life, patients with central vision loss almost never show improvement in reading performance without practicing the use of their residual vision. A rough estimate of the improvement shown by a no-training control group based on simply performing the RSVP reading task twice (pre- and post-test) was 7–10%, as reported in previous studies.19,31 Considering that observers who receive training spend more time in the laboratory than those who do not receive any training, to control for the time spent in the laboratory, or the amount of interaction with laboratory personnel and the attention received, a better control design is to train another group of observers on a task that is unrelated to the training task being studied. In a previous study,31 three groups of normally sighted observers were trained on three different psychophysical tasks — lexical decision, trigram letter recognition, and RSVP reading, for a similar amount of time. A fourth group of observers did not receive any training. The group that was trained on RSVP reading yielded the largest magnitude of improvement (averaged 72%) while the improvements for the other two training groups averaged 40–50%, with the improvement for the no-training group being 10%. The differential magnitudes of improvement for the different training groups confirm that the improvements after training on an RSVP task are not due to psychological or general improvements because the observers spent long periods of time in the laboratory or because they received lots of attention from the laboratory personnel. Also, the largest magnitude of improvement exhibited by the RSVP training group is consistent with the specificity of perceptual learning,20,21,23,30 rather than just an improvement due to general training on any psychophysical tasks.
Clearly, if perceptual learning is to be used clinically to benefit patients with central vision loss, other issues have to be considered. For example, does the improvement after RSVP training transfer to a real-life page-reading task that involves a higher oculomotor demand? Will other modes of reading such as large-print page-reading be equally effective as a training task? Should the amount of training be tailored to each individual observer instead of giving the same amount of training to all observers? What is the optimal training duration? Does the improvement in reading speed also help improve the comprehension of the reading materials? These are all interesting questions which will be addressed in future studies.