Clinical Review

1. Background

Vision is limited by two main factors: (a) the quality of the image that is transferred from the eye, and (b) the neural processing in the brain, which needs to integrate information between different neurons located at neighboring brain locations  (space).  Cortical cells (neurons) are highly specialized and optimized as image analyzers. Thus, to characterize an image, visual processing involves  the cooperative activity of many  neurons—those neuronal interactions contributing to both excitation and inhibition.  The integration of image parts should be performed very quickly, since the time-window in which the first percept is formed is very short. Thus, visual information processing may be limited if the first  percept representation is inefficient either due  to slow neural processing or  to  the lack of effective interactions between the neurons.

1.1. Contrast sensitivity

Contrast sensitivity (CS), i.e., the ability to discriminate between shades of gray, is one of the main determinants of how well people see. It is assumed that the contrast sensitivity function (CSF) describes the combined response of the classical receptive fields of simple cells that have been selectively tuned for location, orientation, and spatial frequency and constitute the fundamental units of analysis. (Wilson, 1991; Wilson & Wilkinson, 1997). Thus, CSF describes the output of an early stage that provides the building blocks for the succeeding steps of visual processing.

During  the  last  two  decades,  it  was  demonstrated  that  contrast  response  is  also determined by lateral interactions in the visual cortex of humans (Bonneh & Sagi, 1999; Cass & Alais, 2006; Cass & Spehar, 2005; Ellenbogen, Polat, & Spitzer, 2006; Polat & Norcia, 1996; Polat & Sagi, 1993, 1994a, 1994b, 2006; Shani & Sagi, 2006; Solomon & Morgan,  2000;  Tanaka  &  Sagi,  1998;  Woods,  Nugent,  &  Peli,  2002) and of  animals (Crook, Engelmann, & Lowel, 2002; Kapadia, Ito, Gilbert, & Westheimer, 1995; Mizobe, Polat,) Visual acuity (VA) is the most common clinical measurement of visual function and is considered  as  the  gold  standard  measure  of  visual  functions.  VA  measures the ability to identify black symbols on a white background at a standardized distance as the size of the symbols  is varied. A person with standard (normal) VA can recognize a letter that is specified as 6/6 (20/20).

1.2. Neural plasticity and perceptual learning

Visual plasticity is the  ability of the visual system to change its  responses in order  to adapt to changes in the visual input. Evidence for plasticity in the adult visual system has been reported in human studies that have demonstrated that  training in specific  visual tasks  leads  to  improvement  in  performance  or  sensitivity  (for  a  review,  see (Fahle & Poggio, 2002)). Perceptual learning has a major  influence on our understanding of the development and plasticity of the visual system. Improvement after perceptual learning was demonstrated using a variety of visual tasks showing that the adult visual system can change according to behavioral demands (Fahle, 2005; Fiorentini & Berardi, 1980; Polat & Sagi, 1994b; Sagi & Tanne, 1994). (For a review, see Fahle (2002), Fahle and Poggio (2002), Gilbert, Sigman, and Crist (2001), Sagi and Tanne (1994).

1.3. Plasticity in amblyopia

Amblyopia is a reduction of visual functions that cannot be directly attributed to  the effect of any structural abnormality of the eye or the posterior visual pathway. It is caused by abnormal binocular visual experience early in life, during the ‘critical  period’  that prevents normal development of the visual  system. A generally practiced  principle of treatment is that therapy can only be effective during the critical period,  usually considered to end around the age of 8–9 (Greenwald & Parks, 1999; Prieto-Diaz, 2000; von Noorden, 1981), when the visual system is considered sufficiently plastic for cortical modifications to occur. The standard amblyopia therapy is thus traditionally  directed toward children and consists of penalizing the preferred eye by using an eye  patch or atropine, thus forcing the brain to use the visual input from the amblyopic eye. However, in adults, the visual deficiencies are thought to be irreparable after the first decade of life, once the developmental maturation window has been terminated;  thus the standard treatment is usually not offered.  However, recovery of visual  functions in adults with amblyopia after occlusion therapy (Birnbaum, Koslowe, & Sanet, 1977; Simmers, Gray, McGraw, & Winn, 1999; Wick, Wingard, Cotter, &  Scheiman, 1992) or after loss of vision in the good eye (El Mallah, Chakravarthy, & Hart, 2000) was reported. The first step in a series of controlled studies that provided evidence for plasticity, after perceptual learning, in adults with amblyopia used training for the vernier acuity task (Levi & Polat, 1996; Levi, Polat, & Hu, 1997b). Repetitive practice led to a substantial improvement in vernier acuity in the  amblyopic eyes  of  adults with amblyopia. In two observers, the improvement in vernier acuity was accompanied by a commensurate improvement in VA reaching up to normal vision. These studies provided an optimistic possibility for future treatment of amblyopia  based on perceptual learning. Recent studies have provided additional evidence for  plasticity in adults with amblyopia  (Chung,  Li,  &  Levi,  2006; Fronius,  Cirina,  Cordey,  &  Ohrloff,  2005;  Fronius,  Cirina,  Kuhli,  Cordey,  &  Ohrloff, 2006; Levi, 2005; Li & Levi, 2004; Polat et al., 2004; Zhou et al., 2006).

1.4. Improving normal visual functions

Some insight into the mechanism underlying neural plasticity, which may improve  the contrast sensitivity, comes from lateral masking experiments (Polat & Sagi, 1994b, 1995; Polat et al., U. Polat / Vision Research 49 (2009) 2566–2573 2567 2004). These studies suggest that practice on lateral interactions increases the efficacy of the  collinear interactions between neighboring neurons, an effect that  enables connectivity with remote neurons via a cascade of local interactions. Thus,  the results suggest a possible tool for the use of lateral interactions for improving CS in people with normal vision and in people with impaired lateral interactions such as amblyopia.  Polat has developed a perceptual learning procedure that was designed  to improve the abnormal lateral interactions in amblyopia by stimulating the deficient  neuronal populations and effectively promoting their collinear interactions (Polat,  2006, 2008; Polat et al., 2004). Since the amblyopic deficit is not identical among subjects (Bonneh, Sagi, & Polat, 2004; Bonneh et al., 2007; Polat, 2008; Polat et al., 2005), the treatment was tailored and specifically designed for each individual’s deficiencies.

1.5. Improvement of lateral interactions in amblyopia

Amblyopes exhibit abnormal lateral interactions (Bonneh et al., 2004, 2007; Ellemberg et al., 2002; Levi et al., 2002; Polat, 2006, 2008; Polat et al., 2004). The lateral interaction function of the amblyopes at the beginning of the treatment showed no facilitation and in fact, increased the amount of suppression. However, after the treatment, the amount of suppression was significantly reduced to a normal level (Polat, 2008; Polat et al., 2004).

1.6. Improvement of CSF in amblyopia

In the study of Polat et al. (2004), the amblyopic eyes exhibit the typical lower CS before treatment, as compared with normal sighted eyes, with the low spatial frequencies near the normal values and the high spatial frequencies showing a worse deficit. The treatment produced a significant improvement in sensitivity, by about a factor of two, in all spatial frequencies including the high spatial frequency range, raising the function to within the normal  (lower) range. Most interesting is the result that after 12 months, CSF was not only retained, but it also increased toward an average range at the high spatial frequencies. This result suggests that the  high spatial frequencies are used after the treatment in daily tasks and thus are naturally practiced.

1.7. Improvement of CSF in non-amblyopic groups

The  procedure  of  Polat  et  al.  (2004),  when  applied  to  people  with  normal  vision  or corrected to normal vision, improved their visual acuity to better than 66.  It has  been recently applied to improve the vision of people with low myopia (Tan & Fong, 2008). The vision of myopic (short  sighted) subjects is blurred without optical  correction. Therefore, the CSF is reduced, especially at the higher spatial frequencies,  when compared with people with corrected vision. This reduction in CS is reminiscent of the CS of amblyopic subjects. This study used a protocol similar to the one used for  the amblyopia (Polat et al., 2004); it showed that when subjects practiced with  uncorrected moderate myopia it improved their CS. Thus, even in cases when the lateral interactions are normal (low myopia), training improves CS.

1.8. Improvement of VA

The VA was found to improve after training on contrast detection  of amblyopes (Polat et al.,  2004), anisometropic amblyopes  (Huang  et  al.,  2008;  Zhou  et  al.,  2006), and  after training on verneir acuity (Levi & Polat, 1996; Levi, Polat, & Hu, 1997a). The training of low myopia on lateral interactions also shows improvement of VA (Tan & Fong, 2008). Thus, the training  can be generalized to the letter recognition task (VA), an effect that supports the relationships between these perceptual tasks and letter recognition.

1.9. Transfer to improvement of binocular vision

In the studies of Polat and colleagues, during the treatment, the fellow eye was covered; thus the treatment was monocular, targeting the abnormal lateral  interactions of the amblyopic eye. Very surprisingly, after treatment, the binocular  functions improved, indicating that both the binocular fusion and the stereo acuity  improved (Polat, 2006, 2008). A significant improvement in stereoacuity was also found in a retrospective study (Lichter, 2007).

1.10. Additional indications for function improvement.

In addition to Amblyopia and Myopia, several other conditions that cause reduced VA were studied. Presbyopic patients showed an increase of 1.5 to 2 lines and an increase of close to 100% in CS following treatment (Polat 2009; Tan 2005; Stahl & Durrie 2008;  Durrie & McMinn, 2007). Patients who have undergone refractive surgery have shown  similar results (Tan 2005, Waring IV et al., unpublished data). Patients who have  undergone intra-ocular-lens (IOL) implant surgery following cataract extraction  showed high CS improvement and an increase of 1 to 1.5 lines of VA in a variety of  monofocal and multifocal or accommodating IOLs (Waring IV et al. 2010). A possible positive treatment outcome in myopia control is suggested by seminal work done on school children (Chua et al. 2007), and although this is yet to be determined by a randomized double blind controlled study, over several years, the current  findings suggest optimistic outcomes.

Due to the promising findings in the above studies and in light of the fact that  the treatment is safe and non-invasive, several practitioners have used this treatment  in managing several types of ocular pathologies. Among others these include:  congenital nystagmus  (CN)  (Morad 2012), age related macular degeneration, retinitis  pigmentosa (Lyra,  2009) pathological myopia and congenital stationary  night blindness. A retrospective multicenter study which is being carried out during this year has already showing positive results in cases of CN.

1.11. Persistence of the improved functions

Different studies measured the persistence of the results over a retention period. While amblyopia  showed  a  surprising  increase  in  CS  function  over  time  (Polat  et  al  2004), others showed a mild regression of about 15% of the treatment effect over the first six months post treatment. However, in the following eighteen months of retention no further regression  was  noted  (Siow  &  Tan,  2008).  Studies  aimed  at  presbyopia  and  post refractive correction procedures have shown no regression over twelve months retention (Tan et al. 2005, Ng et al. 2007)

References

Albrecht, D. G. (1995). Visual cortex neurons in monkey and cat: Effect of contrast  on

the  spatial  and  temporal  phase  transfer  functions.  Visual  Neuroscience,  12(6),  1191– 1210.

Birnbaum, M. H., Koslowe, K., & Sanet, R. (1977). Success in amblyopia therapy as a

function of age: A literature survey.  American Journal of Optometry and  Physiological

Optics, 54(5), 269–275.

Bonneh,  Y.,  &  Sagi,  D.  (1999).  Configuration  saliency  revealed  in  short  duration

binocular rivalry. Vision Research, 39(2), 271–281.

Bonneh, Y. S., Sagi, D., & Polat, U. (2004). Local and non-local deficits in amblyopia:

Acuity and spatial interactions. Vision Research, 44(27), 3099–3110.

Bonneh, Y. S., Sagi, D., & Polat, U. (2007). Spatial and temporal crowding in amblyopia.

Vision Research, 47(14), 1950–1962.

Breitmeyer, B. G. (1984).  Visual masking: an integrative approach.  Oxford Psychology

series (vol. 4). New York: Oxford University Press.

Breitmeyer, B. G., & Ogmen, H. (2000). Recent models and  findings in visual  backward

masking: A comparison, review, and update. Perception and Psychophysics, 62(8), 1572– 1595.

Carrasco,  M.,  Penpeci-Talgar,  C.,  &  Eckstein,  M.  (2000).  Spatial  covert  attention

increases  contrast  sensitivity  across  the  CSF:  Support  for  signal  enhancement.  Vision Research, 40(10–12), 1203–1215.

Carrasco, M., Williams, P. E., & Yeshurun, Y. (2002). Covert attention increases  spatial

resolution  with  or  without  masks:  Support  for  signal  enhancement.  Journal  of  Vision, 2(6), 467–479.

Cass, J., & Alais, D. (2006). The mechanisms of collinear integration.  Journal of Vision,

6(9), 915–922.

Cass, J. R., & Spehar, B. (2005). Dynamics of collinear contrast facilitation are consistent

with long-range horizontal striate transmission. Vision Research, 45(21), 2728–2739.

Chandna, A., Pennefather, P. M., Kovacs, I., & Norcia, A. M. (2001). Contour integration

deficits  in  anisometropic  amblyopia.  Investigative  Ophthalmology  &  Visual  Science,

42(3), 875–878.

Chua WH Tan D Fong A    (2007)  Enhancement of  Under Corrected Visual Acuity and

Contrast Sensitivity in Myopic Children Using NeuroVision’s Neural Vision Correction

(NVC) Technology ARVO 2007

Chung,  S.  T.,  Legge,  G.  E.,  &  Tjan,  B.  S.  (2002).  Spatial-frequency  characteristics  of

letter identification in central and peripheral vision. Vision Research, 42(18), 2137–2152.

Chung, S. T., Levi, D. M., & Legge, G. E. (2001). Spatial-frequency and contrast

properties of crowding. Vision Research, 41(14), 1833–1850.

Chung, S. T., Li, R. W., & Levi, D. M. (2006). Identification of contrast-defined letters

benefits  from  perceptual  learning  in  adults  with  amblyopia.  Vision  Research,  46(22), 3853–3861.

Chung, S. T., Mansfield, J. S., & Legge, G. E. (1998). Psychophysics of reading. XVIII.

The effect of print size on reading speed in normal peripheral vision. Vision

Research, 38(19), 2949–2962.

Crook, J. M., Engelmann, R., & Lowel, S. (2002). GABA-inactivation attenuates colinear

facilitation in cat primary visual cortex. Experimental Brain Research, 143(3), 295–302.

Durrie  D,  McMinn  PS.  (2007)  Computer-based  primary  visual  cortex  training  for

treatment of low myopia and early presbyopia. Trans Am Ophthalmol Soc. 2007;105:132-8; discussion 138-40.

El Mallah, M. K., Chakravarthy, U., & Hart, P. M. (2000). Amblyopia: Is visual loss

permanent? British Journal of Ophthalmology, 84(9), 952–956.

Ellemberg, D., Hess, R. F., & Arsenault, A. S. (2002).  Lateral interactions in amblyopia.

Vision Research, 42(21), 2471–2478.

Ellenbogen, T., Polat, U., & Spitzer, H. (2006).  Chromatic collinear facilitation, further

evidence for chromatic form perception. Spatial Vision, 19(6), 547–568.

Fahle, M.  (2002). Perceptual learning: Gain without pain?  Nature Neuroscience,  5(10),

923–924.

Fahle, M. (2005). Perceptual learning: Specificity versus generalization. Current  Opinion

in Neurobiology, 15(2), 154–160.

Fahle, M., & Poggio, T. (2002). Perceptual learning. Cambridge, MA: MIT Press.

Fahle,  M.,  &  Skrandies,  W.  (1994).  An  electrophysiological  correlate  of  learning  in

motion perception. German Journal of Ophthalmology, 3(6), 427–432.

Fiorentini,  A.,  &  Berardi,  N.  (1980).  Perceptual  learning  specific  for  orientation  and spatial frequency. Nature, 287(5777), 43–44.

Flom, M. C., Weymouth, F. W., & Kahneman, D. (1963). Visual resolution and  contour

interaction. Journal of the Optical Society of America, 53(9), 1026–1032.

Fronius, M., Cirina, L., Cordey, A., & Ohrloff, C. (2005). Visual improvement    during

psychophysical  training  in  an  adult  amblyopic  eye  following  visual  loss  in  the

contralateral  eye.  Graefe’s  Archive  for  Clinical  and  Experimental  Ophthalmology,

243(3), 278–280.

Fronius, M., Cirina, L., Kuhli, C., Cordey, A., & Ohrloff, C. (2006). Training the adult

amblyopic  eye  with  ‘‘perceptual  learning”  after  vision  loss  in  the  non-amblyopic  eye.

Strabismus, 14(2), 75–79.

Gilbert, C. D., Sigman, M., & Crist, R. E. (2001). The neural basis of perceptual learning.

Neuron, 31(5), 681–697.

Greenwald, M. J., & Parks, M. M. (1999). Treatment of amblyopia. In T. Duane (Ed.).

Clinical ophthalmology (Vol. 1). Hagerstown: Harper and Row.

Hariharan, S., Levi, D. M., & Kelin, S. A. (2005). ‘‘Crowding” in normal and amblyopic

vision assessed with Gaussian and Gabor C’s. Vision Research, 45(5), 617–633.

Harwerth,  R.  S.,  &  Levi,  D.  M.  (1978).  Reaction  time  as  a  measure  of  suprathreshold grating detection. Vision Research, 18(11), 1579–1586.

Hess,  R.  F.,  McIlhagga,  W.,  &  Field,  D.  J.  (1997).  Contour  integration  in  strabismic

amblyopia:  The  sufficiency  of  an  explanation  based  on  positional  uncertainty.  Vision Research, 37(22), 3145–3161.

Hirsch, J. A., & Gilbert, C. D. (1991). Synaptic physiology of horizontal connections in

the cat’s visual cortex. Journal of Neuroscience, 11(6), 1800–1809.

Huang, C. B., Zhou, Y., & Lu, Z. L. (2008).  Broad bandwidth of perceptual learning in

the visual system of adults with anisometropic amblyopia.  Proceedings of the  National Academy of Sciences USA, 105(10), 4068–4073.

Kapadia, M. K., Ito, M., Gilbert, C. D., & Westheimer, G. (1995). Improvement in visual

sensitivity by changes in  local context: Parallel studies in human  observers and in V1 of alert monkeys. Neuron, 15(4), 843–856. 2572 U. Polat / Vision Research 49 (2009) 2566–2573 Kovacs, I., Polat, U., Pennefather,

M., Chandna, A., & Norcia, A. M. (2000). A new test of contour integration deficits in

patients  with  a  history  of  disrupted  binocular  experience  during  visual  development. Vision Research, 40(13), 1775–1783.

Legge,  G.  E.,  Mansfield,  J.  S.,  &  Chung,  S.  T.  (2001).  Psychophysics  of  reading.XX.

Linking  letter  recognition  to  reading  speed  in  central  and  peripheral  vision.  Vision Research, 41(6), 725–743.

Legge,  G.  E.,  Pelli,  D.  G.,  Rubin,  G.  S.,  &  Schleske,  M.  M.  (1985).  Psychophysics  of

reading – I. Normal vision. Vision Research, 25(2), 239–252.

Levi,  D.  M.  (2005).  Perceptual  learning  in  adults  with  amblyopia:  A  reevaluation  of critical periods in human vision. Developmental Psychobiology, 46(3), 222–232.

Levi,  D.  M.,  Hariharan,  S.,  &  Klein,  S.  A.  (2002).  Suppressive  and  facilitatory  spatial interactions in amblyopic vision. Vision Research, 42(11), 1379–1394.

Levi,  D.  M.,  &  Li,  R.  W.  (2009).  Perceptual  learning  as  potential  treatment  for

amblyopia: A mini-review. Vision Research., 49(21), 2535–2549.

Levi, D. M., & Polat, U. (1996). Neural plasticity in adults with amblyopia.  Proceedings

of the National Academy of Sciences USA, 93(13), 6830–6834.

Levi, D. M., Polat, U., & Hu, Y. S. (1997a). Improvement in vernier acuity in adults with

amblyopia. Investigative Ophthalmology & Visual Science, 38(8), 1493–1510.

Levi,  D.  M.,  Polat,  U.,  &  Hu,  Y.  S.  (1997b).  Improvement  in  Vernier  acuity  in  adults with amblyopia. Practice makes better.  Investigative Ophthalmology & Visual  Science, 38(8), 1493–1510.

Levi, D. M., Song, S., & Pelli, D. G. (2007). Amblyopic reading is crowded.  Journal  of

Vision, 7(2), 21. 21–17.

Levitt,  H.  (1971).  Transformed  up-down  methods  in  psychoacoustics.  Journal  of  the Acoustical Society of America, 49(Suppl. 2), 467+.

Li,  R.  W.,  &  Levi,  D.  M.  (2004).  Characterizing  the  mechanisms  of  improvement  for position discrimination in adult amblyopia. Journal of Vision, 4(6), 476–487.

Liu, L., Wang, K., Liao, B., Xu, L., & Han, S. (2004). Perceptual salience of global

structures and the crowding effect in amblyopia.  Graefe’s Archive Clinical  Experimental Ophthalmology, 242(7), 566–570.

Livne,  T.,  &  Sagi,  D.,  (2007)  Configuration  influence  on  crowding.  Journal  of  Vision, 7(2): 4, 1–12.

LyraJ.M. (2009), Neuroplasticity, key to vision recovery. AAO 2008. ESCRS 2009

Majaj, N. J., Pelli, D. G., Kurshan, P., & Palomares, M. (2002). The role of spatial

frequency channels in letter identification. Vision Research, 42(9), 1165–1184.

Mizobe,  K.,  Polat,  U.,  Pettet,  M.  W.,  &  Kasamatsu,  T.  (2001).  Facilitation  and

suppression  of  single  striate-cell  activity  by  spatially  discrete  pattern  stimuli  presented beyond the receptive field. Visual Neuroscience, 18(3), 377–391.

Nazarul  M, Fong  A., Tan  D.,  A Randomised Controlled Trial Evaluating the Efficacy of

Neurovision’s Neural Vision Correction Technology in Enhancing Unaided Visual Acuity

in Adults with Low Myopia ARVO 2008

O’Regan, J. K. (1990). Eye movements and reading.  Reviews of Oculomotor Research,

4, 395–453.

Parkes, L., Lund, J., Angelucci, A., Solomon, J. A., & Morgan, M. (2001).  Compulsory

averaging  of  crowded  orientation  signals  in  human  vision.  Nature  Neuroscience,  4(7), 739–744.

Patching, G. R., & Jordan, T. R. (2005). Spatial frequency sensitivity differences between

adults of good and poor reading ability.  Investigative Ophthalmology &  Visual Science,

46(6), 2219–2224.

Pelli, D. G., Palomares, M., & Majaj, N. J. (2004). Crowding is unlike ordinary masking:

Distinguishing feature integration from detection. Journal of Vision, 4(12), 1136–1169.

Peli, E., Arend, L. E., Young, G. M., & Goldstein, R. B. (1993). Contrast sensitivity to

patch  stimuli:  Effects  of  spatial  bandwidth  and  temporal  presentation.  Spatial  Vision, 7(1), 1–14.

Petrov, Y., & McKee, S. P. (2006). The effect of spatial configuration on surround

suppression of contrast sensitivity. Journal of Vision, 6(3), 224–238.

Plainis, S., & Murray, I. J. (2005). Magnocellular channel subserves the human   contrastsensitivity function. Perception, 34(8), 933–940.

Polat,  U.  (1999).  Functional  architecture  of  long-range  perceptual  interactions.  Spatial Vision, 12(2), 143–162.

Polat,  U. (2006). Improving abnormal spatial vision in adults with amblyopia. In M.  R.

Jenkin & L. R. Harris (Eds.), Seeing spatial form  (pp. 371–380). New York:  Oxford

University Press.

Polat, U. (2008). Restoration of underdeveloped cortical functions: Evidence from

treatment of adult amblyopia. Restorative Neurology and Neuroscience, 26, 1–12.

Polat, U., Bonneh, Y., Ma-Naim, T., Belkin, M., & Sagi, D. (2005).  Spatial interactions

in  amblyopia:  Effects  of  stimulus  parameters  and  amblyopia  type.  Vision  Research, 45(11), 1471–1479.

Polat,  U.,  Ma-Naim,  T.,  Belkin,  M.,  &  Sagi,  D.  (2004).  Improving  vision  in  adult

amblyopia  by  perceptual  learning.  Proceedings  of  the  National  Academy  of  Sciences USA, 101(17), 6692–6697.

Polat, U., Mizobe, K., Pettet, M. W., Kasamatsu, T., & Norcia, A. M. (1998). Collinear

stimuli  regulate  visual  responses  depending  on  cell’s  contrast  threshold.  Nature,

391(6667), 580–584.

Polat, U., & Norcia, A. M. (1996). Neurophysiological evidence for contrast  dependent

long-range  facilitation  and  suppression  in  the  human  visual  cortex.  Vision  Research, 36(14), 2099–2109.

Polat, U., & Sagi, D. (1993). Lateral interactions between spatial channels:  Suppression

and  facilitation  revealed  by  lateral  masking  experiments.  Vision  Research,  33(7),  993– 999.

Polat, U., & Sagi, D. (1994a). The architecture of perceptual spatial interactions.  Vision

Research, 34(1), 73–78.

Polat, U., & Sagi, D. (1994b). Spatial interactions in human vision: From near to far  via

experience-dependent cascades of connections.  Proceedings of the National  Academy of Sciences USA, 91(4), 1206–1209.

Polat, U., & Sagi, D. (1995). Plasticity of spatial interactions in early vision. In B.  Julesz

& I. Kovacs (Eds.). Maturational windows and adult cortical plasticity (Vol.

24, pp. 1–15). Addison-Wesley.

Polat, U., & Sagi, D. (2006). Temporal asymmetry of collinear lateral interactions.

Vision Research, 46(6–7), 953–960.

Polat, U., Sagi, D., & Norcia, A. M. (1997). Abnormal long-range spatial interactions  in

amblyopia. Vision Research, 37(6), 737–744.

Polat, U., Sterkin, A., & Yehezkel, O. (2007). Spatio-temporal low-level neural  networks

account for visual masking. Advances in Cognitive Psychology(3),  153–165.

Popple, A. V., & Levi, D. M. (2000). Amblyopes see true alignment where normal

observers  see  illusory  tilt.  Proceedings  of  the  National  Academy  of  Sciences  USA,

97(21), 11667–11672.

Prieto-Diaz, J. S.-D. C. (2000). Strabismus. Boston: Butterworth–Heinemann.

Sagi,  D.,  &  Tanne,  D.  (1994).  Perceptual  learning:  Learning  to  see.  Current    pinion  in Neurobiology, 4(2), 195–199.

Shani, R., & Sagi, D. (2006). Psychometric curves of lateral facilitation.  Spatial Vision,

19(5), 413–426.

Simmers, A. J., Gray, L. S., McGraw, P. V., & Winn, B. (1999). Functional visual loss in

amblyopia  and  the  effect  of  occlusion  therapy.  Investigative  Ophthalmology  &  Visual Science, 40(12), 2859–2871.

Simmers, A. J., Ledgeway, T., Hess, R. F., & McGraw, P. V. (2003). Deficits to global

motion processing in human amblyopia. Vision Research, 43(6), 729–738.

Siow  K,  Tan  D,  (2008)  2  Years  Follow-Up  Results  of  Visual  Acuity  and  Contrast

Sensitivity  Enhancement  in  Patients  with  Low  Myopia  using  NeuroVision’s  Neural

Vision Correction  (NVC) Technology IMC 2008

Solomon, J. A., & Morgan, M. J. (2000). Facilitation from collinear flanks is cancelled by

non-collinear flanks. Vision Research, 40(3), 279–286.

Stuart, J. A., & Burian, H. M. (1962). A study of separation difficulty and its relationship

to visual acuity in normal and amblyopic eyes.  American Journal of  Ophthalmology, 53, 471–477.

Tan  D. T. (2006), Improving VA and CSF in Subjects with Low Degrees of Myopia and

Early Presbyopia using Neural Vision Correction (NVC) Technology, APAO 2006

Tan D.T., Chan B., Tey F., Lee L (2004), Pilot Study To Evaluate The Efficacy of  Neural

Vision  Correction™  (NVC™)  Technology  For  Vision  Improvement  in  Low  Myopia,

ARVO 2004

Tan,  D.  T., & Fong, A. (2008). Efficacy of neural vision therapy to enhance  contrast sensitivity function and visual acuity in low myopia.  Journal of Cataract and  Refractive Surgery, 34(4), 570–577.

Tanaka,  Y.,  &  Sagi,  D.  (1998).  Long-lasting,  long-range  detection  facilitation.  Vision

Research, 38(17), 2591–2599.

Tripathy, S. P., & Cavanagh, P. (2002). The extent of crowding in peripheral vision  does

not scale with target size. Vision Research, 42(20), 2357–2369.

Von  Noorden,  G.  K.  (1981).  New  clinical  aspects  of  stimulus  deprivation  amblyopia. American Journal of Ophthalmology, 92(3), 416–421.

Watson,  A.  B.,  Barlow,  H.  B.,  &  Robson,  J.  G.  (1983).  What  does  the  eye  see  best? Nature, 302(5907), 419–422.

Waring IV G.O., Durrie D.S., Slade G.S. Visual Cortex Training Combined With LASIK

for Treatment of Low Myopia, unpublished Data

Waring  IV  G.O.,  Hunkeler  J.,  Lindstrom  R.,  (2010)  Evaluation  of  Computer  Based

Primary  Visual  Cortex  Training  After  Aspheric  Monofocal,  Multifocal,  and

Accommodating IOL Implantation  ARVO 2010

Wick, B., Wingard, M., Cotter, S., & Scheiman, M. (1992). Anisometropic amblyopia:  Is

the patient ever too old to treat? Optometry and Vision Science, 69(11), 866–878.

Wilson,  H.  R.  (1991).  Psychophysical  models  of  spatial  vision  and  hyperacuity.  In  D.

Regan (Ed.). Vision and Visual Dysfunction (Vol. 10, pp. 64–86). CRC Press, Inc..

Wilson, H. R., & Wilkinson, F. (1997). Evolving concepts of spatial channels in  vision:

From independence to nonlinear interactions. Perception, 26(8), 939–960.

Wong, E. H., & Levi, D. M. (2005). Second-order spatial summation in amblyopia.

Vision Research, 45(21), 2799–2809.

Wong, E. H., Levi, D. M., & McGraw, P. V. (2005). Spatial interactions reveal inhibitory

cortical networks in human amblyopia. Vision Research, 45(21), 2810–2819.

Woods, R. L., Nugent, A. K., & Peli, E. (2002). Lateral interactions: Size does matter.

Vision Research, 42(6), 733–745.

Yu, C., Klein, S. A., & Levi, D. M. (2004). Perceptual learning in contrast discrimination

and the (minimal) role of context. Journal of Vision, 4(3), 169–182.

Zhou, Y., Huang, C., Xu, P., Tao, L., Qiu, Z., Li, X., et al. (2006). Perceptual learning

improves contrast sensitivity and visual acuity in adults with anisometropic  amblyopia.

Vision Research, 46(5), 739–750.