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Contrast is one of the most important parameters activating cortical cells involved in vision processing8. Responses of individual neurons to repeated presentations of the same stimulus are highly variable (noisy)8-10. Noise may impose a fundamental limit on the reliable detection and discrimination of visual signals by individual cortical neurons11,12. Neural interactions determine the sensitivity for contrast at each spatial frequency, and the combination of neural activities derive an individual’s contrast sensitivity function (CSF)13. Theory suggests that the relationship between neuronal responses and perception are mainly determined by the signal-to-noise ratio (S/N ratio) of the neuronal activity. The brain pools responses across many neurons to average out noisy activity of single cells, thus improving signal-to-noise ratio, leading to substantially improved visual performance14. In several studies Uri Polat, PhD has shown that the noise of individual cortical neurons can be brought under experimental control by appropriate choice of stimulus conditions15,16. Polat and colleagues15-18,3 have demonstrated that contrast sensitivity at low levels can be increased by a factor of 2 through control of stimulus parameters. These results are derived from subjects (adults) with normal vision. At the neural level, the improvement in sensitivity would not be expected or largely reduced without a concurrent decrease in response noise. This precise control of stimulus conditions leading to increased neuronal efficiency is fundamental in initiating the neural modifications that are the basis of brain plasticity19,20. The technology behind NVC probes specific neuronal interactions, using a set of patient-specific stimuli that improve neuronal efficiency3,21 and induce improvement of CSF due to a reduction of noise and increase in signal strength – followed by a marked improvement in spatial resolution or visual acuity (VA). Treating Amblyopia NVC has been successfully used in the clinical treatment of amblyopia, a condition where the visual system is underdeveloped due to abnormal visual input to the brain during the critical period (up to age 9). Amblyopia is categorized as anisometropic, where one eye’s refractive value is grossly different than the other eye’s, or as strabmismic, where one eye is out of alignment. These physical conditions often lead to suppression of neural connections in the visual cortex and reduced visual function. Amblyopia is characterized by several functional abnormalities in spatial vision, including reduction in VA and CSF22. The reduction in CSF, pronounced at high spatial frequencies, is believed to result from a low S/N ratio. A low S/N ratio is shown to limit performance on letter identification23. Generally, it is known that CSF (especially the higher spatial frequencies) is closely related to resolution (VA). Amblyopes also suffer from abnormal neural interactions22 and reduced excitation and increased inhibition, an effect that underlies deficient contrast response. Polat’s work revealed the process by which neural connections are formed during the critical or plastic period. This process, where neural connections are formed cell-by-cell, is reliant on a given optical or “front-end” input. If the ocular input is normal, then one can expect normal development of these connections; if, on the other hand, the ocular input is abnormal (i.e. in the case of amblyopia), one can expect abnormal development. REFERENCES: ARTICLES IN SCIENTIFIC AND MEDICAL JOURNALS 8. Levi D.M., Polat U., Hu YS, (1997) Visual improvement in adults with amblyopia. Invest. Ophthalmol. Vis. Sci., 38(8) 1493-1510. 9. Candy, T.R., Norcia, A.M. & Polat, U. (1998) Preferential loss of lateral interaction in amblyopia. Vision Science and Its Applications, Vol. 1, Opt. Soc. Am. Technical Digest, pp. 60-63. 10. Polat U., Mizobe, K., Kasamatsu, T., Norcia A.M. (1998). Collinear stimuli regulate visual responses depending on Cell’s contrast threshold. Nature, 391, 580-584. 11. Polat U., Norcia A.M. (1998) Elongated physiological summation pools in the human visual cortex. Vision Res., 38, 3735-3741. 12. Polat U., Tyler C. W. (1999). What pattern does the eye sees best? Vision Res., 39, 887-895. 13. Polat U., (1999) Functional architecture of long-range perceptual interactions. Spatial Vision, 12, 143-162. 14. Pennefather, P.M., Chandna, A. Kovacs, I., Polat, U. & Norcia, A. M. (1999). Contour detection threshold: repeatability and learning with “contour cards” Spatial Vision, 12, 257-266. 15. Kovács, I., Polat, U., Pennefather, P.M., Chandna , Norcia. A.M. (2000). A new test of contour integration deficit in patients with history of disrupted binocular experience during visual development. Vision Res. 40, 1775-1783 16. Polat, U. & Bonneh, Y. (2000) Collinear interactions and contour detection. Spatial Vision, 13, 393-402. 17. Kasamatsu, T., Polat, U., Pettet M.W., & Norcia, A.M. (2001) Collinear facilitation promotes reliability of single-cell responses in cat striate cortex. Experimental Brain Research, 138(2): 163-172. 18. Popple, A., Polat, U., Bonneh, Y. (2001) Collinear effects on 3-Gabor alignment as a function of spacing, orientation and detectability. Spatial Vision, 14(2), 139-150. 19. Chen, C-C., Kasamatsu, T., Polat, U., Norcia, A.M. (2001) Contrast response characteristics of long-range lateral interactions in cat striate cortex. NeuroReport, 12(4): 655-661. 20. Mizobe, K., Polat, U., Pettet, M. & Kasamatsu, T. (2001) Facilitation and suppression of single straite-cell activity by spatially-discrete pattern stimuli presented beyond the receptive field. Visual NeuroScience, 18(3): 377-391
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