April 2010
Volume 51, Issue 13
ARVO Annual Meeting Abstract  |   April 2010
Patients With Visual Snow Have Normal Equivalent Input Noise Levels
Author Affiliations & Notes
  • M. Raghavan
    Dept. of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin
  • B. F. Remler
    Dept. of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin
  • S. Rozman
    Dept. of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin
  • D. G. Pelli
    Psychology and Neural Science, New York University, New York, New York
  • Footnotes
    Commercial Relationships  M. Raghavan, None; B.F. Remler, None; S. Rozman, None; D.G. Pelli, None.
  • Footnotes
    Support  Medical College of Wisconsin Research Affairs Committee Grant
Investigative Ophthalmology & Visual Science April 2010, Vol.51, 1808. doi:
  • Views
  • Share
  • Tools
    • Alerts
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      M. Raghavan, B. F. Remler, S. Rozman, D. G. Pelli; Patients With Visual Snow Have Normal Equivalent Input Noise Levels. Invest. Ophthalmol. Vis. Sci. 2010;51(13):1808.

      Download citation file:

      © ARVO (1962-2015); The Authors (2016-present)

  • Supplements

Purpose: : "Visual snow" is a poorly understood symptom where patients report seeing fine-grained flickering spots as a chronic aspect of their visual experience. The symptom may be acquired, self-remitting, or lifelong. We hypothesize that what the patients see as "snow" is their own intrinsic visual noise. Our experiments assess whether visual-snow patients have increased levels of intrinsic noise.

Methods: : We quantified intrinsic visual noise in 5 patients with visual snow as an equivalent input noise at the display by measuring grating detection thresholds, with and without high levels of added dynamic display noise (Pelli and Farell, 1999). In central vision, retinal photon noise and cortical neural noise dominate in different signal domains. With a signal of a fixed spatiotemporal scale (1.0 c/deg gabor subtending 3 degs of visual angle, lasting 100 ms), we estimated both photon and cortical noises by making measurements at low (0.8 cd/m2) and high (80 cd/m2) display luminances. For thresholds measured on a noise background, Gaussian dynamic display noise started and terminated 500 ms before and after signal presentation, and was of a magnitude sufficient to elevate contrast threshold by at least a factor of 2 relative to blank-field thresholds. Contrast thresholds measured in high levels of display noise also allow us to compute visual efficiency relative to an ideal observer model. Pupil size was measured under task conditions with an infrared video-camera to estimate retinal illumination. In order to compare photon noise levels across observers, from the measured photon noise and retinal illumination we compute retinal transduction efficiency, which is illumination-independent. We compared our estimates of transduction efficiency, cortical noise and visual efficiency from snow patients, with those from 16 normal observers.

Results: : All of our patients reported fine-grained dynamic "snow" involving the entire visual fields of both eyes. Aside from refractive abnormalities in two patients, visual functions were otherwise normal based on a careful neuro-ophthalmological screen. All 5 patients reported the snow to be stronger at low light levels. However, visual efficiency, transduction efficiency, and cortical noise for all patients were statistically indistinguishable from the control group.

Conclusions: : Visual snow patients have normal levels of equivalent input noise, contrast sensitivity and visual efficiency. We propose that patients with visual snow have normal intrinsic visual noise but increased perceptual gain.

Keywords: perception • contrast sensitivity • visual impairment: neuro-ophthalmological disease 

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.