Visual efficiency in amblyopic macaque monkeys

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Purpose. Amblyopes have reduced contrast sensitivity as well as acuity. This reduction in contrast sensitivity could arise early in the visual system (peripherally) or centrally. We have shown that infant contrast sensitivity is limited to a large extent by peripheral factors. We have now studied the limits on contrast sensitivity in amblyopes, using the visual masking paradigm of Pelli (1990) to measure the way in which visual noise affects contrast detection. Methods. We measured the effect of dynamic spatiotemporal masking noise on contrast detection in strabismic or anisometropic Macaca nemestrina. The monkeys were trained to detect the presence of a grating target in varying levels of background noise, using a two-alternative forced-choice procedure. We measured contrast threshold at low and moderate spatial frequencies over a range of noise contrasts from 0 to 50%. The subjects ranged in age from 6 months to 8 years at the time of test. Results. The effectiveness of noise in elevating contrast threshold is given by the equivalent input noise (Neq), the noise contrast that doubles squared threshold. In non-amblyopic eyes, Neq was correlated with contrast threshold; this relationship was less apparent in amblyopic eyes. Interocular comparison revealed that elevation in contrast threshold was not consistently related to elevation in Neq. While contrast threshold was elevated - often substantially - in amblyopic eyes, Neq was typically more similar in the two eyes. Conclusions. Since Neq is held to represent the efficiency of peripheral encoding, and elevation in contrast threshold was not related to elevation in Neq, our results are consistent with the hypothesis that, unlike normal development, contrast sensitivity in amblyopia is dependent on central factors.

Original languageEnglish (US)
Pages (from-to)S670
JournalInvestigative Ophthalmology and Visual Science
Issue number3
StatePublished - Feb 15 1996

ASJC Scopus subject areas

  • Ophthalmology
  • Sensory Systems
  • Cellular and Molecular Neuroscience


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