June 2015
Volume 56, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2015
Cone photoreceptors adapt to contrast under natural stimulus conditions
Author Affiliations & Notes
  • Maarten Kamermans
    Retinal Signal Processing, Netherlands Institute for Neuroscience, Amsterdam, Netherlands
    Neurogenetics, Academic Medical Center, Amsterdam, Netherlands
  • Marcus Howlett
    Retinal Signal Processing, Netherlands Institute for Neuroscience, Amsterdam, Netherlands
  • Footnotes
    Commercial Relationships Maarten Kamermans, None; Marcus Howlett, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 1711. doi:
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      Maarten Kamermans, Marcus Howlett; Cone photoreceptors adapt to contrast under natural stimulus conditions. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):1711.

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

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Abstract

Purpose: An animal’s ability to survive depends on its sensory systems being able to adapt to a wide range of environmental conditions, by maximizing the information extracted and reducing the noise transmitted. The visual system does this by adapting to the luminance and contrast levels it experiences. Luminance adaptation begins at the retinal photoreceptor. It is generally believed that cones do not adapt to temporal contrast. We revisited this issue.

Methods: Electrophysiological recordings of cones in goldfish retina were made while stimulated with classical (white noise) and natural stimuli with matching mean intensities and contrast levels.

Results: We found that L- and M-cones act as contrast dependent adaptive filters when stimulated with naturalistic stimuli but show no such adaptation when classic white noise stimuli are used. This form of contrast adaptation is mediated by the photoreceptor membrane current, Ih, a membrane current of photoreceptor. Consistent with this, short-wavelength sensitive-cones do not adapt to contrast and had a significantly smaller Ih.

Conclusions: As low contrast conditions generate a lower signal to noise ratio, the adaptive filtering mechanism identified here maximizes information transmitted by removing high frequency noise in low contrast conditions. Our results also highlight the importance of the type of stimuli used when studying sensory systems. Sensory neurons respond to classic stimuli in ‘classic’ ways, which is different to how they response to the conditions they have evolved to process.

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