Context-dependent selectivity to natural images in the retina

Matías A. Goldin (), Baptiste Lefebvre, Samuele Virgili, Mathieu Kim Pham Van Cang, Alexander Ecker, Thierry Mora, Ulisse Ferrari and Olivier Marre ()
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Matías A. Goldin: Sorbonne Université, INSERM, CNRS
Baptiste Lefebvre: Sorbonne Université, INSERM, CNRS
Samuele Virgili: Sorbonne Université, INSERM, CNRS
Mathieu Kim Pham Van Cang: Sorbonne Université, INSERM, CNRS
Alexander Ecker: University of Göttingen
Thierry Mora: CNRS, PSL University, Sorbonne University, and University of Paris
Ulisse Ferrari: Sorbonne Université, INSERM, CNRS
Olivier Marre: Sorbonne Université, INSERM, CNRS

Nature Communications, 2022, vol. 13, issue 1, 1-12

Abstract: Abstract Retina ganglion cells extract specific features from natural scenes and send this information to the brain. In particular, they respond to local light increase (ON responses), and/or decrease (OFF). However, it is unclear if this ON-OFF selectivity, characterized with synthetic stimuli, is maintained under natural scene stimulation. Here we recorded ganglion cell responses to natural images slightly perturbed by random noise patterns to determine their selectivity during natural stimulation. The ON-OFF selectivity strongly depended on the specific image. A single ganglion cell can signal luminance increase for one image, and luminance decrease for another. Modeling and experiments showed that this resulted from the non-linear combination of different retinal pathways. Despite the versatility of the ON-OFF selectivity, a systematic analysis demonstrated that contrast was reliably encoded in these responses. Our perturbative approach uncovered the selectivity of retinal ganglion cells to more complex features than initially thought.

Date: 2022
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DOI: 10.1038/s41467-022-33242-8

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