Cognitive scientists have been studying the computational foundations of vision in depth since at least the 1980s (see David Marr's 1982 book Vision), and AI scientists have been using neural networks for computer vision tasks for at least as long. So yeah, I'm no expert, but this probably isn't the ground-breaking work the article makes it out to be.
This work is about the very early steps of the primate visual pathway -- retina to LGC to the input layer of V1. Marr's opus is meant to be a much more wholistic view of the visual system. A more appropriate context for this article is perhaps David Hubel's (very accessible) Eye, Brain, Vision.
(The book used to be freely available on a website hosted by Harvard Med, but I can't seem to find it anymore.)
FWIW, I work a little bit in computational neuroscience. While I think "ground breaking" is an exaggeration, and I wish the article spent more time explaining the general thinking in the field and why it matters, the content is not terribly written for an article of this type and length. And it should be emphasized that the point of this modeling is really understanding the biology of the primate visual system; what it says about the general problem of vision is a separate question.
Disclaimer: I was not involved in this work, but did collaborate with one of the scientists extensively in the past.
Can't edit anymore, so two very minor corrections: "LGC" should have been "LGN" (had "RGC" and "LGN" both on my mind), and "disclaimer" should really have been "disclosure."
> Not only are LGN cells scarce — they can’t do much either. LGN cells send a pulse to the visual cortex when they detect a change from dark to light, or vice versa, in their tiny section of the visual field. And that’s all.
[I think the "scarcity" is real, but some areas have better coverage than other. But I really don't remember anything similar to the other part of the model.]
>>> LGN cells send a pulse to the visual cortex when they detect a change from dark to light, or vice versa
This looks like an binary toggle encoding (and that the receiving end must remember and count how many pulses received to know if that part is dark or light).
I vaguely remember something like that the neurons in that part or nearby send pulses periodically, and the time between pulses is smaller (or bigger?) when there is more light. (Or perhaps keep the time between pulses, but use double/triple/... pulses more light.) Perhaps add some slow adaptation to the light level, so after a time at a fixed light level the neuron uses the default interval between pulses. I'm not sure about the actual encoding, but all of what I remember are very different from the encoding in the article.