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This represents the absolute worst kind of science journalism, completely devoid of context and domain knowledge. Virtually every definitive statement in here i

by apl 7y ago

This represents the absolute worst kind of science journalism, completely devoid of context and domain knowledge. Virtually every definitive statement in here is wrong. Their explanation of spiking alone is a complete disaster. Out of all the modalities, vision is easily the one we know the most about. And we do so at a fairly deep level. The discussed work seems fine but it's not the groundbreaking insight it's made out to be. Great PR work from the involved scientists (or their enterprising university marketing department).

Circuits 7y ago
I actually learned a bit about how eyes work from this short little article, all I will ever need to know anyhow. It certainly doesn't represent the worst kind of science journalism. I bet I could think of (at least) 4 or 5 worse kinds of science journalism.
asimpletune 7y ago
I don’t know a lot about this subject. Can you elaborate?
- gus_massa 7y ago
  I'm not an expert, but is this paragraph correct? > 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.]
  - raws 7y ago
    I think lgn are a very small part of the visual system as per www.wikipedia.org/wiki/Visual_system (and also uni classes)
    - gus_massa 7y ago
      >>> 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.
- briga 7y ago
  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.
  - kkylin 7y ago
    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.
    - kkylin 7y ago
      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."
floki999 7y ago
Agree - very disappointing. I studied human and machine vision in grad school 20 years ago and fail to see the breakthrough hinted at by the title of the article.
- floki999 7y ago
  This is one of those magazines that comes in this thisck premium paper - perhaps to give a sense of important content where there is little.

by apl 7y ago

Circuits 7y ago

I actually learned a bit about how eyes work from this short little article, all I will ever need to know anyhow. It certainly doesn't represent the worst kind of science journalism. I bet I could think of (at least) 4 or 5 worse kinds of science journalism.

asimpletune 7y ago

I don’t know a lot about this subject. Can you elaborate?

gus_massa 7y ago
I'm not an expert, but is this paragraph correct? > 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.]
- raws 7y ago
  I think lgn are a very small part of the visual system as per www.wikipedia.org/wiki/Visual_system (and also uni classes)
  - gus_massa 7y ago
    >>> 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.
briga 7y ago
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.
- kkylin 7y ago
  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.
  - kkylin 7y ago
    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."

floki999 7y ago

Agree - very disappointing. I studied human and machine vision in grad school 20 years ago and fail to see the breakthrough hinted at by the title of the article.

floki999 7y ago
This is one of those magazines that comes in this thisck premium paper - perhaps to give a sense of important content where there is little.