Human evolution; how our brains create images (Introduction)

by David Turell , Wednesday, August 21, 2019, 18:55 (1710 days ago) @ David Turell

A complex relationship with the visual cortex:

https://www.quantamagazine.org/a-mathematical-model-unlocks-the-secrets-of-vision-20190...

"This is the great mystery of human vision: Vivid pictures of the world appear before our mind’s eye, yet the brain’s visual system receives very little information from the world itself. Much of what we “see” we conjure in our heads.

“'A lot of the things you think you see you’re actually making up,” said Lai-Sang Young, a mathematician at New York University. “You don’t actually see them.”

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"The eye acts as a lens. It receives light from the outside world and projects a scale replica of our visual field onto the retina, which sits in the back of the eye. The retina is connected to the visual cortex, the part of the brain in the back of the head.

"However, there’s very little connectivity between the retina and the visual cortex. For a visual area roughly one-quarter the size of a full moon, there are only about 10 nerve cells connecting the retina to the visual cortex. These cells make up the LGN, or lateral geniculate nucleus, the only pathway through which visual information travels from the outside world into the brain.

"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. The lighted world bombards the retina with data, but all the brain has to go on is the meager signaling of a tiny collection of LGN cells.

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“'But the brain doesn’t take a picture, the retina does, and the information passed from the retina to the visual cortex is sparse.”

"But then the visual cortex goes to work. While the cortex and the retina are connected by relatively few neurons, the cortex itself is dense with nerve cells. For every 10 LGN neurons that snake back from the retina, there are 4,000 neurons in just the initial “input layer” of the visual cortex — and many more in the rest of it. This discrepancy suggests that the brain heavily processes the little visual data it does receive.

“'The visual cortex has a mind of its own,” Shapley said.

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"These “feed forward” models were easier to create, but they ignored the plain implications of the anatomy of the cortex — which suggested “feedback” loops had to be a big part of the story.

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"Young, Shapley and Chariker demonstrated that their feedback-rich model was able to reproduce the orientation of edges in objects — from vertical to horizontal and everything in between — based on only slight changes in the weak LGN input coming into the model.

“[They showed] that you can generate all orientations in the visual world using just a few neurons connecting to other neurons,” Angelucci said.

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"In 2018, the three researchers published a second paper in which they demonstrated that the same model that can detect edges can also reproduce an overall pattern of pulse activity in the cortex known as the gamma rhythm. (It’s similar to what you see when swarms of fireflies flash in collective patterns.)

"They have a third paper under review that explains how the visual cortex perceives changes in contrast. Their explanation involves a mechanism by which excitatory neurons reinforce each other’s activity, an effect like the gathering fervor in a dance party. It’s the type of ratcheting up that’s necessary if the visual cortex is going to create full images from sparse input data.

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"While their model is far from uncovering the full mystery of vision, it is a step in the right direction — the first model to try and decipher vision in a biologically plausible way.
“People hand-waved about that point for a long time,” said Jonathan Victor, a neuroscientist at Cornell University. “Showing you can do it in a model that fits the biology is a real triumph.'”

Comment: Babies see upside down and backward, but their brains are gradually taught to see reality. The visual cortex learns over time to effectively make the pictures. No 'free will' folks will point to this as proof they are right. But this is the only way a biological system can give proper results.