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Ok, I realize now that
if you didn't do half a PhD studying human vision with fMRI, this quote doesn't make sense; and
"OMG" isn't an explanation;
also @goodfellow_ian is messaging me on chat asking great questions;
so let me just broadcast an explanation of why "OMG": 1/nhttps://twitter.com/catherineols/status/1058115313290473472 …
First: What's the phenomenon that needs explaining? "The [location of] face and place selective regions [in the brain] is strikingly consistent across individuals. What dimensions of visual information constrain the development& topography of this shared brain organization?" /2
Rephrase: If I show you images of faces, a particular side of a particular fold of your brain will react to those pictures WAY more than other pictures. It's the *same* side of the *same* brain fold in everyone. Different areas for houses/places, body parts, text, etc. /3
But why did faces end up *there*? Because... they have a smooth texture? ...you learned faces early in life? ...you usually look at them in the center of your vision? ...you have a lot of expertise with them? (Would *anything* you're an expert in be represented nearby?) /4
One of my fav results in this field shows that "what gets recognized where" is NOT shaped by the *order* you learn the categories. They taught baby monkeys 3 types of totally made-up shapes, a different order per monkey. Each type still went to a consistent brain location. /5pic.twitter.com/8KKdgE2fxI
So: this study. Some 8-year-olds in my generation spent *HOURS* staring at avatars of Pokemon. Always with the gameboy held right in the center of our vision, at the same position. Some 8-year-olds didn't. This is a *perfect* natural experiment for neuroscience. Hence "OMG" /6
We're just like the baby monkeys in the other study, forced to look at made-up glyphs for hours & hours per day. You can't approve a study to force human 8-year-olds to stare at a small set of little symbols daily for years. But children can voluntarily do it to themselves! /7
Q1: do pokemon avatars end up represented in the same part of the brain for everyone? A1: YES, if you played pokemon for a bajillion hours as a kid. NO, if you didn't. /8
Q2: Pokemon are *depictions* of animals, which in real-life have faces, bodies, curvy lines, fuzzy. But pokemon *avatars* are pixellated: rectilinear & sharp. Does the "pokemon area" end up near... animate? bodies? rectilinear? expertise / faces? center-of-vision? other? /9pic.twitter.com/em7slmvuf4
A2-a: There's NO preferential response in the face, body, or animal areas. A2-b: The "face" spot is more lateral than the "place" area: there's a separate Pokemon area, and it's is EVEN MORE lateral than that. The best predictor of this is looking *directly at* Pokemon: /10
People look at faces straight-on usually, with mostly-central vision. Places fill more of your visual field, or are seen with peripheral vision (more "out of the corner of your eye") A gameboy is viewed EVEN MORE right-in-the-middle-of-vision than faces. /11
To summarize: The answer to "What determines the physical layout of category-selective visual areas in the brain?" is likely, at least in part, "Retinal eccentricity" that is "Which part of your eye you use: do you look at this category straight-on, or peripherally?" /fin
cc @slatestarcodex whose blog I've commented on ~once ever, to chime in about this very topic
Well explained, though if the human brain will ever be explained, I doubt that these tiny random Sherlock-Holmes-like pieces will have any contribution to it...
If we ever understand the human brain, I would expect that these sorts of discoveries would be exactly the stepping stones toward that end.
Thank you for this detailed explanation! Super exciting stuff!
OMG indeed! After reading your unpacking thread 
.. this is one of those things you learn that causes fireworks in my head as I update so many objects that this has relevance to & stare stunned evaluating even more that it may apply to while doubting I actually understand it 
So cool! I wonder if this correlates with any of the #computervision work that @geoff_hinton & others have done with #deeplearning capsule nets (based on cortical columns) that form a representation of 3d-pose as being a critical component in invariant recognition of objects 
Hmmm
Saluti there is your unroll: Thread by @catherineols: "Ok, I realize now that if you didn't do half a PhD studying human vision with fMRI, this quote doesn't make sense; and " […]" https://threadreaderapp.com/thread/1058143950849007616.html …
Talk to you soon. 
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