MIT Crowdsources and Gamifies Brain Analysis 38
MrSeb writes "There are around 100 billion neurons in a human brain, forming up to 100 trillion synaptic interconnections. Neuroscientists believe that these synapses are the key to almost every one of your unique, identifiable features: Memories, mental disorders, and even your personality are encoded in the wiring of your brain. Understandably, neuroscientists really want to investigate these neurons and synapses to work out how they play such a vital role in our human makeup. Unfortunately, these 100 trillion connections are crammed into a two-pound bag of soggy flesh, making analysis rather hard. Starting small and working its way up, MIT today launched Eyewire, a crowdsourced 'game' that tasks users with wiring up the neurons in a mouse's retina. A future stage of the game will get users to find the synapses, too."
2 pounds? (Score:1)
I thought a brain weighed about 10 pounds. Or are we talking ROUSes...
Re:2 pounds? (Score:4, Informative)
Neither. The average for an adult is ~1400 grams, which according to Google is ~3 pounds.
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Include non-adults, and the average becomes 1100 gms ~ 2.4 pounds.
Re:2 pounds? (Score:4, Funny)
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So it starts with 1.1 kg and then it drops to 1.75 kg?
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Yes, but I don't think infants have the same number of neurons - the number referenced in TFA is for an adult brain, I think.
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Infants actually have more neurons, ironically. For the most part, we start with all of our neurons and then some of them die (this is thought to have some factor in learning, where less useful neurons die and their wiring is replaced by more useful neurons).
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Nice! (Score:1)
As a former cognitive science student, I'm always amazed at how quickly the complexity of the brain limits our ability to understand it. While it's not the same as the Genome project, it's awesome when projects like this show up that prompt us to get a better understanding of the brain.
My question: can uneducated users really use the game to make valid discoveries? What prevents errors?
Also, it's a bummer that this is based on the eye, which has already had a ton of deep-dive research done.
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I suspect that we will never really understand it... we might asymptotically approach an understanding of it, but I don't think we will ever get to a point where we fully do.
The reason for this is because we, ourselves, are limited in complexity of what is cognizable by the capacity and complexity of our own brains. I apologize profuesly in advance for the following oversimplification, but I imagine it would be like trying to an entire additional litre of water into another 1 litre cup that already has
Re:Nice! (Score:4, Insightful)
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Anyways, you may be right... and although I'm skeptical, I still hope that you are. We will see someday, perhaps.
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Except that no one's brain has ever been "filled" up.
Sure it has. Why do you think we forget things?
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https://sonofatweet.appspot.com/cant-tell-if-troll.png [appspot.com]
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I see what you're saying, but I don't know if I agree. The other systems of the body (lymbic, digestive, etc.) are fairly well understood, yet we don't possess the processing power to deliberately (keyword) run them. I believe scientific analysis of many many brains may one do yield just a good understanding of the brain.
This could even more true if you believe in the Singularity, which I personally don't, but it certainly warrants mention.
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Good point. But I don't think we know enough to say, even if the results of this do match past data, that applying this method to something more unfamiliar will yield similar quality. I guess it may bring up some interesting questions that could then be put to scientific scrutiny.
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You and one of your follow-up posters suggested that the eye was basically too simple to try this technique on. This is not correct. The eye contains the retina, which is actually a part of the brain. It's a sort of small computer in the eye that, for example, calculates motion direction. Understanding how this works is cutting edge research, to which this technique has already contributed: http://www.nature.com/nature/journal/v471/n7337/full/nature09818.html
On a more general note, acquiring these datasets
Ambivalent (Score:2)
On one hand, this is a totally cool use of crowdsourcing. On the other hand, this seems like precisely the kind of task at which the computer can be orders of magnitude better than humans with the "right" algorithm.
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Is it at least the case that some of them are classified by computer, and the humans only get the difficult ones?
No more users (Score:2)
There's just an input box so they can email you when they're ready for more users.
Reamde (Score:2)
This sounds familiar to part of Reamde, crowd-sourced gaming for real world activities.
And once we are done... (Score:2)
We will have new overlords....