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Whole human brain mapped in 3D (nature.com)
98 points by feelthepain on June 21, 2013 | hide | past | favorite | 37 comments


Shameless plug: 3Scan [1], a company spun off from a university in Arizona (if I'm not mistaken) and partially funded by Peter Thiel's Breakout Labs grant is making a robot that is capable of doing this entire procedure with absolutely minimal human involvement.

They can already do a full 3d map of blood vessels and neurons (with stains) in a mouse brain within a few days and store it on a TB hard drive (I'm told an equivalent for the human brain would be a petabyte but their slices might be thinner). This is a procedure that would take months if not years to do by hand (they do a full analysis on all of the slices to reproduce a 3d model afterwards).

This paper was done mostly by hand but soon we'll be able to do it quickly and automatically.

[1] http://www.3scan.com/


Ten TRILLION bytes...

It's okay, Nature, the word terabyte doesn't scare people and is indeed now part of common parlance...


Apologies (one of Nature's editors here). Believe it or not it was in terabytes when we sent the copy to our sub-editors (ie copy editors) and they changed it because they thought our readers wouldn't get it. We're as bemused as you.


Roughly 9.09495TB for anybody interested


Now you've done it, this thread is going to collapse into a binary-vs-metric data measurement flamewar.



Wikipedia is not a source~


For proof that Wikipedia is more accurate than other encyclopedias, check out http://en.wikipedia.org/wiki/Reliability_of_Wikipedia

(Though seriously, Wikipedia is about as accurate as the Encyclopedia Brittanica, at least for science articles: http://www.nature.com/nature/journal/v438/n7070/full/438900a...)


That applies well to en.wikipedia.org, not as much to simple.wikipedia.org. See my reply to andyhmltn about how the properly researched page disagrees with the grandparent's link.

Don't trust a wikipedia page that has zero citations.


These are good points and it would be quite helpful if you put them in the comment next time. "The simple english wikipedia page has these specific flaws" is substantially more accurate and informative than "Wikipedia is not a source."


Well, if you want to know, my original objection was toward using Wikipedia as the arbiter of correct stance on a political issue. Wikipedia itself tries to keep politics out, and for good reason with the way online communities can groupthink. Clearly I should have expanded on that in the first comment.

I was not aware at that time that Wikipedia actually contradicted itself, but that was a very easy way to demonstrate my point in a followup post. But the particular flaws in that article were never my main point.


Flamewar: success! Pxtl wins!


Even though it's an argument about wikipedia and nobody has discussed the actual measurement system?


Eh, point. I count any thread with a buried comment (like yours) as a flamewar, is all ;)


I dislike when people say this. No Wikipedia in itself is not a source, but it's usually an aggregate of sources. If you scroll to the bottom of the article, if it's properly labelled up you can find the exact sources for everything said.


I scrolled to the bottom. The page had no sources. Then I went to the main English wikipedia page to get some sources, but apparently it completely disagrees with the simple English page.

The real megabyte page says that it has multiple meanings, and the mebibyte page says that "it was designed to replace the megabyte" and that "it is not commonly used". And I'll assume the sources listed are suitable for the moment.


Wonder if it would have without this comment.


Oh dear.. blame Google, not me!


Actually that's in TiB. TB is metric.


or about $300 worth of Hard Drives at Costco


Yeah but Ten Trillion Bytes sounds a lot bigger than 9 TB.


I think that's the intention. Regardless of how you look at it however: It's still really impressive


I'd love for a neuroscientist to weigh in on this - what is the possibility that something like this could be used to generate an artificial neural network which imitates, even crudely, the functions of the human brain?


Not a neuroscientist but final year med with a strong interest in neuro-

This will certainly be useful for attempts to recreate the functionality of a brain in silico - big research efforts such as the blue brain project [1] have probably been using even early forms of this data.

Having said that, in some ways it won't provide the useful information that will enable the functionality to be restored to the connections.

heres why.

Current efforts involving simulated brains rely both on older, less precise versions of what this nature article talks about - let's call that the roadmap, as it is a map of where all the neurons sit and where they connect to. This project drastically increases the resolution of this roadmap.

However the additional information needed is what traffic is carried by each road. The brain as we understand it today consists not just of the connections between the neurons but also that each neuron, and each different network of the brain, secretes it's own neurotransmitter. Because some of these neurotransmitters are depolarising and some are inhibitory, and they connect widely across the brain and are much more closely related to the actual information processing, we need to have this information before we will be able to better approximate a brain.

In all likelihood this is information gathering is probably underway right now. From what I understand the 'BigBrain' project aims to do for the human brain what the Allen Brain atlas did for mouse brains, that is not only provide a map of the connections but also stain for gene expression and (from memory) neurotransmitter presence.

With this added information we will be closer to our goal of getting skynet sentient.

[1] http://bluebrain.epfl.ch/


Depends. First, a biological network is not just connections of neurons, it's weighted connections of neurons. And even saying that is a huge approximation.

It's not just about mapping the topology of the brain, just having a neural network of 1e10 vertices and 1e12 links will not give you an artificial intelligence. It's just not that simple. The connectome paradigm is not sufficient. It is hip because of computer scientists using artificial neuron networks to achieve awesome stuff. But that doesn't mean that the complexity of the human brain only resides in the number of neurons and interactions. It's not guaranteed that we are getting closer of the goal just by adding billions of neurons and connections.

I find this wannabe holistic approach a bit confusing as it is horizontal whereas I am convinced that what we need is a vertical approach : up from graph topology down to an accurate biophysical understanding of synapses and information transmission, all across multiple scales, from the angström up to microns.

That's the key : multiscale modeling, not single-huge-scale modeling.


I totally agree. The brain is drastically more complex than a CPU, which could be reverse engineered in such a fashion. That's because we have a solid understanding of what happens when electrons flow through a series of specialized circuits, and we can control (and model) the input and output of each one. We cannot yet control or predict that flow with a human neuron, I don't think. At least this map doesn't get us closer in that regard, as much as I want it to.


Systems Neuroscientist here. I've only skimmed this paper so far, but it seems as though this dataset is limited to studying cytoarchitecture (what types of neurons are in what regions of the brain) as well as some tracing of major fiber pathways. This does not represent the successful conclusion to connectomics efforts to map every neuron and every connection in the brain (see Sebastian Seung's work and the eyewire project [1]). It's hard to tell exactly how useful this dataset and model are.

There are other exciting developments that map not just neuroanatomical structure but also the distribution of proteins and gene expression [2],[3]

[1] http://eyewire.org/ [2] http://med.stanford.edu/ism/2013/april/clarity.html [3] http://smithlab.stanford.edu/Smithlab/Array_Tomography.html


>what is the possibility that something like this could be used to generate an artificial neural network which imitates, even crudely, the functions of the human brain?

If possible, this would open a huge ethical can of worms: how can we tell such a simulation is not conscious? Would deleting its runtime data after however many simulation cycles be tantamount to murder?

Edit: I am not saying that the above concerns should stop us from working towards developing human brain simulations since the potential benefits of those are just too great. Rather, it is something we have to have in mind as they get more complex and closer to the real thing.


I'm not necessarily saying we _should_ create a simulation of the human brain - just asking whether it would be possible. There are other much more concrete concerns with creating strong AI too - avoiding accidentally creating a paperclip maximiser comes to mind: http://wiki.lesswrong.com/wiki/Paperclip_maximizer


Heh... as serious as they may be, the idea of one of those hypothetical ethical issues science fiction authors have written a million almost-but-not-quite-plausible takes on finally becoming real makes me giddy. I suppose it has already happened for certain issues, but nothing so dramatic as considering a simulation conscious!

Then again, it will likely be many years still before that actually comes up.


Another "not a neuroscientist" - but I do have a slightly-more-than-layperson knowledge and interest in the area, and a degree in AI if that matters.

"I'd love for a neuroscientist to weigh in on this - what is the possibility that something like this could be used to generate an artificial neural network which imitates, even crudely, the functions of the human brain?"

Pretty much zero. Because it really just focussed on the organisation of the neurons, and ignores the complexity of the neurons themselves and the chemical/electrical/etc. communication between 'em. Neurons themselves are pretty complex beasts, and we're still learning things about them and the level of "processing" that is happening within neurons, as opposed to between 'em.

For example as recently as ten years ago everybody knew that most of the computation was implicit in the neural connectivity of the synapses. We now know that there is significant computation within individual neurons - in the dendrites of all things (previously thought to be pretty much passive carriers of output from other cells - just wires basically).

(See http://www.annualreviews.org/doi/abs/10.1146/annurev.neuro.2... ).

Don't get me wrong - it's useful work. But nowhere close to the level of detail needed to run people-sims.


Not a neuroscientist, but used to work in the field, and my first idea was "well by cutting it up, they also cut all connections". And those connections are far more important for understanding how the brain works than seeing where an individual neuron is physically located. Unless off course they can somehow get the connections out of it.


Here is part of the software that was used to create this:

https://github.com/BIC-MNI

as confirmed here:

http://www.sciencemag.org/content/suppl/2013/06/19/340.6139....

Hell yeah, free science requires free software!


The BigBrain dataset is a subject of the NSA's research into graph analysis [1]. Some sample numbers:

  - 100 billion vertices, 100 trillion edges
  - 2.08 mNA · bytes^2 (molar bytes) adjacency matrix
  - 2.84 PB adjacency list
  - 2.84 PB edge list
[1]: http://www.pdl.cmu.edu/SDI/2013/slides/big_graph_nsa_rd_2013...


It seems like each brain is unique and it is meaningful to speak only about "connections" between regions and areas, given that even structure of nerves are different from person to person.

And, of course, it isn't even near to what we could call a "working model". Just a mapping of every neuron of some particular brain specimen. No one understands how it works yet. There are detailed description in textbooks of how each kind of cells in the brain works, but still can't see the mind among neurons.))


I am wondering how can you work with a 3D model with a file size of 1 TB ? Does it require custom software to deal with such a large data ?

EDIT: Perhaps its similar to google maps, where 3D "tiles" are loaded as required as you zoom in or out.


It's kind of like Iron Man 3




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