
Network of 75 Million Neurons of the Mouse Brain Mapped for the First Time - sethbannon
http://singularityhub.com/2014/04/14/network-of-75-million-neurons-of-the-mouse-brain-mapped-for-the-first-time/
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khawkins
Like its artificial neural net cousins, I feel like black-box approaches are
generally weak for studying intelligence. Programming a complex model is
relatively simple, given decades of neurobiological research. But running this
brain, absent a physical embodiment or model simplifications, offers few
lessons about the nature, structure, and form of intelligence.

The purpose of a brain is to control homeostasis, motor, and perception
functionality. Without a rich world simulation, the brain is just an isolated
processor. By modelling at the neuron level, the only inputs can be at the
neuron level. That means you have to physically model the entire mouse's body
to connect all the inputs.

Even if you had a realistic body simulation, you also need to run the system
for an extended period of time. Intelligence is an emergent behavior, and it
needs time to work and learn. Since you have to model every single neuron
firing at the same time, the speed at which you can run this model is
unreasonably slow.

I feel like approaches which slowly build a system of models, each of which
simplifies the function of a particular neural region to something
computationally tractable is the more realistic approach. In doing so, you
develop models which reveal the structure of intelligence.

~~~
habosa
That's a very cool way to think about it. Kind of like aliens finding my Core
i7 CPU and announcing they had replicated its transistor network ... except
for all they can do is run power to it and they have no idea how the RAM, GPU,
or any I/O works.

You have to start somewhere though.

~~~
z3phyr
I totally agree with this!

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tmragan
Excuse the plug, but I’m Tim Ragan the CEO of TissueVision. We’re the MIT
startup who developed the microscope technology responsible for all the mouse
brain images in the Allen Connectivity map that you see here.

We’re thrilled to have been a part of this groundbreaking project. If you’re
excited about this sort of science too, drop me a line. We’re hiring talented
developers who can push not just the microscope technology but also the super
cool bioinformatics just waiting to be mined from these and other projects.

Tim

~~~
gone35
Wow just wanted to say thank you for developing this technology. From your
white paper [1] I can see how serial two-photon tomography is a huge leap in
imaging and a crucial platform tool for the kind of ambitious large-scale
surveys we badly need.

I can see too how your main challenge is going to be registration/segmentation
on such huge datasets but there's plenty of ML/computer vision work and talent
next door in Cambridge. Maybe pair-up or present a poster during the incoming
New England Machine Learning day at Microsoft Research this May 13th? (Poster
deadline April 25) [2]. Good luck with your recruiting!

[1]
[http://www.tissuevision.com/nihms344616.pdf](http://www.tissuevision.com/nihms344616.pdf)

[2] [http://research.microsoft.com/en-
us/events/neml2014/](http://research.microsoft.com/en-us/events/neml2014/)

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csense
It says the data's available at [http://mouse.brain-
map.org/](http://mouse.brain-map.org/)

Is there a torrent available?

And what is the probability my ISP will cut me off for downloading 1.8 PB?

For that matter...I guess I'd need to buy ~600 3 TB hard drives to store
it...that would cost $60,000. Plus networking and servers...eep...

Why is it so big?

Suppose you have 75M neurons where each neuron has on average 1000 weighted
connections with other neurons. Then you would need 4 bytes per connection to
store the address and 4 more bytes to store the weight, for a total of

    
    
        (4 + 4 bytes) * 1,000 * 75,000,000 ~ 600 GB
    

This back-of-the-envelope computation is off by over three orders of
magnitude. What gives?

~~~
epistasis
The data they're talking about isn't anything like that at all, it's actually
micron-resolution 3D scans. Here's the abstract of the paper:

>Comprehensive knowledge of the brain’s wiring diagram is fundamental for
understanding how the nervous system processes information at both local and
global scales. However, with the singular exception of the C. elegans
microscale connectome, there are no complete connectivity data sets in other
species. Here we report a brain-wide, cellular-level, mesoscale connectome for
the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green
fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace
axonal projections from defined regions and cell types, and high-throughput
serial two-photon tomography to image the EGFP-labelled axons throughout the
brain. This systematic and standardized approach allows spatial registration
of individual experiments into a common three dimensional (3D) reference
space, resulting in a whole-brain connectivity matrix. A computational model
yields insights into connectional strength distribution, symmetry and other
network properties. Virtual tractography illustrates 3D topography among
interconnected regions. Cortico-thalamic pathway analysis demonstrates
segregation and integration of parallel pathways. The Allen Mouse Brain
Connectivity Atlas is a freely available, foundational resource for structural
and functional investigations into the neural circuits that support
behavioural and cognitive processes in health and disease.

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return0
They seem to be coming up with great work there. Unfortunately, thousands of
neuroscientists who have been sharing huge funds the past decade couldn't come
up with a big project like this one, it had to take private initiative to map
a mouse. To me this shows how badly allocated funding sets the bar too low for
most neuroscience teams.

And for those who say that this is not a big deal, it actually is a very big
deal. Not only for the connection map of the brain, which may or may not lead
to simulating a brain (we are far from that yet), but because we can analyze
the distributions of connections and their weights to infer possible
functional roles.

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rstoner
All of the data is available through a well-documented API: [http://www.brain-
map.org/api/index.html](http://www.brain-map.org/api/index.html)

Fully documented with plenty of examples and relevant white papers.

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joe_the_user
_" It’s hard to comprehend how, in this age of advanced science, experts don’t
know more about how the brain works. But it has a vastly complex structure."_

Yes, we have a map of 75 million thingies and how they interact in some ways
... but we don't really know _what_ even the interactions of just two neurons
"really mean," which parts of their many interactions are the important ones,
how they change over time and so-forth.

It does we humans a lot time to figure what an artifact from an alien human
civilization does, even a fairly simple one - and that figuring generally
involves something like figuring out the "blue print", the "purpose", the
"programming" and so-forth of such an artifact. These are all analogies with
our own intentional processes.

"Figuring out" the brain even as if it was a human-created artifact seems
immensely hard. Yet like DNA, the brain isn't human-created or created at
least-all. _It just happened,_ in ways whose understanding will clearly take a
lot of unraveling to really understand.

Not sure where I'm going with this aside from awe of the challenge.

~~~
deciplex
Pretty much _all_ human brains, that I know of, were created by humans.

~~~
jimmaswell
I guess they meant to say design.

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SapphireSun
For those of you with institutional access:
[http://www.nature.com/nature/journal/v508/n7495/full/nature1...](http://www.nature.com/nature/journal/v508/n7495/full/nature13186.html)

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s-macke
What is your guess about the amount of memory needed to save a human brain. I
mean all necessary information to save the personality. The article mentions
98,000 petabytes. But does this contain everything?

In Wolfram alpha and Wikipedia you can read, that the storage capacity of the
human brain is around 2-2.5PB.

When I estimate it assuming 10^14 synapses and 24 bytes (weight, connection
info, etc.) for each synapse, I come close to 2PB.

~~~
friendcomputer
The article lists 1.8P for a brain with 75 million neurons. Unless I've
misplaced my zeroes, that's over ~20M per neuron, which seems much higher than
I'd expect.

~~~
jostmey
A neuron is a lot more complicated than you would expect.

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d0m
I wish I'll be able to understand how the brain really work before dying. I
have the feeling that a deep understand of the brain will open scary and
amazing opportunities in AI.

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teddyknox
Summarizing previous points, a big criticism of studies like these is that
they don't have a huge potential to unearth real understanding of real neural
networks. The suggestion is to figure out the 302 neurons in [this little
worm]([https://en.wikipedia.org/wiki/Caenorhabditis_elegans](https://en.wikipedia.org/wiki/Caenorhabditis_elegans))
before attacking problems orders of magitude more difficult, like mouse and
human brains.

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yeukhon
Is it just me or people actually think it'd be even cooler to have a
visualization like the first image?

How do they actually know they have mapped everything right? How do they test
that?

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eli_gottlieb
For once I find the use of the "Singularity Hub" domain for mirroring a news
article entirely acceptable. Whole Brain Emulation for mice would be a big
step towards hyperintelligent lobster-ems, and from there it's only a short
step to killing all humans and spawning a Matrioshka Brain of capitalistic
rational agents that have optimized their consciousness, subjectivity, and
humanity away as market inefficiencies!

</Accelerando references>

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dalek2point3
two questions for someone more familiar with this area:

1\. what are the immediate applications of having such a dataset? either for
the mouse or the brain?

2\. once we have the map, will we also have the technology to identify
precisely what neurons are lighting up and how information is travelling
during certain actions / responses? in short how far are we from a green /
yellow / red Google Maps style traffic map for the brain?

~~~
return0
1\. There are some people who claim to make whole-brain simulations based on
earlier anatomical data [1,2]. I don't expect that anyone can make meaningful
predictions by simulating the new map, because the neuronal models used are
either rudimentary, or do not capture neuronal variability (also non-neuron
cells may be involved). However, the analysis of the connectivity between
various regions as well as intra-region may lead to accurate predictions about
what many circuits "do".

2\. Functional imaging is advancing, but it's still very hard to capture
large-scale neuronal activity. The current state of the art, calcium imaging
can visualize activity from one focal plane, not too many neurons at a time,
with slow time resolution, and only at the surface. I 'd say we are pretty far
from that as it would require some amazing imaging technology.

1\. [http://www.izhikevich.org/publications/large-
scale_model_of_...](http://www.izhikevich.org/publications/large-
scale_model_of_human_brain.htm)

2\. [http://bluebrain.epfl.ch/](http://bluebrain.epfl.ch/)

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DonGateley
If the human brain was simple enough to be understood it would be too simple
to understand.

We will glean bits and pieces but a detailed functional understanding of an
emergent system as large, containing as much feedback (within feedback), and
with as enormous a connectivity as any large (or probably even small)
mammalian brain is far beyond any reasonable expectation ever.

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karmicthreat
While this is a great first step, it is an amalgamation of images from over
1000 mice. Each mouse is going to have different connectome, though hopefully
we can distinguish major features more clearly now.

