After an appropriate transport period, the brain is
perfused, sectioned, suitably stained, and each section
digitally imaged. These 2-D images are co-registered into a
3-D computer stack that is subsequently registered to a
common reference atlas. The resulting 3-D brain image is
largely unlabeled (i.e., contains no signal of interest),
except for the connections between the injected region and
its target regions. Thus the labeled connections are
clearly identifiable. A given region is injected in
multiple animals to account for individual variability.
They do two passes, in each pass they stain mouse brain cells in a particular region, then they kill the mouse, slice its brain, and image the slices. While this method certainly works well on mice (I've seen surgical work done of mice first hand, neat stuff), sadly it doesn't quite scale up to imaging the human brain. But having all those (petabytes) of data has gotta be worth something.
I must be missing something. When I think of connections, I think of synapses or gap junctions -- the coupling of one neuron to others through a signaling mechanism. Their tracers do the equivalent of segmentation of neurons, which doesn't give you the connections, just the morphology of neurons. You left out what seems to be a key part of their method -- use of retrograde tracers that are taken up by axon terminals. These retrograde tracers have to be injected into likely end points. Seems like its an interesting technique for mapping a limited number of connections but useless for producing a comprehensive connectome due to required injection density. Am I missing some aspect of this that allows generation of a connectome?
It's misleading to use the term "wiring diagram for entire mouse brain". An engineer wouldn't consider it a wiring diagram if you stripped out a majority of the contact descriptions and just said there's a wire here, here, and here.
Well, there are both retrograde and anterograde tracers. So you can trace from either target->source or source->target depending on your choice of tracer.
These tracers are used to map circuits because they are passed from one neuron to the next via functional synapses...which means that any neuron that is stained must have been in contact with a previous neuron, etc etc.
The "connectome" is built up by injecting a limited amount of tracer in a single region, in multiple animals, to provide a mapping of that region. To get the entire brain you need lots and lots of injections in a very large number of mice (and a lot of technicians slaving away over cryostats).
To your point about not labeling synapses and gap junctions: those are relatively unimportant when considering wiring diagrams of the brain. What is more important is knowing which partners a neuron synapses onto. You don't really care how many synapses are involved unless you are looking at single or clusters of neurons, nor can you really measure it without some other method (e.g. electrophysiology).
Caveat about tracers which often goes unannounced: the staining of a tracer in a secondary neuron is only as strong as the connection between the primary and the secondary. Which means that a neuron who synapses strongly will be much brighter than a neuron that synapses weakly. Similarly, tertiary (and quaternary, etc) neurons become progressively weaker stained as the exponential dilution of the tracer kicks in.
The title is a little misleading. What they've done is effectively created hundreds of snapshots of neural connectivity, each focusing on how one particular region of the brain hooks into another. The goal is to make this data available so experts and hobbyists alike can potentially identify connections that offer insight into brain function and disease.
An analogy would be trying to reconstruct the street layout of a city by taking pictures from a plane as it flew over. Each time you fly past, you might get a different angle, different weather conditions, or try a different camera. Now you have hundreds of photos, and you are hoping people who know things about cities will find useful information there, like where the best restaurants might be located.
Disclosure: I worked on the front-facing side of this project (data browser and image viewer).
There's a number of scientific researchers on HN (I'm recently ex-neurosci, and I've contacted a number of other people through their profiles to chat about biology stuff).
Great project, and especially great that the data is available for public study!
I'm not keen on the article title though. 'Scientists trace a wiring plan...' sounds like it has been done already (present tense in news articles tends to read this way), which is completely false - as work on the 'wiring plan' has hardly even begun. I didn't expect Nature would be so 'headliney'...
I've written a blog post once, dreaming about having a backup of my brain put on S3 and working as a programmer on(in?) a EC2 instance to earn enough money to keep Amazon from (killing?) discontinuing the service for me.
Now I see that this is much closer to reality than I thought.
Interesting how young programmers would compete with a guy who can work 24/7 and have 250 years of professional experience...
I like Sci-Fi and sometimes I fantasize with a world where brains have become (non-self-conscious) processing power connected to a big terminal; with such a vast amount of analytic power that you can brute-force 100 billions of passwords in one second and where you can focus the abstract thinking (aka creativity) of all the brains into one specific problem; leading to a lot of new discoveries.
I believe this is the future of AI research. Once we could map all components of a mouse brain to their logic software equivalents and then let this simulation run, we could make significant steps towards learning what intelligence in animals really constitutes. I believe the current images of the mouse brain are yet insufficient to derive a logical circuitry from, but I'm sure that will be possible in time.
Connectomes are only a small part though. Individual neurons are still largely black-boxes. So you may know how they wire, but you still need to figure out how they respond to each other locally, regionally and across the whole brain.
I agree though, it's cool stuff and definitely the way forward.
I have a question about this, I know that we have a complete wiring diagram of all 302 neurons in the C. elegans nervous system, so are we able to simulate that neural network and see the same behaviours as in the living nematode worm? I've seen papers that's focused on the locomotion circuit and other parts but I don't seem to be able to find any attempts at simulating the whole thing at once.
> (...) are we able to simulate that neural network and see the same
> behaviours as in the living nematode worm?
No. With biological networks, wiring diagrams are only part of the bigger picture; (electro-)physiological differences matter a lot. This is especially true for small systems in which individual neurons perform highly specialized functions. (Mammalian neurons are substantially more generic!)
So the short answer is no; the longer answer is we're slowly getting there. Key problems are lack of plausible feedback from sensory etc. systems as well as currently inexplicable in vivo/in silico disparities.
The full set of information needed to model the c elegans worm seems to still be incomplete (see apl's reply), but if you want to monitor the progress of one such attempt at in silico simulation, take a look at the Openworm project ( http://www.openworm.org/ ).
My information is a few years old, and hearsay, but I gather that research focuses on locomotion because the worm moves differently than the wiring would imply. Which suggests that this mouse brain wiring will have less immediate utility than you might hope.
Sharing the images is great, but they are of little use without segmentation. The macroconnectome describes connections between regions. How are people supposed to collaborate if everybody comes up with a different way of overlaying atlas regions on each brain slice?
The Nature article is a bit too optimistic. Just because we can establish semi-quantitative connectivity levels between cortical regions with varying degrees of accuracy (many things can go wrong when injecting the tracer) it doesn't mean that a complete map of cell level connectivity is just around the corner. Hell, we disregard electrical synapses completely right now...
[1] http://brainarchitecture.org/mouse/documentation/project-whi...