Want to read Slashdot from your mobile device? Point it at m.slashdot.org and keep reading!


Forgot your password?
Science Technology

Method Rapidly Reconstructs Animal's Development Cell By Cell 39

An anonymous reader writes Researchers at the Howard Hughes Medical Institute's Janelia Research Campus have developed software that can track each and every cell in a developing embryo. The software will allow a researcher to pick out a single cell at any point in development and trace its life backward and forward during the embryo's growth. Philipp Keller, a group leader at Janelia says: "We want to reconstruct the elemental building plan of animals, tracking each cell from very early development until late stages, so that we know everything that has happened in terms of cell movement and cell division. In particular, we want to understand how the nervous system forms. Ultimately, we would like to collect the developmental history of every cell in the nervous system and link that information to the cell's final function. For this purpose, we need to be able to follow individual cells on a fairly large scale and over a long period of time."
This discussion has been archived. No new comments can be posted.

Method Rapidly Reconstructs Animal's Development Cell By Cell

Comments Filter:
  • Wow (Score:4, Funny)

    by Falos ( 2905315 ) on Monday July 21, 2014 @12:29PM (#47501371)
    When they can track everything every individual cell has ever done, you know it's time to rein in the surveillance state.

    Seriously though, promising tech.
  • Could this give us a method for mind uploading? If we are able to track every cell in the human brain, especially over time, we should be able to emulate it wholesale with one or two more layers of software (electrical and chemical signaling).

    Very exciting times we are living in.
    • No.

      What it MIGHT give you, eventually, is a set of observations on which to model the synhetic generation of nervous systems (and whole organisms if you have the CPU and memory to blow) within a computational model framework.

      What can you do with an emulated nervous system?

      Outside of medical research and drug candidate evaluations-- perhaps it could be useful for developing BCIs and the like-- but without a considerable amount more data than just what cells turn into what other cells, the model wont be usefu

      • by Ichijo ( 607641 )

        Also, full nervous system emulation is about the worst possible way to approach strong AI.

        Please elaborate. Why is it a bad way to approach strong AI, and what would be a better way?

        • Think about it this way--

          You have a system that does $FOO.

          you arent sure how it does $FOO, exactly. You see that inputs go in, some magical process $BAR happens inside, and $FOO comes out.

          Strong AI strives to reproduce this $FOO.

          The issue, is that the process $BAR is very much dependent on what the system is built from. (In this case, complex organic molecules and saline ions). Understanding $BAR is insanely hard, because $BAR is carried out in a highly parallelized fashion, with many many subprocesses goin

          • by Ichijo ( 607641 )

            Slavishly reimplement millions of models in the new medium's physical construction...

            You make it sound like implementing one million cells in software is a million times more difficult than implementing just one.

          • Do you:

            1) Slavishly reimplement millions of models in the new medium's physical construction, to emulate the quirks and behaviors of the target system's physical construction, wasting huge amounts of energy and making a system that is actually *MORE* complex than the original....


            2) Deconstruct all the mechanisms at work in the physical system that currently performs $BAR to get $FOO, evaluate which of these are hardware dependent, and can be removed/adapted to high efficiency analouges in the new hardware platform-- and produce only the components needed for $BAR to be accomplished, to generate $FOO?

            The former will most certainly get you $FOO, but is HORRIBLY INEFFICIENT, and does not really shed light on what is actually needed to get $FOO.

            The latter is MUCH HARDER to do, as it requires actually understanding the process, $BAR, through which $FOO is attained. It will however, yeild the higher efficiency synthetic system, AND the means to prove that it is the best possible implementation.

            Basically, it's the difference between building a rube-goldberg contraption, VS an efficient machine.

            We've been trying, in various ways, to do #2, but can't do it yet. So, we're trying to do #1, analyse it, and then do #2. You say that we should 'produce only the components needed', but really, that's the crux of the matter. We don't know what the components needed are. We can't even simulate a worm yet at either the individual cell OR functional level; see the OpenWorm project (http://www.openworm.org/) for an attempt at the former. We can use that sort of model organism to figure out what the impor

    • No.

      This method is currently only for embryology studies. They are only able to track each cell while it is being observed. There are no tracking devices placed into these cells.

      What you are proposing would be roughly 100 orders of magnitude more complex. In addition to each cell you'd have to track each synapse connection, which ranges in the 100s of billions.

      The only way I could see 'mind uploading' work is if there was some MRI-like machine that could resolve down to the molecular level and wa
      • by tmosley ( 996283 )
        Well damn.

        Uploading can also work by doing it gradually, replacing neurons one at a time with artificial ones, or fast links to an emulator. This could actually be done after being placed in a Matrix-like device that replaces signals going into and out of the brain. This has the upshot of not creating copies, meaning that there isn't a "you" that dies in the process.
        • Replacing neurons with artificial ones sounds iffy, but other than that I think you're on the right track. So-called 'brains in jars' are probably the way it'll get done. Instead of artificial neurons I could see GM neurons or GM viruses keeping your existing neurons in tip-top shape. Given sufficient sensory stimulation and input there's no physical reason why this could happen indefinitely. Moving from neurons to 'not neurons' is going to be extremely difficult, if not practically impossible.
          • Actually they are already beginning to experiment with this - IIRC they've managed to emulate "generic" subsections of rat brain to the point where they can wire in a simulated version to restore much of the functionality lost by destroying the original. Very crude, and I doubt personality would would be preserved even with an exact copy. But undeniably cool.

    • Not really. The embryo here is a fruit fly. They're small enough to see the entire thing with a microscope. Vertebrates tend to get too big to image completely with current microscopes really early on in development. A human brain is way too big to image completely with a microscope without slicing it thinner than lunch meat.
    • Well, if neurons worked like transistors, perhaps. However available evidence is that each neuron operates more like an embedded processor, possessing memory and firing in response to some sort of non-trivial analysis of the state of the 7,000 (average for a human) synaptic connections is possesses. That suggests that in order to make an artificial copy of a mind we'd first have to figure out how to emulate individual neurons and possibly even record their internal states. And of course emulate the vario

  • This sounds quite amazing. What's the catch?
    • Re:What? (Score:4, Insightful)

      by Anonymous Coward on Monday July 21, 2014 @01:11PM (#47501753)
      It only tracks the nuclei (which will provide very little information about a nervous system) from existing image data. It is not currently not even possible to image how the final nervous system of a fruit fly is setup so that this software could be run. They are too thick and opaque for any current microscopy technique to use while alive. Philipp Keller also developed a microscopy technique for imaging this type of data. I've tried using it on flies, and it doesn't work.
      • In fairness fly neurons appear to be far more sophisticated than those of humans - we had the luxury of being able to just keep adding more neurons at minimal cost in order to build more sophisticated structures - as long as those extra neurons on average put more calories in our bellies than they consumed they were a clear win. Flies on the other hand have extremely tight mass and volume constraints, and as a result the individual neurons had to become more sophisticated instead - to the point where an in

        • Very interesting; is there a technical book (or chapter) or paper with a good overview of this comparative aspect of fly neurons?

          I was just starting to look around to see what's available on comparative neuroscience in general, based on an interest in the most salient functional differences from human neurons, so anything related to that more general topic would also be welcome.

          • Can't offer one offhand - there was a TED talk on it not too terribly long ago though, and they may have a few references.

  • Cell Division

    1 cell becomes 2 cells -- which cell does it follow?

    • Both -- track the entire tree. Seems like an obvious thing to try...on retrospect.

      Once you know this, you can start looking for conttol mechanisms at the DNA and chemistry level.

    • Cell Division

      1 cell becomes 2 cells -- which cell does it follow?

      My understanding is that it can follow both. "Once a cluster of supervoxels has been identified as a cell nucleus, the computer uses that information to find the nucleus again in subsequent images." That sounds like extraordinarily cool technology. Tracking the embryonic development of cells is currently very hard. For really simple organisms, each embryonic cell can be tracked to one or more fixed descendent cells in known locations. For most organisms however, where a given embryonic cell ends up is a n

  • Wasn't this the opening scene for Jurassic Park?

  • by Anonymous Coward

    I wonder how thick the imaging works over.

    For a mouse, how far can they image the development.

    • Hmm, I seem to remember some folks a while back figuring out how to replace the fats in neurons to render a brain transparent. If they could figure out how to do that, even partially, without killing the organism in the process, then it could dramatically increase the power of this tracking.

  • I know it sounds vain but it does also have practical applications for people with muscular deficiencies owing to immobility. From what I've gathered, no one really knows what happens, precisely, to cause muscles to "grow". Sure, there's a hundred different theories tossed around on body building forums, but a lot of sounds more like pseudo-biological nonsense rather than real science. There's precious little experiment in the field and my lay understanding is that it is because the only method of looking

All Finagle Laws may be bypassed by learning the simple art of doing without thinking.