The town of Lund, in Sweden, is already home to a number of major scientific facilities, including one of the most advanced synchrotron X-ray sources, the MAX IV, scheduled for inauguration in 2016. Now Lund will also be the site of the world's most powerful neutron source, the €1.8 billion European Spallation Source (ESS).
Spallation is the process for producing neutrons by means of a particle accelerator and a heavy metal target. The ESS's 600-meter long linear accelerator will fire protons derived from hydrogen gas at a velocity just below the speed of light at a target made out of the metal tungsten.
The metal target absorbs the proton beam and transforms into fast neutrons. Which is basically just a really polite way of saying that the proton beam rips the target a new one which causes it to spill its guts all over the place, showering its environment with fast neutrons. To contain the extreme level of highly penetrating gamma and fast neutron radiation the target chamber is surrounded by a radiation shielding system, a 7000 ton sphere of steel. If that kind of talk doesn't get your heart racing I don't know what will! ;)
When the neutrons are slowed down they are, guided by beam lines, lead towards experimental stations where they allow us to see through matter on the smallest of scales. Because neutrons have no charge, they don't scatter on electrons and can penetrate deep into atoms and probe atomic nuclei directly, which is not possible with X-rays.
Two factors make neutrons especially interesting. With X-rays you only "see" the heavy elements, but with neutrons, which interact with light elements such as hydrogen and carbon, you can probe a wider range of materials, with applications in molecular biology, biomedical research, and even food science.
The second factor is that neutrons carry a magnetic moment. They interact with the magnetic moments of atoms and thus can assist researchers investigating materials like superconductors.
A big thanks to the more than a dozen European countries that are funding the project, especially Sweden and Denmark, the two biggest backers. If all goes well first light should be produced in 2019.
Normally, you have to collect particles that come from the object to image it, says Anton Zeilinger, a physicist at the Austrian Academy of Sciences in Vienna who led the work. “Now, for the first time, you don’t have to do that."
One advantage of this imaging technique is that the two photons need not be of the same energy, Zeilinger says, meaning that the light that touches the object can be of a different colour than the light that is detected. For example, a quantum imager could probe delicate biological samples by sending low-energy photons through them while building up the image using visible-range photons and a conventional camera. (!)
According to the laws of quantum physics, if no one detects which path a photon took, the particle effectively has taken both routes, and a photon pair is created in each path at once, says Gabriela Barreto Lemos, a physicist at Austrian Academy of Sciences and a co-author on the latest paper.
In the first path, one photon in the pair passes through the object to be imaged, and the other does not. The photon that passed through the object is then recombined with its other ‘possible self’ — which travelled down the second path and not through the object — and is thrown away. The remaining photon from the second path is also reunited with itself from the first path and directed towards a camera, where it is used to build the image, despite having never interacted with the object.
The researchers imaged a cut-out of a cat, a few millimetres wide, as well as other shapes etched into silicon. The team probed the cat cut-out using a wavelength of light which they knew could not be detected by their camera. "That's important, it's the proof that it's working," says Zeilinger.
Information is central to quantum mechanics. In particular, quantum interference occurs only if there exists no information to distinguish between the superposed states. The mere possibility of obtaining information that could distinguish between overlapping states inhibits quantum interference. Here we introduce and experimentally demonstrate a quantum imaging concept based on induced coherence without induced emission.
The experiment is fundamentally different from previous quantum imaging techniques, such as interaction-free imaging or ghost imaging, because now the photons used to illuminate the object do not have to be detected at all and no coincidence detection is necessary. This enables the probe wavelength to be chosen in a range for which suitable detectors are not available. To illustrate this, we show images of objects that are either opaque or invisible to the detected photons.
Shortened edit of a NYT article worth reading in full;
In 2005, Sebastian Seung suffered the academic equivalent of an existential crisis. Seung was growing increasingly depressed. He and his colleagues spent their days arguing over how the brain might function, but science offered no way to scan it for the answers. “It seemed like decades could go by,” Seung told me recently, “and you would never know one way or another whether any of the theories were correct.”
That November, Seung sought the advice of David Tank, a mentor he met at Bell Laboratories. Over lunch Tank administered a radical cure. He informed Seung of a former colleague in Heidelberg, Germany, Winfried Denk, who had just built a device that imaged brain tissue with enough resolution to make out the connections between individual neurons... Less than a month later Seung arrived at the Max Planck institute where Denk introduced him to the high-resolution brain-imager he had built.
Now, eight years later, Seung has become the leading proponent of a plan to create a wiring diagram of all 100 trillion connections between the neurons of the human brain, an unimaginably vast and complex network known as the connectome.
If science were to gain the power to record and store connectomes, then it would be natural to speculate, as Seung and others have, that technology might some day enable a recording to play again, thereby reanimating a human consciousness. The mapping of connectomes, its most zealous proponents believe, would confer nothing less than immortality.
For now he hopes to prove that he can find a specific memory in the brain of a mouse and show how neural connections sustain it.
What makes the connectome’s relationship to our identity so difficult to understand, Seung told me, is that we associate our “self” with motion. We walk. We sing. We experience thoughts and feelings that bloom into consciousness and then fade. “Psyche” is derived from the Greek “to blow,” evoking the vital breath that defines life. “It seems like a fallacy to talk about our self as some wiring diagram that doesn’t change very quickly,” Seung said. “The connectome is just meat, and people rebel at that.”
When Seung started, he estimated that it would take a single tracer roughly a million years to finish a cubic millimeter of human cortex — meaning that tracing an entire human brain would consume roughly one trillion years of labor. He would need a little help.
In 2012, Seung started EyeWire, an online game that challenges the public to trace neuronal wiring — now using computers, not pens — in the retina of a mouse’s eye. Seung’s artificial-intelligence algorithms process the raw images, then players earn points as they mark, paint-by-numbers style, the branches of a neuron through a three-dimensional cube.
Ultimately, Seung still hopes that artificial intelligence will be able to handle the entire job. But in the meantime, he is working to recruit more help. In August, South Korea’s largest telecom company announced a partnership with EyeWire, running nationwide ads to bring in more players. In the next few years, Seung hopes to go bigger by enticing a company to turn EyeWire into a game with characters and a story line that people play purely for fun. “Think of what we could do,” Seung said, “if we could capture even a small fraction of the mental effort that goes into Angry Birds.”
To explain what he finds so compelling about the substance of the brain, Seung points to stories of near death. Like the one of a young doctor named Anna Bagenholm who miraculously recovered from being clinically dead for more than 2 hours. Even after the cold arrested Bagenholm’s heart and hushed her crackling neuronal net to a whisper, her connectome endured.
At the Janelia Research Campus you can find MERLIN, a pair of hulking beige devices, a next generation brain-imaging system. The system combines slicing and imaging: An electron microscope takes a picture of the brain sample from above, then a beam of ions moves across the top, vaporizing material and revealing the next layer of brain tissue for the microscope. It is, however, a “temperature-sensitive beast,” said Shan Xu, a scientist at Janelia. If the room warms by even a fraction of a degree, the metal can expand imperceptibly, skewing the ion beam, wrecking the sample and forcing the team to start over. Xu was once within days of completing a monthslong run when a July heat wave caused the air-conditioning to hiccup. All the work was lost. Xu has since designed elaborate fail-safes, including a system that can (and does) wake him up in the middle of the night; Janelia has also invested several hundred thousand dollars in backup climate control. “We’ve learned more about utilities than you would ever want to know,” Hess said.
Here at Janelia, connectome science will face its most demanding test. Gerry Rubin, Janelia’s director, said his team hopes to have a complete catalog of high-resolution images of the fruit-fly brain in a year or two and a completely traced wiring diagram within a decade. Rubin is a veteran of genome mapping and saw how technological advances enabled a project that critics originally derided as prohibitively difficult and expensive. He is betting that the story of the connectome will follow the same arc. Ken Hayworth, a scientist in Hess’s lab, is developing a way to cleanly cut larger brains into cubes; he calls it “the hot knife.” In other labs, Jeff Lichtman of Harvard and Clay Reid of the Allen Institute for Brain Science are building their own ultrafast imaging systems. Denk, Seung’s longtime collaborator in Heidelberg, is working on a new device to slice and image a mouse’s entire brain, a volume orders of magnitude larger than what has been tried to date.
As connectomics has gained traction, though, there are the first hints that it may be of interest to more than just monkish academics. In September, at a Brain Initiative conference in the Eisenhower building on the White House grounds, it was announced that Google had started its own connectome project. Tom Dean, a Google research scientist and the former chairman of the Brown University computer-science department, told me he has been assembling a team to improve the artificial intelligence: four engineers in Mountain View, Calif., and a group based in Seattle. To begin, Dean said, Google will be working most closely with the Allen Institute, which is trying to understand how the brain of a mouse processes images from the eye. Yet Dean said they also want to serve as a clearinghouse for Seung and others, applying different variations of artificial intelligence to brain imagery coming out of different labs, to see what works best.
It’s possible now to see a virtuous cycle that could build the connectome. The artificial intelligence used at Google, and in EyeWire, is known as deep learning because it takes its central principles from the way networks of neurons function. This could, in the coming decades, lead to more insights about neural networks, improving deep learning itself — the premise of a new project funded by Iarpa, a blue-sky research arm of the American intelligence community, and perhaps one reason for Google’s interest. Better deep learning, in turn, could be used to accelerate the mapping and understanding of the brain, and so on.
Eve Marder, a prominent neuroscientist at Brandeis University, cautions against expecting too much from the connectome. She studies neurons that control the stomachs of crabs and lobsters. In these relatively simple systems of 30 or so neurons, she has shown that neuromodulators — signaling chemicals that wash across regions of the brain, omitted from Seung’s static map — can fundamentally change how a circuit functions. If this is true for the stomach of a crustacean, the mind reels to consider what may be happening in the brain of a mouse, not to mention a human.
“If we want to understand the brain,” Marder says, “the connectome is absolutely necessary and completely insufficient.”
Seung agrees but has never seen that as an argument for abandoning the enterprise. Science progresses when its practitioners find answers — this is the way of glory — but also when they make something that future generations rely on, even if they take it for granted. That, for Seung, would be more than good enough. “Necessary,” he said, “is still a pretty strong word, right?”
