This month's issue of Nature delivers a special on the brain that really gets you thinking. They take a detailed look at how Europe's Human Brain Project and the US BRAIN initiative are taking shape but the real prize is this interesting write-up on some of the most promising currently existing neuromorphic hardware. Check out Neurogrid, SpiNNaker, BrainScaleS, SyNAPSE and the neural net simulation called Spaun. http://www.nature.com/news/neuroelectronics-smart-connections-1.14089
Here's a collection of interesting bits from the article that will make you click onwards to read the thing in full.
Just a few years ago, Kwabena Boahen completed a device called Neurogrid that emulates a million neurons, about as many as there are in a honeybee's brain. Now applications for 'neuromorphic technology' are finally in sight.
In 2012 Boahen contacted Chris Eliasmith, who is responsible for Spaun: a design for a computer model of the brain that includes the parts responsible for vision, movement and decision-making. Previously, a simulation of Spaun on a conventional computer had shown that, with 2.5 million simulated neurons plus a simulated retina and hand, it could copy handwritten digits, recall the items in a list, work out the next number in a given sequence and carry out several other cognitive tasks. But the Spaun simulation ran about 9,000 times slower than real time, taking 2.5 hours to simulate 1 second of behaviour.
Boahen contacted Eliasmith with the obvious proposition: build a physical version of Spaun using real-time neuromorphic hardware. “I got very excited,” says Eliasmith, for whom the match seemed perfect. “You've got the peanut butter, we've got the chocolate!”
With funding from the US Office of Naval Research, Boahen and Eliasmith have put together a team that plans to build a small-scale prototype in three years and a full-scale system in five. For sensory input they will use neuromorphic retinas and cochleas developed at the INI, says Boahen. For output, they have a robotic arm. But the cognitive hardware will be built from scratch.
The system is explicitly designed for real-world applications. On a five-year timescale, says Boahen, “we envision building fully autonomous robots that interact with their environments in a meaningful way, and operate in real-time while [their brains] consume as much electricity as a cell phone”. Such devices would be much more flexible and adaptive than today's autonomous robots, and would consume considerably less power.
In the longer term, Boahen adds, the project could pave the way for compact, low-power processors in any computer system, not just robotics. If researchers really have managed to capture the essential ingredients that make the brain so efficient, compact and robust, then it could be the salvation of an industry about to run into a wall as chips get ever smaller.
“But we won't know for sure,” Boahen says, “until we try.”
Many of you have likely heard a thing or two about the recent Nobel prizes awarded for the development of the blue LED (physics), the discovery of cells that constitute a positioning system in the brain (Physiology/Medicine), and the super-resolution fluorescence microscopy technique (chemistry). If not, I've included some links below that will bring you up to speed.
One article I particularly enjoyed was one from nature that, apart from digging into the incredibly awesome science behind the discovery of the specialized brain cells that enable us to navigate our surroundings, also took some time to cast a light on the lives of the husband and wife team largely responsible for the breakthrough.
If anyone knows how we navigate home, it is the Mosers. They shot to fame in 2005 with their discovery of grid cells deep in the brains of rats. These intriguing cells, which are also present in humans, work much like the Global Positioning System, allowing animals to understand their location.
In 2007, while still only in their mid-40s, they won a competition by the Kavli Foundation of Oxnard, California, to build and direct one of only 17 Kavli Institutes around the world. The Mosers are now minor celebrities in their home country, and their institute has become a magnet for other big thinkers in neuroscience.
The Mosers' work has also given them traction at one of the most challenging twenty-first-century research frontiers: how the brain computes. Just as computers use programming languages such as Java, the brain seems to have its own operating languages — a bewildering set of codes hidden in the rates and timing with which neurons fire as well as the rhythmic electrical activities that oscillate through brain circuits. These codes allow the brain to represent features of the external world — such as sound, light, smell and position in space — in a language that it can understand and compute. With their grid-cell work, the Mosers have been the first to crack one such code deep in the brain; now the challenge for the field is to find all the rest.
The Mosers grew up on different Norwegian islands in the North Atlantic, where summer days seem eternal and the long winter nights are brightened only by the dancing Northern Lights. They were both from non-academic families and they went to the same school. But they didn't get to know each other until 1983, when both were at the University of Oslo, both were wondering what to study and both were starting to realize that their true passion was for neuroscience and the brain.
Suddenly, everything sparked: romance between the two of them, intellectual curiosity and the beginnings of their mission in life — to find out how the brain generates behaviour. The Mosers visited one of the university's more famous faculty members, electrophysiologist Per Andersen, and asked to do their undergraduate projects with him. Andersen was studying the activity of neurons in the hippocampus — a brain area associated with memory — and the two students wanted to try to link this precise activity of cells with the behaviour of animals. Andersen, like most neuroscientists at the time, was sceptical about making such a big leap across the black box of the brain. But the pair wouldn't leave his office until he gave in and offered them an apparently simple project: how much of the hippocampus could you cut away before a rat could no longer remember new environments?
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In 1984, while still undergraduates, the couple got engaged on top of the dormant volcano Mount Kilimanjaro in Tanzania. (The bitter temperature at the peak forced them to rush their exchange of rings, the quicker to get their gloves back on.) The pair had decided how their joint lives should be: children early, postdoc experience abroad and then their own lab together, somewhere in the world. These plans panned out — just a little faster than they had anticipated.
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Not every couple would find it easy to work together in such apparent harmony. The Mosers ascribe their ability to do so in large part to their patient temperaments and shared interests — in science and beyond. Both love outdoor activities: May-Britt runs every other day across the rugged hills around their coastal home, and Edvard hikes at weekends. They share an obsession with volcanoes — hence their engagement at the top of one — and have climbed many of the globe's most spectacular peaks.
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Edvard and May-Britt Moser: A journey into entorhinal cortex
It took some months before it dawned on them that they needed the rats to run around bigger boxes, so that the pattern would be stretched out and easier to see. At that point, it came into view: a near-perfect hexagon lattice, like a honeycomb. At first they refused to believe it. Such simplicity and regularity was the last thing they had expected — biology is usually a lot messier than this.
There were no physical hexagons traced on the floor; the shapes were abstractly created in the rat's brain and imposed on its environment, such that a single neuron fired whenever it crossed one of the points of the hexagon. The discovery was exciting for more than its pleasing pattern. This representation of space in brain-language was one of the long-sought codes by which the brain represents the world around us. “It was a long-drawn-out eureka moment,” recalls Edvard.
The Mosers also found that the different cells in the entorhinal cortex generate grids of many different types, like overlapping honeycombs — big, small and in every orientation and position relative to the box's border. And they ultimately came to see that the brain's grid cells are arranged according to a precise mathematical rule.
The cells that generate smaller grids, with narrower spacing, are at the top of the entorhinal cortex, and those that generate bigger grids are at the bottom. But it is even more exact than that: cells that make grids of the same size and orientation seem to cluster into modules. The modules are arranged in steps down the length of the entorhinal cortex, and the size of the grid represented by each module expands by a constant factor of 1.4 with every step.
The discoveries also astonished and thrilled theoreticians, because the hexagonal pattern is the optimal arrangement for achieving the highest-possible spatial resolution with a minimum number of grid cells. This saves energy, showing how beautifully efficient the brain can sometimes be. “Whoever would have believed that such a beautiful hexagonal representation existed so deep in the brain?” says Andreas Herz, a computational neuroscientist at the University of Munich in Germany.
Mindblowing stuff. There's a lot more where that came from so check out the article in full!
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?”
