Project on Brain
Three decades ago, the U.S. government launched the Human Genome Project, a 13-year endeavor to sequence and map all the genes of the human species. Although initially met with skepticism and even opposition, the project has since transformed the field of genetics and is today considered one of the most successful scientific enterprises in history.
Now the Intelligence Advanced Research Projects Activity (IARPA), a research organization for the intelligence community modeled after the defense department‚Äôs famed DARPA, has dedicated $100 million to a similarly ambitious project. The Machine Intelligence from Cortical Networks program, or MICrONS, aims to reverse-engineer one cubic millimeter of the brain, study the way it makes computations, and use those findings to better inform algorithms in machine learning and artificial intelligence. IARPA has recruited three teams, led by David Cox, a biologist and computer scientist at Harvard University, Tai Sing Lee, a computer scientist at Carnegie Mellon University, and Andreas Tolias, a neuroscientist at the Baylor College of Medicine. Each team has proposed its own five-year approach to the problem.
‚ÄúIt‚Äôs a substantial investment because we think it‚Äôs a critical challenge, and [it‚Äôll have a] transformative impact for the intelligence community as well as the world more broadly, ‚ÄĚ says Jacob Vogelstein at IARPA, who manages the MICrONS program.
MICrONS, as a part of President Obama‚Äôs BRAIN Initiative, is an attempt to push forward the status quo in brain-inspired computing. A great deal of technology today already relies on a class of algorithms called artificial neural networks, which, as their name would suggest, are inspired by the architecture (or at least what we know about the architecture) of the brain. Thanks to significant increases in computing power and the availability of vast amounts of data on the Internet, Facebook can identify faces, Siri can recognize voices, cars can self-navigate, and computers can beat humans at games like chess. These algorithms, however, are still primitive, relying on a highly simplified process of analyzing information for patterns. Based on models dating back to the 1980s, neural networks tend to perform poorly in cluttered environments, where the object the computer is trying to identify is hidden among a large number of objects, many of which are overlapping or ambiguous. These algorithms do not generalize well, either. Seeing one or two examples of a dog, for instance, does not teach the computer how to identify all dogs.
Humans, on the other hand, seem to overcome these challenges effortlessly. We can make out a friend in a crowd, focus on a familiar voice in a noisy setting, and deduce patterns in sounds or an image based on just one or a handful of examples. We are constantly learning to generalize without the need for any instructions. And so the MICrONS researchers have turned to the brain to find what these models are missing. ‚ÄúThat‚Äôs the smoking gun, ‚ÄĚ Cox says.
While neural networks retain elements of the architecture found in the brain, the computations they use are not copied directly from any algorithms that neurons use to process information. In other words, the ways in which current algorithms represent, transform, and learn from data are engineering solutions, determined largely by trial and error. They work, but scientists do not really know why‚ÄĒcertainly not well enough to define a way to design a neural network. Whether this neural processing is similar to or different from corresponding operations in the brain remains unknown. ‚ÄúSo if we go one level deeper and take information from the brain at the computational level and not just the architectural level, we can enhance those algorithms and get them closer to brain-like performance, ‚ÄĚ Vogelstein says.
The various teams will attempt to map the complete circuitry between all the neurons of a cubic millimeter of a rodent‚Äôs cortex. This volume, which constitutes less than one millionth the size of the human brain, may seem tiny. But to date, scientists have only been able to measure the activity of either a few neurons at a time or millions of neurons contained in the composite pictures obtained through functional magnetic resonance imaging. Now, the members of MICrONS plan to record the activity and connectivity of 100, 000 neurons while the rodent is engaged in visual perception and learning tasks‚ÄĒa relatively enormous feat, since it requires imaging, with nanometer resolution, the twists and turn of wires whose full length is a few millimeters. ‚ÄúThat‚Äôs like creating a road map of the U.S. by measuring every inch, ‚ÄĚ Vogelstein says.
Still, Vogelstein is optimistic because of recent support given for large-scale neuroscience research. ‚ÄúWith the advent of the BRAIN Initiative, an enormous number of new tools have come online for interrogating the brain both at the resolution and scale that‚Äôs required for recovering a detailed circuit diagram, ‚ÄĚ he says. ‚ÄúSo it‚Äôs a unique point in history, where we have the right tools, techniques, and technologies for the first time ever to reveal the wiring diagram of the brain at the level of every single neuron and every single synapse.‚ÄĚ
Each team plans to record the brain‚Äôs road map differently. Cox‚Äôs team will use a technique called two-photon microscopy to measure brain activity in rats as they are trained to recognize objects on a computer screen. The researchers will introduce a modified fluorescent protein, which is sensitive to calcium, into the rodents. When a neuron fires, calcium ions rush into the cell, causing the protein to glow brighter‚ÄĒso using a laser scanning microscope, the researchers will be able to watch the neurons as they‚Äôre firing. ‚ÄúThat‚Äôs a little bit like wire tapping the brain, ‚ÄĚ Cox says. ‚ÄúThe way you might listen in on a phone call to see what‚Äôs going on, we can listen in on important internal aspects of the brain while the animal is alive and doing something.‚ÄĚ
Then one cubic millimeter of the rat‚Äôs brain will be sent to Jeffrey Lichtman, a biologist and neuroscientist also at Harvard University. In Lichtman‚Äôs lab, it will be cut into incredibly thin slices and imaged under a state-of-the-art electron microscope at enough resolution to see all the wire-like extensions of brain cells that connect to each other. Tolias‚Äôs team is taking a similar approach, called three-photon microscopy, to look into the deeper layers of a mouse‚Äôs brain, and not just the top layers examined by Cox and his colleagues.
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Should I do my project on Amnesty International or Human Rights Watch
I think you should do it on Amnesty International. Although both would be very interesting and useful for you to know about.