Neuroscience & Cognitive Computing

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Israel Rosenfield, Edward Ziff, How the Mind Works: Revelations. New York Review of Books, Volume 55, Number 11 · June 26, 2008. Overview of neurobiology, in a review of seven recent books. Good explanations of brain function.

Neurobiology: Turing's Enigma Solution. Professor Michael Shadlen's talk at CSE Colloquia - 2006, The University of Washington Computer Science & Engineering Colloquium Series, available from the ResearchChannel ("a non-profit organization founded in 1996 by a consortium of leading research universities, institutions and corporate research centers dedicated to creating a widely accessible voice for research through video and Internet channels").

Resolution of Uncertainty in Prefrontal Cortex. By Wako Yoshida and Shin Ishii. Neuron 50: 781-789, June 2006. "Making optimal decisions in the face of uncertain or incomplete information arises as a common problem in everyday behavior, but the neural processes underlying this ability remain poorly understood. ... Here, we use functional magnetic resonance imaging during a maze navigation task to study neural activity relating to the resolution of uncertainty as subjects make sequential decisions to reach a goal. We show that distinct regions of prefrontal cortex are engaged in specific computational functions that are well described by a Bayesian model of decision making. This permits efficient goal-oriented navigation and provides new insights into decision making by humans."

CMU finds human brains similarly organized. By David Templeton. Pittsburgh Post-Gazette (January 4, 2008). "Carnegie Mellon University has taken an important step in mapping thought patterns in the human brain, and the research has produced an amazing insight: Human brains are similarly organized. Based on how one person thinks about a hammer, a computer can identify when another person also is thinking about a hammer. It also can differentiate between items in the same category of tools, be it a hammer or screwdriver. ... For this study, Tom M. Mitchell, chairman of Carnegie Mellon's department of machine learning, and other scientists on the team developed the algorithm, or computer procedure used to analyze brain patterns, that was precise enough to tell accurately what tool the person was observing. Using that general pattern, the computer then could identify when others were looking at and thinking about the same image. The study makes two important scientific advances: '[T]here is an identifiable neural pattern associated with perception and contemplation of individual objects, and that part of the pattern is shared' by people."

• Also see this video: Mind Reading. ScienCentral News (February 2, 2008). "As pollsters have so well demonstrated this presidential primary season, reading minds, whether of voters or the person next to you, is close to impossible. However as this ScienCentral News video [embedded in article] explains, scientists are actually one step closer to reading our thoughts. ... Researchers using MRI imaging have gone from studying peoples' brains to identifying specific thoughts, allowing them to tell which of 10 similar objects a person is viewing or thinking about. ... [T]he new research is aimed at the biology underlying thoughts-- or, as scientists call them, 'cognitive processes.' Carnegie Mellon cognitive psychologist Marcel Just teamed up with machine learning expert Tom Mitchell to conduct the research. They scanned the brains of people who looked at sets images of similar objects-- like 10 types of tools, or 10 types of homes. ... They used machine learning techniques similar to those used in other types of pattern recognition, including when you swipe your credit card to make a purchase, Mitchell says. 'When you swipe your credit card through a transaction and they approve it, that approval is done by computers based on having analyzed many historcial transactions and determining what's common to the fraudulent ones versus the normal ones and using that pattern. We do the same thing with brain images.' ... 'The biggest news here is in field of cognitive neuroscience,' Mitchell says."

Brainy Robots Start Stepping Into Daily Life. By John Markoff. The New York Times (July 18, 2006). "Robot cars drive themselves across the desert, electronic eyes perform lifeguard duty in swimming pools and virtual enemies with humanlike behavior battle video game players. These are some fruits of the research field known as artificial intelligence, where reality is finally catching up to the science-fiction hype. A half-century after the term was coined, both scientists and engineers say they are making rapid progress in simulating the human brain, and their work is finding its way into a new wave of real-world products. The advances can also be seen in the emergence of bold new projects intended to create more ambitious machines that can improve safety and security, entertain and inform, or just handle everyday tasks. ... Today some scientists are beginning to use the term cognitive computing, to distinguish their research from an earlier generation of artificial intelligence work. What sets the new researchers apart is a wealth of new biological data on how the human brain functions. 'There's definitely been a palpable upswing in methods, competence and boldness,' said Eric Horvitz, a Microsoft researcher who is president-elect of the American Association for Artificial Intelligence. ... 'There is a new synthesis of four fields, including mathematics, neuroscience, computer science and psychology,' said Dharmendra S. Modha, an I.B.M. computer scientist. 'The implication of this is amazing. What you are seeing is that cognitive computing is at a cusp where it's knocking on the door of potentially mainstream applications.'"

AI set to exceed human brain power. CNN.com (July 25, 2006). "Mention Artificial Intelligence and most people are immediately transported into a distant future inspired by popular science fiction. Humankind either co-exists in blissful peace with subservient robots and conscious computers or faces a battle for survival against ultra-smart psychotic machines set on its destruction. Yet Artificial Intelligence (AI) has already been with us for half a century. The phrase was first coined by Professor John McCarthy for a conference on the subject at Dartmouth College in 1956. And while the AI fantasies imagined by science fiction writers such as Isaac Asimov, author of 'I, Robot,' may not have materialized, AI is already in more common usage than many of us might imagine. Nick Bostrom, Director of the Future of Humanity Institute at the UK's Oxford University, said that AI-inspired systems were already integral to many everyday technologies such as internet search engines, bank software for processing transactions and in medical diagnosis. ... In the short-term, developments in AI are likely to lead to more mundane technological improvements, such as more intuitive search engines and more sophisticated pattern recognition software. Yet Bostrom is confident that technological advances coupled with a growing understanding of the workings of the human brain could enable machines to exceed human brain power within a couple of decades."

It's Alive (ish). By Brandon Keim. Wired News (August 1, 2006). "Scientists at the Georgia Institute of Technology figured they could learn more from neuron clumps that acted more like real brains, so they've developed 'neurally controlled animats' -- a few thousand rat neurons grown atop a grid of electrodes and connected to a robot body or computer-simulated virtual environment. In theory, animats seem to cross the line from mass of goo to autonomous brain. But Steve Potter, a neuroscientist and head of the Georgia Tech lab where the animats were created, said his brain clumps won't be reciting French philosophy anytime soon. ... Potter's team programs a robot to associate neural firing patterns with actions. ... While he's quick to disavow any comparisons to Dr. Frankenstein, Potter admits the clumps have a certain amount of awareness. ... Potter hopes his research will eventually lead to better neural prosthetics, understanding of neural pathologies and even artificial intelligence. As for consciousness, he said, 'I don't think it will get that far. But I'd love to be proven wrong.'"

New brain imaging technique . BBC News Video [accessed November 2, 2007]. "Researchers have developed a new brain mapping technique showing complex connections in colour."

Mimicking How the Brain Recognizes Street Scenes. CCNmag.com (February 6, 2007). "At last, neuroscience is having an impact on computer science and artificial intelligence (AI). For the first time, scientists in Tomaso Poggio’s laboratory at the McGovern Institute for Brain Research at MIT applied a computational model of how the brain processes visual information to a complex, real world task: recognizing the objects in a busy street scene. The researchers were pleasantly surprised at the power of this new approach. ... 'People have been talking about computers imitating the brain for a long time,' said Poggio, who is also the Eugene McDermott Professor in the Department of Brain and Cognitive Sciences and the co-director of the Center for Biological and Computational Learning at MIT. 'That was Alan Turing’s original motivation in the 1940s. But in the last 50 years, computer science and AI have developed independently of neuroscience. Our work is biologically inspired computer science.' ... Near-term applications include surveillance and automobile driver’s assistance, and eventually visual search engines, biomedical imaging analysis, robots with realistic vision."

• Visit The Center for Biological & Computational Learning (CBCL) and The McGovern Institute for Brain Research, both being located at MIT.

Hearts & Minds - Since Plato, scholars have drawn a clear distinction between thinking and feeling. Now science suggests that our emotions are what make thought possible. By Jonah Lehrer. The Boston Globe (April 29, 2007). "Just over 50 years ago, a group of brash young scholars at an MIT symposium introduced a series of ideas that would forever alter the way we think about how we think. In three groundbreaking papers, including one on grammar by a 27-year-old linguist named Noam Chomsky, the scholars ignited what is now known as the cognitive revolution, which was built on the radical notion that it is possible to study, with scientific precision, the actual processes of thought. The movement eventually freed psychology from the grip of behaviorism, a scientific movement popular in America that studied behavior as a proxy for understanding the mind. ... From its inception, the cognitive revolution was guided by a metaphor: the mind is like a computer. We are a set of software programs running on 3 pounds of neural hardware. And cognitive psychologists were interested in the software. The computer metaphor helped stimulate some crucial scientific breakthroughs. It led to the birth of artificial intelligence and helped make our inner life a subject suitable for science. For the first time, cognitive psychologists were able to simulate aspects of human thought. At the seminal MIT symposium, held on Sept. 11, 1956, Herbert Simon and Allen Newell announced that they had invented a 'thinking machine' -- basically a room full of vacuum tubes -- capable of solving difficult logical problems. (In one instance, the machine even improved on the work of Bertrand Russell.) ... But the computer metaphor was misleading, at least in one crucial respect. Computers don't have feelings. Feelings didn't fit into the preferred language of thought. Because our emotions weren't reducible to bits of information or logical structures, cognitive psychologists diminished their importance. ... This new science of emotion has brought a new conception of what it means to think, and, in some sense, a rediscovery of the unconscious. ... The lasting influence of the cognitive revolution is apparent in the language used by neuroscientists when describing the mind. For example, the unconscious is often described as a massive computer, processing millions of bits of information per second. Emotions emerge from this activity."

Can our brains understand themselves? They're tough nuts to crack even for the brainiest of scientists. By Jeanna Bryner. LiveScience via MSNBC.com (August 2, 2007). "Our brains can fathom the beginning of time and the end of the universe, but is any brain capable of understanding itself? ... Neurologists and cognitive scientists nowadays are probing how the mind gives rise to thoughts, actions, emotions and ultimately consciousness. ... 'Whether the human brain can understand itself is one of the oldest philosophical questions,' said Anders Garm of the University of Copenhagen, Denmark.... Scientists have made some progress in taking an objective, direct 'look' at the human brain. In recent years, brain-imaging techniques, such as functional magnetic resonance imaging (fMRI) have allowed scientists to observe the brain in action and determine how groups of neurons function."

Brain2Robot project at the Fraunhofer Institute for Computer Architecture and Software Technology (FIRST): "The aim of the EU funded Brain2Robot project is to develop a prosthetic control system based on intended movements. ... Electrodes attached to the patient’s scalp measure the brain’s electrical signals. These are then amplified and transmitted to the computer. High-efficiency algorithms analyze these signals using machine-learning methods. They are capable of detecting changes in brain activity triggered by the purely mental conception of a particular behaviour. They can, for instance, unequivocally identify patterns reflecting the idea of moving the left or right hand and extract them from the many millions of neural impulses. They are then converted into control commands for the computer, enabling one to choose, for example, between two alternatives. Here – and this is the Fraunhofer researchers’ particular achievement – the main learning task is performed by the computer."

Reverse-Engineering the Brain - At MIT, neuroscience and artificial intelligence are beginning to intersect. By Fred Hapgood. Technology Review (July 11, 2006). "'Maggie is a very smart monkey,' says Tim Buschman, a graduate student in Professor Earl Miller's neuroscience lab. Maggie isn't visible -- she's in a biosafety enclosure meant to protect her from human germs -- but the signs of her intelligence flow over two monitors in front of Buschman. For the last seven years, Maggie has 'worked' for MIT's Department of Brain and Cognitive Sciences (BCS). Three hours a day, the macaque plays computer games that (usually) are designed to require her to generate abstract representations and then use those abstractions as tools. 'Even I have trouble with this one,' Buschman says, nodding at a game that involves classifying logical operations. But Maggie is on a roll, slamming through problems, taking about half a second for each and getting about four out of five right. Maggie's gaming lies at the intersection of artificial intelligence (AI) and neuroscience. Under the tutelage of Buschman and Michelle Machon, another graduate student, she is contributing to research on how the brain learns and constructs logical rules, and how its performance of those tasks compares with that of the artificial neural networks used in AI. Forty years ago, the idea that neuroscience and AI might converge in labs like Miller's would have been all but unthinkable."

It's All In Your Head . A special report by Robert M. Metcalfe. Forbes.com (May 7, 2007). "Astonishing as they are, electronic networks can't hold a synaptic spark to the human brain. We know this intuitively--that the intelligence from the brain's network of neurons makes even the most advanced supercomputers look pitifully stupid. And yet, this paradox: Why is it that a comparison of the components goes the other way? When you stack neurons up against modern transistors in switching speed, the brain looks pathetic."

Encyclopedia of Computational Neuroscience. From Scholarpedia, "the free peer reviewed encyclopedia written by scholars from all around the world."