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"I Feel Your Pain" - " The Neural Basis of Empathy

Last month, a terrible earthquake raised havoc in Port-au-Prince, Haiti. While the Haitians in Port-au-Prince are miles away from us, witnessing media images of their physical and emotional suffering moves us tremendously, and motivates many of us to respond to their distress with monetary and other donations.

Google Buzz's official demo [video]

Google has just unveiled its latest attempt to become more relevant in the social media space—Google Buzz. The product is integrated within Gmail and will be rolled out gradually to all of the webmail service’s users over the next few days.

While this development is still unfolding, you can check out Google Buzz’s two-minute demo of Buzz in action both online and via mobile.

What are your initial reactions? Another soon-to-be-forgotten Google product like Wave, or a Facebook/Twitter killer?

Full story at Mashable.

Total Google coverage.

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Darth Vader’s original wimpy voice [video]

Imagine a galaxy far, far away where Darth Vader sounded like any other British bloke strolling down the corridors of the Death Star. Before James Earl Jones provided the menacing voice of the Dark Lord of the Sith, English actor and bodybuilder David Prowse delivered the lines from inside the Darth costume. While George Lucas never intended for Prowse’s voice to make the flick’s final cut, it’s weird to imagine how different Star Wars would have been with a different Vader voice.

Full story at Huffington Post.

Tons of Star Wars tidbits.

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Marijuana ineffective as an Alzheimer's treatment

The benefits of marijuana in tempering or reversing the effects of Alzheimer's disease have been challenged in a new study.

7 things you didn’t know about condoms

Rubbers. Raincoats. Inconvenient. Whatever you call 'em, condoms remain a must-have in the safe sex tool box. Long before the days of Durex and Trojans, men used animal intestines to protect their willies (that sounds lovely, eh ladies?) and still to this day use lambskin condoms for latex allergies and supposed extra sensitivity.

Want to learn even more fun facts about condoms that will surely impress your friends and potential lovers? Check out Asylum's seven things you probably didn't know about condoms that includes tantalizing tidbits like:

Vaseline + condoms = Disintegrated rubber and pregnancy scare.
Stealing condoms in Thailand could earn you a beat down.
Condoms and network TV don't mix.

Full story at Asylum.

Let's talk about sex, baby.

Photo credit: Fotolia

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'Zen' Bats Hit Their Target by Not Aiming at It

New research conducted at the University of Maryland's bat lab shows Egyptian fruit bats find a target by NOT aiming their guiding sonar directly at it.

New era of pain drugs advanced by Barrow researcher

Research led by a scientist at Barrow Neurological Institute at St. Joseph's Hospital and Medical Center has opened the door for the advancement of a new category of painkillers, called TRPV1 antagonists.

Horror flick mirror scare mash-up [video]

Horror movies love to rely on cliches to scare the bejeezus out of us, but does it really surprise anyone that the axe murderer is going to pop in the reflection of a mirror? Ok, yes, it still totally sparks a few pee-in-pants moments. Check out this mash-up of mirror scare moments (fair warning: don’t watch alone in a big, dark, scary house):

Full story at Four Four.

Boo! Tons of scary and not so scary movie news.

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7 things you shouldn't do on Valentine's Day

Ah, Valentine’s day. February fourteenth marks that special moment in the year when Hallmark cashes in on our emotions and cupid gets busy shooting arrows. Whether you’re indifferent, excited, upset, or madly in love—there are seven things you just shouldn’t do on this lovey-dovey holiday.

See a few do-not-do’s below:

Go on a first date. First dates are hard enough, why add the extra pressure?
Call your ex. Abort mission! On a day like this, it’s normal for your thoughts to drift to the one you used to be with, but you broke up for a reason. So, spare yourself the emotional next-day hangover and skip the reunion.
Overlook the good things in your life. It’s hard not to get caught up in the tornado of sweet hearts and teddy bears and chocolates—but there are far more important things in life. Make a list to remind yourself of the good things in your life and be thankful for them.

Full story at Divine Caroline.

The mobile communication device in your head.

Here's a real-life horror story: Five people have been found buried alive inside their bodies .

Social Studies

Michael Kesterton Published on Tuesday, Feb. 09, 2010 11:14AM EST Last updated on Tuesday, Feb.

Mediterranean diet may lower risk of brain damage that causes thinking problems

A Mediterranean diet may help people avoid the small areas of brain damage that can lead to problems with thinking and memory, according to a new study.

Drug shows promise for Huntington's disease

An early stage clinical trial of the experimental drug dimebon (latrepirdine) in people with Huntington's disease appears to be safe and may improve cognition.

Incidence Of Cerebral Palsy On Rise In United States

Cerebral palsy (CP) has increased in infants born prematurely in the United States, according to data presented by researchers from Loyola University Health System (LUHS). These findings were reported at the 30th Annual Meeting of the Society for Maternal-Fetal Medicine in Chicago. They also were published in the latest issue of the American Journal of Obstetrics & Gynecology...

Histostem Participates In Successful Stem Cell Treatment For Acute Spinal Cord Injury In Dogs

Stem Cell Therapy International, Inc. (OTCBB: SCII) announced that Histostem Ltd. of South Korea ("Histostem") has participated in a study resulting in the successful treatment of spinal cord injury in dogs through the use of Multipotent Stem Cells (MSCs) derived from Human Umbilical Cord Blood (HUCB)...

Medication Appears Well Tolerated And May Have Beneficial Effects In Patients With Huntington's Disease

A medication previously studied in patients with Alzheimer's disease (latrepirdine) appears well tolerated and may improve thinking, learning and memory skills among individuals with Huntington's disease, according to a report in the February issue of Archives of Neurology, one of the JAMA/Archives journals...

Hypertension May Predict Dementia In Older Adults With Certain Cognitive Deficits

High blood pressure appears to predict the progression to dementia in older adults with impaired executive functions (ability to organize thoughts and make decisions) but not in those with memory dysfunction, according to a report in the February issue of Archives of Neurology, one of the JAMA/Archives journals...

Mediterranean Diet May Lower Risk Of Brain Damage That Causes Thinking Problems

A Mediterranean diet may help people avoid the small areas of brain damage that can lead to problems with thinking and memory, according to a study released that will be presented at the American Academy of Neurology's 62nd Annual Meeting in Toronto April 10 to April 17, 2010...

A Conversation With Samuel Wang - New York Times

At his Princeton laboratory, Samuel Wang is searching for basic information on how the brains of humans and dogs work. Dr. Wang, 42, an associate professor at the university, also spends time popularizing breakthroughs in his specialty ...

Older investors prone to mental misfires while playing the market, study shows

Old age traditionally brings with it respect, experience and wisdom. But when it comes to making risky financial investments, an older mind is likely to make more mistakes than a younger one, psychologists say.

Emory receives $2.4 million to improve humanities - Atlanta Journal Constitution

The grant from the Andrew W. Mellon Foundation will allow the college to refocus the humanities around interdisciplinary areas and and to recruit new faculty, officials said. The university plans to create a "Society of Fellows" -- a cohort or ...

Brain Location for Fear of Losing Money Pinpointed -- The Amygdala - Science Daily

Researchers at the California Institute of Technology studied a phenomenon known as 'loss aversion' in two patients with lesions to the amygdala, a region deep within the brain involved in emotions and decision-making. The results of the study, part ...

Double agent: Glial cells can protect or kill neurons, vision

Scientists have identified a double agent in the eye that, once triggered, can morph from neuron protector to neuron killer. The discovery has significant health implications since the neurons killed through this process results in vision loss and blindness.

New robot joins Three Rivers ER - TMCnet

LOUISA, Feb 08, 2010 (The Daily Independent - McClatchy-Tribune Information Services via COMTEX) -- Three Rivers Medical Center, in partnership with St. Mary's Regional Neuroscience and Stroke Center, has acquired a RP-7 Remote Presence Robotic ...

Uncorrelated Activity in the Brain - Science Daily

Their findings provide detail as to how the brain accesses and processes information. "Understanding healthy neuronal activity is one of the first steps to unlocking the brains of those with illnesses such as autism," said Dr. Andreas S. Tolias ...

Mapping the brain

C. elegans, a tiny worm about a millimeter long, doesn’t have much of a brain, but it has a nervous system — one that comprises 302 nerve cells, or neurons, to be exact. In the 1970s, a team of researchers at Cambridge University decided to create a complete “wiring diagram” of how each of those neurons are connected to one another. Such wiring diagrams have recently been christened “connectomes,” drawing on their similarity to the genome, the total DNA sequence of an organism. The C. elegans connectome, reported in 1986, took more than a dozen years of tedious labor to find.

Now a handful of researchers scattered across the globe are tackling a much more ambitious project: to find connectomes of brains more like our own. The scientists, including several at MIT, are working on technologies needed to accelerate the slow and laborious process that the C. elegans researchers originally applied to worms. With these technologies, they intend to map the connectomes of our animal cousins, and eventually perhaps even those of humans. Their results could fundamentally alter our understanding of the brain.

Mapping the millions of miles of neuronal “wires” in the brain could help researchers understand how those neurons give rise to intelligence, personality and memory, says Sebastian Seung, professor of computational neuroscience at MIT. For the past three years, Seung and his students have been building tools that they hope will allow researchers to unravel some of those connections. To find connectomes, researchers will need to employ vast computing power to process images of the brain. But first, they need to teach the computers what to look for.

A tangled web

Piecing together connectomes requires analyzing vast numbers of electron microscopic images of brain slices and tracing the tangled connections between neurons, each of which can send projections to other cells several inches away.

At the Max Planck Institute for Medical Research in Heidelberg, Germany, neuroscientists in the laboratory of Winfried Denk have assembled a team of several dozen people to manually trace connections between neurons in the retina. It’s a painstaking process — each neuron takes hours to trace, and each must be traced by as many as 10 people, in order to catch careless errors. Using this manual approach, finding the connectome of just one cubic millimeter of brain would take tens of thousands of work-years, says Viren Jain, who recently completed his PhD in Seung’s lab.

Jain and postdoctoral associate Srinivas Turaga want to speed up the process dramatically by enlisting the help of high-powered computers. To do that, they are teaching the computers to analyze the brain slices, using a common computer science technique called automated machine learning, which allows computers to change their behavior in response to new data.

With machine learning, the researchers teach computers to learn by example. They feed their computer electron micrographs as well as human tracings of these images. The computer then searches for an algorithm that allows it to imitate human performance.

“Instead of specifying the details of how the computer does something, you give it an example of what you want it to do and an algorithm that tries to figure out how to do what you want,” says Jain. After the computer is trained on the human tracings, it is applied to electron micrographs that have not been traced by humans. This new technique represents the first time that computers have been effectively taught to segment any kind of images, not just neurons.

Jain and Turaga have also invented new ways of evaluating how well the computer imitates humans at the task of tracing. Those measures are crucial for machine learning because the computer, just like students in a class, will not learn the desired task well unless the “exam” properly measures performance.

In their early efforts, it took the computer weeks or even months to come up with an accurate neuron-tracing algorithm. However, Jain and Turaga cut that time dramatically when they started using computers equipped with graphics processing cards, allowing them to perform computations 50 to 100 times faster. Now, it takes only days for their computer programs to produce a new tracing algorithm.

Their eventual goal is to use computers to process the bulk of the images needed to create connectomes, but they expect that humans will still need to proofread the computers’ work. Jain and Turaga have reported their advances at the International Conference on Computer Vision and the Neural Information Processing Systems Conference.

Olaf Sporns, a neuroscientist at the University of Indiana who first proposed diagramming the connectome in 2005, says that he originally did not think it would be possible to create a map of individual connections between single neurons, and thought it would be best to focus on higher-level connections between brain regions.

“Doing such a microscopic level of resolution seemed to be infeasible at the time,” he says. “But now I’m coming around to the idea that something like that may well be possible.” The machine learning technology that Seung and his students are developing could be “a big leap forward” in making that kind of diagram a reality, Sporns adds.

First steps

Last year, the National Institutes of Health announced a five-year, $30 million Human Connectome Project to develop new techniques to figure out the connectivity of the human brain. That project is focused mainly on higher level, region-to-region connections. Sporns says he believes that a good draft of higher-level connections could be achieved within the five-year timeline of the NIH project, and that significant progress will also be made toward a neuron-to-neuron map.

Some neuroscientists believe that mapping connectomes could have just as much impact as sequencing the human genome. Much as genetic researchers can now compare individuals’ genes to look for variability that might account for diseases, brain researchers could discover which differences in the wiring diagrams are important in diseases like Alzheimer’s and schizophrenia, says Turaga.

Comparing connectomes as human development unfolds could also be informative, since much human behavior is learned, not encoded in the genome. “Compared to an adult, a baby doesn’t know how to do very much. The brain is slowly refined and becomes more powerful, and the thing that’s refined is the wiring diagram,” says Jain.

Many of the research teams that have begun working on neuron-to-neuron connectome diagrams are starting with small pieces of the whole. These teams include a group at Harvard that’s focusing on the human hippocampus, a brain region involved in memory and learning. Other groups are starting with brain diagrams for smaller animals such as mice and zebrafish.

Though only a handful of labs around the world are working on the connectome right now, Jain and Turaga expect that to change as tools for diagramming the brain improve. “It’s a common pattern in neuroscience: A few people will come up with new technology and pioneer some applications, and then everybody else will start to adopt it,” says Jain.

Silencing the brain with light

Giving epilepsy patients an electric jolt to shut off out-of-control neuron firing during seizures is being explored as a way to treat the chronic brain disorder. New research from MIT now raises the possibility of silencing those seizures with light instead of electricity.

A team led by neuroengineer Edward Boyden has found a class of proteins that, when inserted into neurons, allow them to be turned off with rays of yellow-green light. The silencing is near instantaneous and easily reversible.

This kind of selective brain silencing, reported in the Jan. 7 issue of Nature, could not only help treat brain disorders but also allows researchers to investigate the role of different types of neurons in normal brain circuits and how those circuits can go wrong.

“We hope to enable a broad platform of molecular tools for controlling brain activity, thus enabling new general therapeutic tools, and new ways of studying brain function,” says Boyden, the Benesse Career Development Professor in the MIT Media Lab and an associate member of the McGovern Institute for Brain Research at MIT.

‘Clean and digital’

Boyden first demonstrated the use of light to reduce brain activity in 2007. However, the feat was performed in cells, not living animals, and the silencing was not as precise. In the new study, the researchers used a different protein — one that inhibits neurons more strongly, silences more brain tissue and can be repeatedly activated because it returns to its original state within milliseconds of light activation.

With the new protein, called Arch, brain silencing is “extremely clean and digital,” says Boyden. “The other one was more like a volume knob turning up and down.”

Boyden and his colleagues combined genetic and optical techniques to control neuron activity, a strategy that has come to be called “optogenetic.” First, they engineered brain cells of living mice to express the gene for the Arch protein, which functions as a proton pump, moving protons across the cell membrane to alter the cell’s voltage. The proton pumps are light-sensitive, so they pump protons out of cells when activated by yellow-green light. That lowers voltage inside the cells, silencing their firing.

In their previous work, the researchers used a light-sensitive chloride pump called halorhodopsin, which changes neurons’ voltage by pumping chloride ions into the cell. However, they weren’t satisfied with it and started looking for a better chloride pump, examining proteins from a range of bacteria, plants and fungi. They couldn’t find a chloride pump that offered the kind of control they were seeking, but discovered the new Arch proton pump in a strain of archaebacteria called Halorubrum sodomense that lives in the Dead Sea.

“This is the result of mining the wealth of the natural world — genomic diversity and ecological variation — to discover new tools that can empower scientists to study complex systems like the brain,” says Boyden. “We're using natural tools isolated from the wild to help us understand how neural circuits work.” This strategy has long been used in molecular and cellular biology, resulting in tools like restriction enzymes, PCR and GFP, but Boyden's work only recently has been applied to tackle complex systems-level biological problems.

One major advantage of the new pumps is that they can be used over and over again: They recover their ability to be light-activated within seconds, rather than the minutes required for the old tool, halorhodopsin, to reprime itself. That is critical to neuroscientists who want to study the role of particular cell types in different tasks, says Edward Callaway, professor of systems neurobiology at the Salk Institute, who was not involved in the research.

“If you have to wait a long time to get recovery, you just can’t compare different conditions quickly,” says Callaway, who studies vision-processing circuits in the brain. The new channels offer a “much more practical” way to use optogenetics for animal studies such as testing which neurons are involved in different visual tasks, he says.

To achieve brain silencing in mice, the researchers implanted an externally controllable light source inside the mice’s brains. While the current device requires mice to be wired up to an external control, the researchers are designing a fully wireless system.

Boyden's group, working with the Desimone lab at the McGovern Institute at MIT, is now performing pre-clinical testing of this approach in non-human primates, to assess its safety as a potential therapy for epilepsy, chronic pain and post-traumatic stress disorder. The team has also developed, in collaboration with other groups at MIT, hardware for optical neural stimulation, which could be valuable for neural prosthetic purposes.

The MIT researchers have also discovered other proton pumps activated by different colors of light, combining these pumps with previously discovered tools allows researchers to selectively silence different brain regions using red and blue light. “One beautiful thing about this is we can inactivate different projections in the same brain,” says Boyden.

In future studies, the researchers plan to use their neuron-silencing tools to examine the neural circuits of cognition and emotion, and to determine whether the new pumps are safe and effective in monkeys — a critical step toward potentially using optical control to treat human diseases.
Listen to Ed Boyden talk about this research with the National Science Foundation
Clip 1

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HHMI lists Tsai team’s advance among 10 biggest stories of 2009

The discovery by researchers at MIT’s Picower Institute for Learning and Memory of a single DNA-packaging protein that is specifically associated with learning and memory has been named one of the 10 biggest stories of 2009 by the Howard Hughes Medical Institute.

The HHMI annual report honors the work of Li-Huei Tsai, the Picower Professor of Neuroscience and an HHMI investigator, whose team identified that the gene HDAC2 and its associated protein could be the target of safer, more specific drugs that promote learning when DNA in the brain unwinds from its tightly coiled configuration.

Although certain drugs can prime the brain for learning by blocking a class of proteins known to keep DNA tightly packed in mice, they also cause unwanted side effects. By narrowing the focus to a single protein, Tsai’s work “could aid the development of drugs that treat memory loss associated with Alzheimer’s disease and other neurodegenerative diseases with fewer side effects,” the report says.

To read more about the advance, please see the MIT News story from earlier this year.

Rethinking artificial intelligence

The field of artificial-intelligence research (AI), founded more than 50 years ago, seems to many researchers to have spent much of that time wandering in the wilderness, swapping hugely ambitious goals for a relatively modest set of actual accomplishments. Now, some of the pioneers of the field, joined by later generations of thinkers, are gearing up for a massive “do-over” of the whole idea.

This time, they are determined to get it right — and, with the advantages of hindsight, experience, the rapid growth of new technologies and insights from the new field of computational neuroscience, they think they have a good shot at it.

The new project, launched with an initial $5 million grant and a five-year timetable, is called the Mind Machine Project, or MMP, a loosely bound collaboration of about two dozen professors, researchers, students and postdocs. According to Neil Gershenfeld, one of the leaders of MMP and director of MIT’s Center for Bits and Atoms, one of the project’s goals is to create intelligent machines — “whatever that means.”

The project is “revisiting fundamental assumptions” in all of the areas encompassed by the field of AI, including the nature of the mind and of memory, and how intelligence can be manifested in physical form, says Gershenfeld, professor of media arts and sciences. “Essentially, we want to rewind to 30 years ago and revisit some ideas that had gotten frozen,” he says, adding that the new group hopes to correct “fundamental mistakes” made in AI research over the years.

The birth of AI as a concept and a field of study is generally dated to a conference in the summer of 1956, where the idea took off with projections of swift success. One of that meeting’s participants, Herbert Simon, predicted in the 1960s, “Machines will be capable, within 20 years, of doing any work a man can do.” Yet two decades beyond that horizon, that goal now seems to many to be as elusive as ever.

It is widely accepted that AI has failed to realize many of those lofty early promises. “Considering the outrageous optimism of much of the early hype for AI, it is no wonder that it couldn't deliver. This is an occupational hazard of many new fields,” says Daniel Dennett, a professor of philosophy at Tufts University and co-director of the Center for Cognitive Science there. Still, he says, it hasn’t all been for nothing: “The reality is not dazzling, but still impressive, and many applications of AI that were deemed next-to-impossible in the ’80s are routine today,” including the automated systems that answer many phone inquiries using voice recognition.

Fixing what’s broken

Gershenfeld says he and his fellow MMP members “want to go back and fix what’s broken in the foundations of information technology.” He says that there are three specific areas — having to do with the mind, memory, and the body — where AI research has become stuck, and each of these will be addressed in specific ways by the new project

The first of these areas, he says, is the nature of the mind: “how do you model thought?” In AI research to date, he says, “what’s been missing is an ecology of models, a system that can solve problems in many ways,” as the mind does.

Part of this difficulty comes from the very nature of the human mind, evolved over billions of years as a complex mix of different functions and systems. “The pieces are very disparate; they’re not necessarily built in a compatible way,” Gershenfeld says. “There’s a similar pattern in AI research. There are lots of pieces that work well to solve some particular problem, and people have tried to fit everything into one of these.” Instead, he says, what’s needed are ways to “make systems made up of lots of pieces” that work together like the different elements of the mind. “Instead of searching for silver bullets, we’re looking at a range of models, trying to integrate them and aggregate them,” he says.

The second area of focus is memory. Much work in AI has tried to impose an artificial consistency of systems and rules on the messy, complex nature of human thought and memory. “It’s now possible to accumulate the whole life experience of a person, and then reason using these data sets which are full of ambiguities and inconsistencies. That’s how we function — we don’t reason with precise truths,” he says. Computers need to learn “ways to reason that work with, rather than avoid, ambiguity and inconsistency.”

And the third focus of the new research has to do with what they describe as “body”: “Computer science and physical science diverged decades ago,” Gershenfeld says. Computers are programmed by writing a sequence of lines of code, but “the mind doesn’t work that way. In the mind, everything happens everywhere all the time.” A new approach to programming, called RALA (for reconfigurable asynchronous logic automata) attempts to “re-implement all of computer science on a base that looks like physics,” he says, representing computations “in a way that has physical units of time and space, so the description of the system aligns with the system it represents.” This could lead to making computers that “run with the fine-grained parallelism the brain uses,” he says.

MMP group members span five generations of artificial-intelligence research, Gershenfeld says. Representing the first generation is Marvin Minsky, professor of media arts and sciences and computer science and engineering emeritus, who has been a leader in the field since its inception. Ford Professor of Engineering Patrick Winston of the Computer Science and Artificial Intelligence Laboratory is one of the second-generation researchers, and Gershenfeld himself represents the third generation. Ed Boyden, a Media Lab assistant professor and leader of the Synthetic Neurobiology Group, was a student of Gershenfeld and thus represents the fourth generation. And the fifth generation includes David Dalrymple, one of the youngest students ever at MIT, where he started graduate school at the age of 14, and Peter Schmidt-Nielsen, a home-schooled prodigy who, though he never took a computer science class, at 15 is taking a leading role in developing design tools for the new software.

The MMP project is led by Newton Howard, who came to MIT to head this project from a background in government and industry computer research and cognitive science. The project is being funded by the Make a Mind Company, whose chairman is Richard Wirt, an Intel Senior Fellow.

“To our knowledge, this is the first collaboration of its kind,” Boyden says. Referring to the new group’s initial planning meetings over the summer, he says “what’s unique about everybody in that room is that they really think big; they’re not afraid to tackle the big problems, the big questions.”

The big picture

Harvard (and former MIT) cognitive psychologist Steven Pinker says that it’s that kind of big picture thinking that has been sorely lacking in AI research in recent years. Since the 1980s, he says “there was far more focus on getting software products to market, regardless of whether they instantiated interesting principles of intelligent systems that could also illuminate the human mind. This was a real shame, in my mind, because cognitive psychologists (my people) are largely atheoretical lab nerds, linguists are narrowly focused on their own theoretical paradigms, and philosophers of mind are largely uninterested in mechanism.

“The fading of theoretical AI has led to a paucity of theory in the sciences of mind,” Pinker says. “I hope that this new movement brings it back.”

Boyden agrees that the time is ripe for revisiting these big questions, because there have been so many advances in the various fields that contribute to artificial intelligence. “Certainly the ability to image the neurological system and to perturb the neurological system has made great advances in the last few years. And computers have advanced so much — there are supercomputers for a few thousand dollars now that can do a trillion operations per second.”

Minsky, one of the pioneering researchers from AI’s early days, sees real hope for important contributions this time around. Decades ago, the computer visionary Alan Turing famously proposed a simple test — now known as the Turing Test — to determine whether a machine could be said to be truly intelligent: If a person communicating via computer terminal could carry on a conversation with a machine but couldn’t tell whether or not it was a person, then the machine could be deemed intelligent. But annual “Turing test” competitions have still not produced a machine that can convincingly pass for human.

Now, Minsky proposes a different test that would determine when machines have reached a level of sophistication that could begin to be truly useful: whether the machine can read a simple children’s book, understand what the story is about, and explain it in its own words or ask reasonable questions about it.

It’s not clear whether that’s an achievable goal on this kind of timescale, but Gershenfeld says, “We need good challenging projects that force us to bring our program together.”

One of the projects being developed by the group is a form of assistive technology they call a brain co-processor. This system, also referred to as a cognitive assistive system, would initially be aimed at people suffering from cognitive disorders such as Alzheimer’s disease. The concept is that it would monitor people’s activities and brain functions, determine when they needed help, and provide exactly the right bit of helpful information — for example, the name of a person who just entered the room, and information about when the patient last saw that person — at just the right time.

The same kind of system, members of the group suggest, could also find applications for people without any disability, as a form of brain augmentation — a way to enhance their own abilities, for example by making everything from personal databases of information to all the resources of the internet instantly available just when it’s needed. The idea is to make the device as non-invasive and unobtrusive as possible — perhaps something people would simply slip on like a pair of headphones.

Boyden suggests that the project’s initial five-year timeframe seems about right. “It’s long enough that people can take risks and try really adventurous ideas,” he says, “but not so long that we won’t get anywhere.” It’s a short enough span to produce “a useful kind of pressure,” he says. Among the concepts the group may explore are concepts for “intelligent,” adaptive books and games — or, as Gershenfeld suggests, “books that think.”

In the longer run, Minsky still sees hope for far grander goals. For example, he points to the fact that his iPhone can now download thousands of different applications, instantly allowing it to perform new functions. Why not do the same with the brain? “I would like to be able to download the ability to juggle,” he says. “There’s nothing more boring than learning to juggle.”

3 Questions: Suzanne Corkin on the world’s most famous amnesic

H.M., the well-known amnesic patient whose condition helped scientists understand memory and memory impairment, died a year ago at the age of 82. H.M. (whose full name, Henry Gustav Molaison, was disclosed only after his death) suffered from an unusual condition as a result of brain surgery to treat his epilepsy: He was unable to form new long-term memories. Before his death, H.M. and his guardian agreed that his brain would be donated to scientists for future study. MIT Professor of Brain and Cognitive Sciences Suzanne Corkin studied H.M. during his life and is now part of a team that will be analyzing H.M.’s brain starting this week. In this interview, she explains H.M.’s impact on understanding how memory works.

Q. In life, what were the most important contributions H.M. made to understanding human memory and brain function?
A. H.M. illuminated the science of memory. His brain damage was deep in both temporal lobes. Prior to his surgery, the clinical literature contained hints that this area played a role in long-term memory. His case, however, showed definitively that the hippocampus and neighboring cortex are critical for the establishment of long-term declarative memory. He also taught us that memory is compartmentalized in the brain, and thus profound amnesia could exist in an individual with an above-average I.Q. H.M.’s motor skill learning and perceptual learning were preserved, indicating that these kinds of learning rely on networks outside the medial temporal lobe. Further, immediate memory, like remembering a telephone number, was intact in H.M., suggesting that different cognitive and brain processes support immediate memory and long-term memory. His core deficit was an inability to transfer information from short-term memory into long-term memory. The only way he could hang on to new information was to rehearse it over and over again.

Q. Why is it important to examine H.M.’s brain after his death?
A. H.M.’s high-resolution MRI scans preformed before and after his death gave us an approximate idea of the location of his lesion, but these images provided only an indirect view. An autopsy study is the only way to define the true borders of his surgical removal. His brain has been frozen, and on Dec. 2, exactly one year after his death, it will be cut into roughly 2,600 very thin slices from front to back. Each will be photographed by a specially designed camera, and will be available for anyone in the world to view on a dedicated web site. Some slices will be examined microscopically to count nerve cells, and other slices will be stained to determine, for example, whether he developed Alzheimer’s disease in old age. Other scientists outside our group will be able to request tissue to address their own hypotheses about H.M.’s brain. A small number of slices will be displayed as part of a touring exhibition, “Remembering H.M.,” which is being planned and created by the MIT Museum.

Q. What was H.M. like as a person and a patient? How well did he understand his condition?
A. Despite his devastating amnesia, H.M. was quiet, polite and congenial, greeting all strangers as friends. He loved to talk about his family and childhood vacations. He had a great sense of humor and would often say, “Knock on wood” while tapping the side of his head with his fist. He was altruistic. When asked how he felt about doing all of our tests and answering questions, he replied, “What they find out about me helps them to help other people.” He knew that he had epilepsy, that he had a brain operation, and that he had trouble remembering things. Sometimes when we asked him a question, and he didn’t know the answer, he would say, “I’m having an argument with myself.” This phrase caught on in my lab, and now, in many parts of the world, former Corkin Lab members have arguments with themselves and remember H.M.

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