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Learning drugs reawaken grown-up brain's inner child

http://www.newscientist.com/article/dn24831-learning-drugs-reawaken-grownup-brains-inner-child.html?utm_source=NSNS&utm_medium=SOC&utm_campaign=facebookgoogletwitter&cmpid=SOC%7CNSNS%7C2012-GLOBAL-facebookgoogletwitter#.Us13V3l3v4g

 

• 13:17 08 January 2014 by Helen Thomson
• For similar stories, visit the The Human Brain Topic Guide

A drug for perfect pitch is just the start: mastering new skills could become easy if we can restore the brain's youthful ability to create new circuits

WANNABE maestros, listen up. A mood-stabilising drug can help you achieve perfect pitch – the ability to identify any note you hear without inferring it from a reference note.

Since this is a skill that is usually acquired only early in life, the discovery is the first evidence that it may be possible to revert the human brain to a childlike state, enabling us to treat disorders and unlock skills that are difficult, if not impossible, to acquire beyond a certain age.

From bilingualism to sporting prowess, many abilities rely on neural circuits that are laid down by our early experiences. Until the age of 7 or so, the brain goes through several "critical periods" during which it can be radically changed by the environment. During these times, the brain is said to have increased plasticity.

In order to take advantage of these critical periods, the brain needs to be stimulated appropriately so it lays down the neuronal circuitry needed for a particular ability. For example, young children with poor sight in one eye may develop lazy eye, or amblyopia. It can be treated by covering the better eye, forcing the child to use the lazy eye – but this strategy only works during the critical period.

These windows of opportunity are fleeting, but now researchers are beginning to understand what closes them and how they might be reopened.

"We used to have this dogmatic view that the young brain is full of plasticity factors that disappear with age, and that's why critical periods close," says Takao Hensch, professor of neurology at Harvard University. "Then we realised that regardless of when the critical period is triggered, its length is finite. That suggested gene programs are unleashed that wind down plasticity."

Hensch's team has shown that several physiological changes close the door on plasticity in animals. A key player is histone deacetylase (HDAC), an enzyme that acts on DNA and makes it harder to switch genes on or off.

Hensch and his colleagues reasoned that reversing this molecular brake might allow the brain's plasticity machinery to kick in again. "And that's exactly what we found," he says. In 2010, they used valproate – a drug that inhibits HDAC and is used to treat bipolar disorder – to cure amblyopia in adult mice.

To test whether valproate might reawaken the critical period in humans, Hensch, together with Allan Young at King's College London and colleagues, had to settle on a skill that appears impossible for adults to acquire. They chose perfect pitch because it is a rare ability and is usually seen only in some people who were taught music before the age of 6. There are no conclusive examples of adults acquiring it, although people who do months of training can gain some ability to identify notes.

 

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The team gave 24 men with little or no musical training a dose of valproate or a placebo every day for 15 days. During the second week, participants watched a 10-minute training video daily, which taught them to associate six different tones over three octaves with six names, such as Sarah, David and Jimmy. The researchers used people's names rather than the names of notes to ensure any existing familiarity with musical notation would not influence the results.

On the final day, the group heard 18 different tones and had to give the name associated with them. Men who took valproate identified 5.09 notes on average, a significantly better performance than those given the placebo, who got an average of 3.5 notes correct – no better than chance (Frontiers in Systems Neuroscience, doi.org/qq8).

The study is a promising first step towards demonstrating that critical-period learning can happen in adults, says Diana Deutsch, a psychologist at the University of California, San Diego. "The number of subjects explored here was small," she says. "However the results were significant, and they should be taken very seriously."

The team will now try to replicate the results in a bigger study, which will include an additional group taking a mood stabiliser that does not affect HDAC.

Studies looking at other drugs are already under way. One hinges on a second brake mechanism that could affect plasticity, involving genes that dampen the transmission of the nutrient choline around a cell. Donepezil, an Alzheimer's drug, increases this transmission, so a team at Boston Children's Hospital, which includes Hensch, is investigating whether it can help reverse amblyopia in older children and adults. The results are promising, says Hensch. "The first wave of subjects have improved. We don't know how long it will last; we're looking at that now." Another study is focusing on the antidepressant fluoxetine, better known as Prozac.

Researchers are treading with caution, however. The brain shuts down critical periods for good reason – it would be disastrous to have it rewiring itself extensively for the rest of your life. Hensch says he would have been timid about testing valproate's effects in humans except for the fact that it is an approved treatment for mood disorders and epilepsy. "We're not opening the brain up to a massive rewrite. We're enhancing its potential for plasticity – which, when paired with training, can manifest in changes we want."

It's difficult to predict the ramifications of this work, says Young, but they could be major. Several disorders, including autism, may be a result of mistimed critical periods (see "Timing is everything for blooming talents") so switching them back on could be useful therapeutically. Then there is the potential to endow us with new skills. "If you can reopen that critical period, you could potentially reawaken learning in all," says Young.

Timing is everything for blooming talents

Our developing brain is incredibly malleable, capable of structuring and restructuring connections between neurons in response to different experiences. Times of greatest change – or "sensitivity" – are called critical periods. These begin and end at certain ages (see graph) to allow the brain to build and cement circuitry for processes such as hearing, vision, emotion and language.

Sculpting these circuits involves a delicate balance of excitation and inhibition. Neurons that are excited, or active, at the same time will form robust connections, helping new circuits to form, while neurons that are inhibited or fire out of sync may become pruned.

Researchers have now shown that certain drugs might open up critical periods in adults (see main story). As well as potentially giving us a way to learn new skills, it may offer a path to tackle neurological disorders. For example, many genes implicated in autism are involved in establishing or maintaining the balance between excitation and inhibition. Some researchers believe the cognitive deficits seen in autism might be the result of mistimed critical periods. Studies of mice bred to express different autism-related genes have found evidence for such mistimings.

If critical periods don't occur at the correct time, the brain may lay down some circuits too early, which means they may link up with underdeveloped brain areas. Or it can happen too late, in which case the functions these circuits handle, for example the ability to identify facial features, will not integrate with more sophisticated neural processes such as those that help us interpret others' emotions.

Babbling babies -- responding to one-on-one 'baby talk' -- master more words

 

		AUDIO:   A parent demonstrates babytalk ( "parentese ") with child. Click here for more information.

Common advice to new parents is that the more words babies hear the faster their vocabulary grows. Now new findings show that what spurs early language development isn't so much the quantity of words as the style of speech and social context in which speech occurs.

Researchers at the University of Washington and University of Connecticut examined thousands of 30-second snippets of verbal exchanges between parents and babies. They measured parents' use of a regular speaking voice versus an exaggerated, animated baby talk style, and whether speech occurred one-on-one between parent and child or in group settings.

"What our analysis shows is that the prevalence of baby talk in one-on-one conversations with children is linked to better language development, both concurrent and future," said Patricia Kuhl, co-author and co-director of UW's Institute for Learning & Brain Sciences.

The more parents exaggerated vowels – for example "How are youuuuu?" – and raised the pitch of their voices, the more the 1-year olds babbled, which is a forerunner of word production. Baby talk was most effective when a parent spoke with a child individually, without other adults or children around.

"The fact that the infant's babbling itself plays a role in future language development shows how important the interchange between parent and child is," Kuhl said.

The findings will be published in an upcoming issue of the journal Developmental Science.

Twenty-six babies about 1 year of age wore vests containing audio recorders that collected sounds from the children's auditory environment for eight hours a day for four days. The researchers used LENA ("language environment analysis") software to examine 4,075 30-second intervals of recorded speech. Within those segments, the researchers identified who was talking in each segment, how many people were there, whether baby talk – also known as "parentese" – or regular voice was used, and other variables.

When the babies were 2 years old, parents filled out a questionnaire measuring how many words their children knew. Infants who had heard more baby talk knew more words. In the study, 2-year olds in families who spoke the most baby talk in a one-on-one social context knew 433 words, on average, compared with the 169 words recognized by 2-year olds in families who used the least babytalk in one-on-one situations.

The relationship between baby talk and language development persisted across socioeconomic status and despite there only being 26 families in the study.

"Some parents produce baby talk naturally and they don't realize they're benefiting their children," said first author Nairán Ramírez-Esparza, an assistant psychology professor at the University of Connecticut. "Some families are more quiet, not talking all the time. But it helps to make an effort to talk more."

Previous studies have focused on the amount of language babies hear, without considering the social context. The new study shows that quality, not quantity, is what matters.

"What this study is adding is that how you talk to children matters. Parentese is much better at developing language than regular speech, and even better if it occurs in a one-on-one interaction," Ramirez-Esparza said.

Parents can use baby talk when going about everyday activities, saying things like, "Where are your shoooes?," "Let's change your diiiiaper," and "Oh, this tastes goooood!," emphasizing important words and speaking slowly using a happy tone of voice.

"It's not just talk, talk, talk at the child," said Kuhl. "It's more important to work toward interaction and engagement around language. You want to engage the infant and get the baby to babble back. The more you get that serve and volley going, the more language advances."

###

 

A National Science Foundation Science of Learning Program to the UW-hosted LIFE Center funded the study.

For more information, contact Kuhl at 206-685-1921 or [email protected] or Ramírez-Esparza 860-486-6365 or [email protected].

http://www.eurekalert.org/multimedia/pub/66854.php?from=257453

How you practice matters for learning a skill quickly

 

 

Practice alone doesn't make perfect, but learning can be optimized if you practice in the right way, according to new research based on online gaming data from more than 850,000 people.

The research, led by psychological scientist Tom Stafford of the University of Sheffield (UK), suggests that the way you practice is just as important as how often you practice when it comes to learning quickly.

The new findings are published in Psychological Science, a journal of the Association for Psychological Science.

Stafford and Michael Dewar from The New York Times Research and Development Lab analyzed data from 854,064 people playing an online game called Axon. Players are tasked with guiding a neuron from connection to connection by clicking on potential targets, testing participants' ability to perceive, make decisions, and move quickly.

Stafford and Dewar were interested to know how practice affected players' subsequent performance in the game.

Some Axon players achieved higher scores than others despite practicing for the same amount of time. Game play data revealed that those players who seemed to learn more quickly had either spaced out their practice or had more variable early performance — suggesting they were exploring how the game works — before going on to perform better.

"The study suggests that learning can be improved — you can learn more efficiently or use the same practice time to learn to a higher level," says Stafford. "As we live longer, and as more of our lives become based around acquiring complex skills, optimal learning becomes increasingly relevant to everyone."

Using data collected from people playing games offers a new way for researchers to study learning, and has strong advantages compared to research on learning that is based in the lab. Game data provide insight into a real skill that people presumably enjoy practicing, and detailed data regarding all actions that players take as they learn to play are easily recorded.

"This kind of data affords us to look in an unprecedented way at the shape of the learning curve, allowing us to explore how the way we practice helps or hinders learning," says Stafford.

Stafford hopes to collaborate with game designers to further investigate the factors that shape optimal learning.

###

 

For more information about this study, please contact: Tom Stafford at [email protected].

The article abstract is available online: http://pss.sagepub.com/content/early/2013/12/30/0956797613511466.abstract

Axon was developed for the Wellcome Trust by game designer Preloaded. The game can be played http://axon.wellcomeapps.com/. Researchers inserted a tracking code that recorded machine identity each time the game was loaded and kept track of the score and the date and time of play. No information on the players, other than their game scores, was collected.

Stafford and Dewar have made their data and analysis code publicly available for anyone who wishes to replicate or conduct their own analyses.

The APS journal Psychological Science is the highest ranked empirical journal in psychology. For a copy of the article "Tracing the Trajectory of Skill Learning With a Very Large Sample of Online Game Players" and access to other Psychological Science research findings, please contact Anna Mikulak at 202-293-9300 or [email protected].

Synaptic transistor learns while it computes- transistor that mimics the behavior of a synapse

 

First of its kind, brain-inspired device looks toward highly efficient and fast parallel computing

 

Cambridge, Mass. – November 1, 2013 – It doesn't take a Watson to realize that even the world's best supercomputers are staggeringly inefficient and energy-intensive machines.

Our brains have upwards of 86 billion neurons, connected by synapses that not only complete myriad logic circuits; they continuously adapt to stimuli, strengthening some connections while weakening others. We call that process learning, and it enables the kind of rapid, highly efficient computational processes that put Siri and Blue Gene to shame.

Materials scientists at the Harvard School of Engineering and Applied Sciences (SEAS) have now created a new type of transistor that mimics the behavior of a synapse. The novel device simultaneously modulates the flow of information in a circuit and physically adapts to changing signals.

Exploiting unusual properties in modern materials, the synaptic transistor could mark the
beginning of a new kind of artificial intelligence: one embedded not in smart algorithms but in the very architecture of a computer. The findings appear in Nature Communications.

“There’s extraordinary interest in building energy-efficient electronics these days,” says principal investigator Shriram Ramanathan, associate professor of materials science at Harvard SEAS. “Historically, people have been focused on speed, but with speed comes the penalty of power dissipation. With electronics becoming more and more powerful and ubiquitous, you could have a
huge impact by cutting down the amount of energy they consume.”

The human mind, for all its phenomenal computing power, runs on roughly 20 Watts of energy (less
than a household light bulb), so it offers a natural model for engineers.

“The transistor we’ve demonstrated is really an analog to the synapse in our brains,” says co-lead
author Jian Shi, a postdoctoral fellow at SEAS. “Each time a neuron initiates an action and another neuron reacts, the synapse between them increases the strength of its connection. And the faster the neurons spike each time, the stronger the synaptic connection. Essentially, it memorizes the action between the neurons.”

In principle, a system integrating millions of tiny synaptic transistors and neuron terminals could take parallel computing into a new era of ultra-efficient high performance.

Several prototypes of the synaptic transistor are visible on this silicon chip. (Photo by Eliza Grinnell, SEAS Communications.)

While calcium ions and receptors effect a change in a biological synapse, the artificial version
achieves the same plasticity with oxygen ions. When a voltage is applied, these ions slip in and out of the crystal lattice of a very thin (80-nanometer) film of samarium nickelate, which acts as the synapse channel between two platinum "axon" and "dendrite" terminals. The varying concentration
of ions in the nickelate raises or lowers its conductance—that is, its ability to carry information on an electrical current—and, just as in a natural synapse, the strength of the connection depends on the time delay in the electrical signal.

Structurally, the device consists of the nickelate semiconductor sandwiched between two platinum
electrodes and adjacent to a small pocket of ionic liquid. An external circuit multiplexer converts the time delay into a magnitude of voltage which it applies to the ionic liquid, creating an electric field that either drives ions into the nickelate or removes them. The entire device, just a few hundred
microns long, is embedded in a silicon chip.

The synaptic transistor offers several immediate advantages over traditional silicon transistors.
For a start, it is not restricted to the binary system of ones and zeros.

“This system changes its conductance in an analog way, continuously, as the composition of the
material changes,” explains Shi. “It would be rather challenging to use CMOS, the traditional circuit technology, to imitate a synapse, because real biological synapses have a practically unlimited number of possible states—not just ‘on’ or ‘off.’”

The synaptic transistor offers another advantage: non-volatile memory, which means even when
power is interrupted, the device remembers its state.

Additionally, the new transistor is inherently energy efficient. The nickelate belongs to an unusual
class of materials, called correlated electron systems, that can undergo an insulator-metal transition. At a certain temperature—or, in this case, when exposed to an external field—the conductance of the material suddenly changes.

“We exploit the extreme sensitivity of this material,” says Ramanathan. “A very small excitation allows you to get a large signal, so the input energy required to drive this switching is potentially very small. That could translate into a large boost for energy efficiency.”

The nickelate system is also well positioned for seamless integration into existing silicon-based systems.

“In this paper, we demonstrate high-temperature operation, but the beauty of this type of a device
is that the 'learning' behavior is more or less temperature insensitive, and that’s a big advantage,” says Ramanathan. “We can operate this anywhere from about room temperature up to at least 160 degrees Celsius.”

For now, the limitations relate to the challenges of synthesizing a relatively unexplored material system, and to the size of the device, which affects its speed.

“In our proof-of-concept device, the time constant is really set by our experimental geometry,” says Ramanathan. “In other words, to really make a super-fas device, all you’d have to do is confine the liquid and position the gate electrode closer to it.”

In fact, Ramanathan and his research team are already planning, with microfluidics experts at SEAS,
to investigate the possibilities and limits for this “ultimate fluidic transistor.”

He also has a seed grant from the National Academy of Sciences to explore the integration of
synaptic transistors into bioinspired circuits, with L. Mahadevan, Lola England de Valpine Professor of Applied Mathematics, professor of organismic and evolutionary biology, and professor of physics.

“In the SEAS setting it’s very exciting; we’re able to collaborate easily with people from very
diverse interests,” Ramanathan says.

For the materials scientist, as much curiosity derives from exploring the capabilities of correlated oxides (like the nickelate used in this study) as from the possible applications.

“You have to build new instrumentation to be able to synthesize these new materials, but once
you’re able to do that, you really have a completely new material system whose properties are virtually unexplored,” Ramanathan says. “It’s very exciting to have such materials to work with, where very little is known about them and you have an opportunity to build knowledge from scratch.”

“This kind of proof-of-concept demonstration carries that work into the ‘applied’ world,” he
adds, “where you can really translate these exotic electronic properties into compelling, state-of-the-art devices.”

This research was supported by the National Science Foundation (NSF), the Army Research Office’s
Multidisciplinary University Research Initiative, and the Air Force Office of Scientific Research. The team also benefited from the facilities at the Harvard Center for Nanoscale Systems, a member
of the NSF-supported National Nanotechnology Infrastructure Network. Sieu D. Ha, a postdoctoral fellow at SEAS, was the co-lead author; additional coauthors included graduate student You Zhou and Frank Schoofs, a former postdoctoral fellow.

 

 

 

REMINDER 8 week course on Lateral and Critical Thinking for Students and Adults starts on Tuesday Oct 8th at 7 pm in Toronto

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The structure of language- the orderof words influences learning

The order of words

The structure of language influences learning

Think of a frequently used noun or verb in our language. Try to count how
many times you have uttered it in the last two hours. Now, do the same with the
article "the". The language we speak is not only made of content words (nouns,
verbs, adjectives, for instance) but also of lots of words that provide a
support to them (articles, prepositions, etc.) that are used much more
frequently than the first (function words, or functors). Despite the huge
variability of known languages, language scientists were able to divide them
roughly into two main categories: the languages in which the functor precedes
the content word – and that use a Verb-Object order (VO) – and vice versa (OV).
The experimental observations showed that the frequency of the terms is a clue
that helps identifying to which category a language belongs and, as a
consequence, "tuning in" to it.

Knowing the language's structure enables the individual to segment the speech
(to divide the language flow into single words) and affects language
learnability. This effect has been observed also in very young children for some
languages, such as Italian and Japanese. Now a group of neuroscientists
including Jacques Mehler and Marina Nespor of the International School for
Advanced Studies (SISSA) of Trieste have extended the experiment also to adults,
employing a wider range of languages. The research has been published in the
review Frontiers in Psychology.

The experiment was carried on Italian and French native speakers (in
representation of the VO language group), and on Japanese and Basque native
speakers (OV languages), carrying out learning tasks centered on sentences in an
artificial (invented) language that could feature one of the two order
structures. "In the previous studies we observed that infants as young as
8-month-old already 'prefer' an artificial language that mirrors the structure
of their native language," explains Nespor. "In this new series of studies we
have observed this type of preference also in adults".

"This would also explain the increasingly greater difficulties encountered in
learning a new language when growing up. Children, while showing such preference
precociously, are in fact much more flexible and can easily learn also a
language that has a different word order from their own, while adults seem to be
more rigidly tied to their native language scheme." adds Nespor. "Of course,
when learning a language, also other variables come into play such as lexicon
and prosody" concludes the neuroscientist.

 

###

 

 

Surprisingly simple scheme for self-assembling robots

      Small cubes with no exterior moving parts can propel themselves forward, jump on top of each other, and snap together to form arbitrary shapes.  

 

    CAMBRIDGE, Mass. — In 2011, when an MIT senior named John Romanishin proposed a new design for modular robots to his robotics professor, Daniela Rus, she said, “That can’t be done.”

Two years later, Rus showed her colleague Hod Lipson, a robotics researcher at Cornell University, a video of prototype robots, based on Romanishin’s design, in action. “That can’t be done,” Lipson said.

In November, Romanishin — now a research scientist in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) — Rus, and postdoc Kyle Gilpin will establish once and for all that it can be done, when they present a paper describing their new robots at the IEEE/RSJ International Conference on Intelligent Robots and Systems.

Known as M-Blocks, the robots are cubes with no external moving parts. Nonetheless, they’re able to climb over and around one another, leap through the air, roll across the ground, and even move while suspended upside down from metallic surfaces. 

Inside each M-Block is a flywheel that can reach speeds of 20,000 revolutions per minute; when the flywheel is braked, it imparts its angular momentum to the cube. On each edge of an M-Block, and on every face, are cleverly arranged permanent magnets that allow any two cubes to attach to each other.

“It’s one of these things that the [modular-robotics] community has been trying to do for a long time,” says Rus, a professor of electrical engineering and computer science and director of CSAIL. “We just needed a creative insight and somebody who was passionate enough to keep coming at it — despite being discouraged.”

Embodied abstraction

As Rus explains, researchers studying reconfigurable robots have long used an abstraction called the sliding-cube model. In this model, if two cubes are face to face, one of them can slide up the side of the other and, without changing orientation, slide across its top.

The sliding-cube model simplifies the development of self-assembly algorithms, but the robots that implement them tend to be much more complex devices. Rus’ group, for instance, previously developed a modular robot called the Molecule, which consisted of two cubes connected by an angled bar and had 18 separate motors. “We were quite proud of it at the time,” Rus says.

According to Gilpin, existing modular-robot systems are also “statically stable,” meaning that “you can pause the motion at any point, and they’ll stay where they are.” What enabled the MIT researchers to drastically simplify their robots’ design was giving up on the principle of static stability.

“There’s a point in time when the cube is essentially flying through the air,” Gilpin says. “And you are depending on the magnets to bring it into alignment when it lands. That’s something that’s totally unique to this system.”

That’s also what made Rus skeptical about Romanishin’s initial proposal. “I asked him build a prototype,” Rus says. “Then I said, ‘OK, maybe I was wrong.’”

Sticking the landing

To compensate for its static instability, the researchers’ robot relies on some ingenious engineering. On each edge of a cube are two cylindrical magnets, mounted like rolling pins. When two cubes approach each other, the magnets naturally rotate, so that north poles align with south, and vice versa. Any face of any cube can thus attach to any face of any other.

The cubes’ edges are also beveled, so when two cubes are face to face, there’s a slight gap between their magnets. When one cube begins to flip on top of another, the bevels, and thus the magnets, touch. The connection between the cubes becomes much stronger, anchoring the pivot. On each face of a cube are four more pairs of smaller magnets, arranged symmetrically, which help snap a moving cube into place when it lands on top of another.

As with any modular-robot system, the hope is that the modules can be miniaturized: the ultimate aim of most such research is hordes of swarming microbots that can self-assemble, like the “liquid steel” androids in the movie “Terminator II.” And the simplicity of the cubes’ design makes miniaturization promising.

But the researchers believe that a more refined version of their system could prove useful even at something like its current scale. Armies of mobile cubes could temporarily repair bridges or buildings during emergencies, or raise and reconfigure scaffolding for building projects. They could assemble into different types of furniture or heavy equipment as needed. And they could swarm into environments hostile or inaccessible to humans, diagnose problems, and reorganize themselves to provide solutions.

Strength in diversity

The researchers also imagine that among the mobile cubes could be special-purpose cubes, containing cameras, or lights, or battery packs, or other equipment, which the mobile cubes could transport. “In the vast majority of other modular systems, an individual module cannot move on its own,” Gilpin says. “If you drop one of these along the way, or something goes wrong, it can rejoin the group, no problem.”

“It’s one of those things that you kick yourself for not thinking of,” Cornell’s Lipson says. “It’s a low-tech solution to a problem that people have been trying to solve with extraordinarily high-tech approaches.”

“What they did that was very interesting is they showed several modes of locomotion,” Lipson adds. “Not just one cube flipping around, but multiple cubes working together, multiple cubes moving other cubes — a lot of other modes of motion that really open the door to many, many applications, much beyond what people usually consider when they talk about self-assembly. They rarely think about parts dragging other parts — this kind of cooperative group behavior.”

In ongoing work, the MIT researchers are building an army of 100 cubes, each of which can move in any direction, and designing algorithms to guide them. “We want hundreds of cubes, scattered randomly across the floor, to be able to identify each other, coalesce, and autonomously transform into a chair, or a ladder, or a desk, on demand,” Romanishin says.    Written by: Larry Hardesty, MIT News Office

Brain may rely on computer-like mechanism to make sense of novel situations, says CU-Boulder study

Brain  may rely on computer-like mechanism to make sense of novel situations, says
CU-Boulder study

Our brains give us  the remarkable ability to make sense of situations we've never encountered before—a familiar person in an unfamiliar place, for example, or a coworker in a  different job role—but the mechanism our brains use to accomplish this has been  a longstanding mystery of neuroscience.

Now, researchers at  the University of Colorado Boulder have demonstrated that our brains could process these new situations by relying on a method similar to the "pointer" system used by computers. "Pointers" are used to tell a computer where to look for information stored elsewhere in the system to replace a variable.

For the study, published today in the Proceedings of the National Academy of Sciences, the research team relied on sentences with words used in unique ways to test the brain's ability to understand the role familiar words play in a sentence even when those words are used in unfamiliar, and even nonsensical, ways.

For example, in the sentence, "I want to desk you," we understand theword "desk" is being used as a verb even though our past experience with the word "desk" is as a noun.

"The fact that you understand that the sentence is grammatically well formed means you can process these completely novel inputs," said Randall O'Reilly, a professor in CU-Boulder's Department of Psychology and Neuroscience and co-author of the study. "But in the past when we've tried to get computer models of a brain to do that, we haven't been successful."

This shows that human brains are able to understand the sentence as a structure with variables—a subject, a verb and often, an object—and that the brain can assign a wide variety of words to those variables and still understand the sentence structure. But the way the brain does this has not been understood.

Computers routinely complete similar tasks. In computer science, for example, a computer program could create an email form letter that has a pointer in the greeting line. The pointer would then draw the name information for each individual recipient into the greeting being sent to that person.

In the new study, led by Trenton Kriete, a postdoctoral researcher in O'Reilly's lab, the scientists show that the connections in the brain between the prefrontal cortex and the basal ganglia could play a similar role to the pointers used in computer science. The researchers added new information about how the connections between those two regions of the brain could work into their model.

The result was that the model could be trained to understand simple sentences using a select group of words. After the training period, the researchers fed the model new sentences using familiar words in novel ways and found that the model could still comprehend the sentence structure.

While the results show that a pointer-like system could be at play in the brain, the function is not identical to the system used in computer science, the scientists said. It's similar to comparing an airplane's wing and a bird's wing, O'Reilly said. They're both used for flying but they work differently.

In the brain, for example, the pointer-like system must still be learned. The brain has to be trained, in this case, to understand sentences while a computer can be programmed to understand sentences immediately.

"As your brain learns, it gets better and better at processing these novel kinds of information," O'Reilly said.

###

Other study co-authors include David Noelle of the University of California, Merced, and Jonathan Cohen of Princeton University. The research was supported by an Intelligence Advanced Research Projects Activity grant through the U.S. Department of the Interior.

Mathematicians aim to take publishers out of publishing

Episciences Project to launch series of community-run, open-access journals.

17 January 2013

Jean-Pierre Demailly is a leader in an effort to create a researcher-run publishing system.

Mathematicians plan to launch a series of free open-access journals that will host their peer-reviewed
articles on the preprint server arXiv. The project was publicly revealed yesterday in a blog post by Tim Gowers, a Fields Medal winner and mathematician at the University of Cambridge, UK.

 

The initiative, called the Episciences Project, hopes to show that researchers can organize the peer
review and publication of their work at minimal cost, without involving commercial publishers.

“It’s a global vision of how the research community should work: we want to offer an alternative to traditional mathematics journals,” says Jean-Pierre Demailly, a mathematician at the University of Grenoble, France, who is a leader in the effort. Backed by funding from the French government, the initiative may launch as early as April, he says.

Many mathematicians — and researchers in other fields — claim that they already do most of the work
involved in publishing their research. At no cost, they type up and format
their own papers, post them to online servers, join journal editorial boards
and review the work of their peers. By creating journals that publish links to
peer-reviewed work on servers such as arXiv, Demailly says, the community could
run its own publishing system. The extra expense involved would be the cost of
maintaining websites and computer equipment, he says.

That cost is not small, but it
could eventually be provided in part by the journals' users. The arXiv server,
for example, costs about US$826,000 a year to run, and is funded by the Cornell
University Library in Ithaca, New
York; the Simons Foundation in New York and institutional members.

Demailly says that he first thought of open-access electronic journals that overlay arXiv eight years ago, but the concept became a reality only last June, when he was contacted by the
Centre for Direct Scientific Communication (CCSD), based in Villeurbanne,
France. The CCSD, a unit of the French National Centre for Scientific Research,
develops open-access repositories such as the multidisciplinary archive HAL,
which mirrors the arXiv site.

For the Episciences Project, the CCSD plans to create a publishing platform that will support online
peer-reviewed journals. Each journal, or ‘epijournal’, would have its own
editor and editorial board, and authors could submit their arXiv-posted papers
to their journal of choice. The journal would then organize peer review,
perhaps using workflow software provided by the CCSD. Peer-reviewed papers
would be posted on arXiv alongside their un-reviewed versions. A central
committee (led by Demailly) would manage new journal candidates and make
recommendations on paper formatting, but each journal would be free to set its
own policies (including whether to charge for publication).

Gowers plans to start a journal in the interdisciplinary field of additive combinatorics; Demailly would not
say what other early epijournals might be. Gowers has strong views on shaking
up research publishing — last year, he kick-started
a boycott of the Dutch publishing giant Elsevier (see also Nature’s
profile of Gowers).

The idea of overlaying arXiv is
not new: some mathematics journals tried it in the early 2000s but scrapped the
idea because libraries began dropping print subscriptions, says Demailly.
Meanwhile, there are already some free, community-organized mathematics
journals, such as Documenta Mathematica, funded by the German Mathematical Society. “They are doing things on their own with a small website; we will have a global platform
capable of drastically reducing an individual journal’s administration costs,”
Demailly says.

Demailly says that he expects to adjust the concept with feedback from the mathematics community. “If people want larger reviews linked to papers, or the possibility of online comments and
blogs, we can offer this with only minor changes to the platform,” he says. At
the moment, the model's success or failure hinges on buy-in from mathematicians
— but the involvement of Gowers and other prominent mathematicians, such as
Terence Tao of the University of California, Los
  Angeles, may help to build support.

Journal name: Nature

DOI:doi:10.1038/nature.2013.12243

 

 

Study pinpoints brain area's role in learning in Neuroscience

An area of the brain called the orbitofrontal cortex is
responsible for decisions made on the spur of the moment, but not those made
based on prior experience or habit, according to a new basic science study from
substance abuse researchers at the University of Maryland School of Medicine
and the National Institute on Drug Abuse (NIDA). Scientists had previously
believed that the area of the brain was responsible for both types of behavior
and decision-making. The distinction is critical to understanding the
neurobiology of decision-making, particularly with regard to substance abuse.
The study was published online in the journal Science.

Scientists have assumed that the orbitofrontal cortex plays a
role in "value-based" decision-making, when a person compares options
and weights consequences and rewards to choose best alternative. The Science
study shows that this area of the brain is involved in decision-making only
when the value must be inferred or computed rapidly or hastily. If the value
has been "cached" or pre-computed, like a habit, then the
orbitofrontal cortex is not necessary. The same is true for learning—if a
person infers an outcome but it does not happen, the resulting error can drive learning.
The study shows that the orbitofrontal cortex is necessary for the inferred
value that is used for this type of learning. "Our research showed that
damage to the orbitofrontal cortex may decrease a person's ability to use prior
experience to make good decisions on the fly," says lead author Joshua
Jones, Ph.D., a postdoctoral researcher at the University of Maryland School of
Medicine and a research scientist at NIDA, part of the National Institutes of
Health. "The person isn't able to consider the whole continuum of the
decision—the mind's map of how choices play out further down the road. Instead,
the person is going to regress to habitual behavior, gravitating toward the
choice that provides the most value in its immediate reward." The study
enhances scientists' understanding of how the brain works in healthy and
unhealthy individuals, according to the researchers. "This discovery has
general implications in understanding how the brain processes information to
help us make good decisions and to learn from our mistakes," says senior
author Geoffrey Schoenbaum, M.D., Ph.D., adjunct professor at the University of
Maryland School of Medicine and senior investigator and chief of the Cellular
Neurobiology Research Branch at NIDA. "Understanding more about the orbitofrontal
cortex also is important for understanding disorders such as addiction that
seem to involve maladaptive decision-making and learning. Cocaine in particular
seems to have long-lasting effects on the orbitofrontal cortex. One aspect of
this work, which we are pursuing, is that perhaps some of the problems that
characterize addiction are the result of drug-induced changes in this area of
the brain."

The scientists are continuing their research, examining the
specific coding of the neurons in the orbitofrontal cortex during this process,
as well as the effects that drugs of abuse have upon this area of the brain.
"Drug addiction is marked by severe deficits in judgment and bad
decision-making on the part of the addict," says Dr. Jones. "We
believe that drugs, particularly cocaine, affect the orbitofrontal cortex. They
coerce the system and hijack decision-making." The researchers examined
the orbitofrontal cortex's role in value-guided behavior. The brain assigns two
different types of values to behaviors and choices. Cached value is a value
that is learned during prior experience. Inferred value happens on the spur of
the moment, considering the entire model of rewards and consequences.
"Cached value is stored during prior experience, says Dr. Jones. "For
example, you learn your route home on your commute through experience—the habit
of how you get home. You turn right, go left, make another right. Inferred
values, however, are based on estimating goals and values on the fly using your
knowledge of the entire structure of the environment. For example, instead of
just habitually going home on your usual route, you have the full map in your
mind of all the roads that you use. You can adjust your route, making different
turns, depending on the time of day or the amount of traffic. These inferred
decisions are adaptive—much more flexible based on the situation." The
scientists used a rat model for their research, disabling the orbitofrontal
cortex and measuring the difference in behavior that resulted. Further study
using the same rat model—work not reported in this paper—has shown that cocaine
use mimics this damage to the orbitofrontal cortex. Further study of this
neurobiological mechanism is needed, and the results have not been replicated
in humans, but certainly the research is promising, says E. Albert Reece, M.D.,
Ph.D., M.B.A., vice president for medical affairs at the University of Maryland
and John Z. and Akiko K. Bowers Distinguished Professor and dean at the
University of Maryland School of Medicine. "Our goal here at the School of Medicine is to make groundbreaking
discoveries in the laboratory that can be translated into new treatments and
new hope for patients and their families," says Dean Reece. "We are
hopeful that research tells us more about the basic mechanisms in the brain
will translate to new techniques in neurobiology and in treating devastating
conditions such as drug addiction." Journal reference: Science Provided by
University of Maryland 



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