A 10-year old girl born with half of her cerebral cortex missing sees perfectly because of a massive reorganisation of the brain circuits involved in vision, a new study finds.

"It was quite a surprise to see that something like this is possible," says Lars Muckli, a neuroscientist at the University of Glasgow, UK, who was part of the team that imaged the girl's brain.

Doctors discovered that she was missing the right half at the age of three, after she began suffering from seizures.

Normal life

However, the seizures proved treatable and the girl – known as AH – lives an otherwise normal life. The left side of her body is slightly weaker than the right, but this hasn't stopped her from bicycling or roller-skating.

But what's most amazing, Muckli says, is her ability to see out of the left and right visual fields. Patients who have half of their cortex removed to treat epilepsy invariably lose half of their visual field. "They would only see half of the world; this is what's expected," he says.

That's because, each eye sends visual signals to two different halves of the brain via two distinct bundles of nerves. The nerves on the side of the eye nearest the nose are routed to the opposite side of the brain. The nerves nearest the temple, however, send information to the same side of the brain as the eye.

For example, the nose side of the left eye sends left visual field data to the right side of the brain; while the temple side of the left eye sends right visual field data to the left side of the brain.

For this reason, the right side of the brain processes our left visual field, and vice versa.

Rerouted neurons

AH, on the other hand, has no right hemisphere to receive any signal from her left visual field. What's more, her right eye never developed, so she should get visual information only from one half of her left eye – that is, from just one nerve bundle.

Brain scans performed by Muckli's team explain why that's not the case. Her retinal nerves that should normally connect to the right half of her brain instead set up shop in two parts of the left brain: the thalamus and the visual cortex.

In some cases, the diverted nerves seemed to have followed the molecular cues that would have guided nerves from the right eye, were they not missing. But for the most part, the left visual field neurons carved out their own islands in the right brain, Muckli says.

This kind of organisation allows AH's brain to process the left and right fields of vision distinctly from one another, ensuring that she sees both halves of her world.

"It's fascinating to have someone who is absolutely, completely behaving normally and then knowing she only has half of a brain," Muckli says.

Journal reference: Proceedings of the National Academy of Sciences, DOI: 10.1073/pnas.0809688106 (in press)

Unedited running notes from TEDGlobal 2009.

Henry Markram is leading the Blue Brain Project, which hopes to create a realistic digital 3D model of the whole human brain within the next 10 years. (The simulation promises to do all the things that real human brains can do, including consciousness.) He's done a proof of concept by modeling half of a rodent brain. Now he's scaling up the project to reach a human brain.

But why? It's essential to understand the brain for us to get along in society. We can't keep doing animal experimentation forever. We have to embody our data in a working digital model. We need better medicines that are more specific, more concrete, more precise. (Also, it's just fascinating.)

Markram, for the first time, shares how he is addressing one theory of how the brain works. The theory is that the brain "builds" a version of the universe and projects this version, like a bubble, all around us. But Markram says we can directly address this philosophical question with science. Anesthetics don't work by blocking receptors. They introduce a noise into the brain to confuse the neurons to prevent you from making "decisions." You must make decisions to perceive anything. 99% of what you see in a room is not what comes in through the eyes -- it's what you infer about that room.

Instead of speculating or philosophizing, we can actually build something to test the theories.

It took the universe 11 billion years to build a brain. The big step was the neocortex. It allowed animals to cope with parenthood, social functions. So the neocortex is the ultimate solution, the pinnacle of complex design that the universe has produced. The neocortex continues to evolve rapidly. The neocortex uses the same basic unit for computation, over and over again, and built up so fast evolutionarily that the brain had to fold itself up to fit more of the stuff into the skull.

The holy grail for neuroscience is to understand the design of the neocortical column. It will help us understand not just the brain, but perhaps physical reality. Understanding the structures that make it up is extremely difficult, because beyond just cataloging the parts, you have to figure out how they actually work -- and then build realistic digital models.

The branches of neurons intersect in millions of locations, and in each location, each synapse, communication happens. The circuit, or the fabric of the brain, the way it is patterned is a challenge to any theory of the brain. Every neuron is different. How is it possible, then, that we create a reality that we all share? Although the circuitry may change, the pattern of design does not change.

Mathematics underlies the models of the brain. Each neuron has a mathematical representation. Even though this simplifies things, you still need a huge computer to do the kinds of simulations Markram is talking about. You'd need one laptop for every single neuron in order to accurately model it. So what do you do? You go to IBM!

"Where is the rose?" is a popular formulation of what the study of cognition is all about. Amid the tangle of neurons, amid the raw, chaotic electrical activity, where is reality -- metaphorically thought of as a "rose" one is perceiving or thinking about -- actually physically represented? Markram looks at "electrical objects" that neural activity forms, in order to nail down how thoughts are represented.

The universe has evolved a structure for it to become aware of itself. We're about to create another such structure in the digital universe we ourselves have created.

Photo: Henry Markram at TEDGlobal 2009, Session 5: " Hidden algorithm," July 22, 2009, in Oxford, UK. Credit: TED / James Duncan Davidson

Pictures paint concepts of a thousand words- now, for the first time, scientists studying the brain have worked out how words paint concepts in our minds.

The team, including Professor Rodrigo Quian Quiroga at the Department of Engineering of the University of Leicester in the UK, Professor Itzhak Fried at the University California Los Angeles and Professor Christof Koch at the California Institute of Technology, has published these findings in the journal Current Biology. It is published online on 23 July and in the print issue on 11 August.

The results are important for understanding how perception and memory formation occurs.

Professor Rodrigo Quian Quiroga, head of Bioengineering at the University of Leicester, led the study which concluded that, although processing of visual and auditory information occur along completely separate pathways, the visual and auditory processing routes converge to end up firing the same single neurons.

He said: "Different pictures of Marilyn Monroe can evoke the same mental image, even if greatly modified as in Warhol's famous portraits. This process relates to one of the most fascinating questions in neuroscience: how do neurons in the brain manage to abstract and disregard irrelevant details to recognize highly variable pictures as the same person?"

Professor Quian Quiroga said various studies had provided insights into how visual information is processed in the brain. He added:

"Interestingly, in humans, the same "concept" of Marilyn can be evoked with other stimulus modalities, for instance by hearing or reading her name. Brain imaging studies have identified cortical areas in the human temporal lobe that are selective to voices and words. However, how visual, text and sound information can elicit a unique percept is still largely unknown."

The University of Leicester team in collaboration with UCLA and Caltech used presentations of pictures, spoken and written names to show that single neurons in the human hippocampus and surrounding areas respond selectively to representations of the same individual using different sensory prompts. For example a neuron responded to three pictures of the TV host "Oprah Winfrey", to her name written in the computer screen and to a computer synthesized voice saying "Oprah"; another one fired to different pictures and the written and pronounced name of "Luke Skywalker", from the classic movie "Star Wars". Another neuron fired strongly to the pictures and the written and spoken name of the ex-football star "Diego Maradona", even to a picture of Maradona in the soccer field when his face was not visible but the patient still recognized as Maradona.

They also found that such degree of abstraction -in the sense that neurons fired the same to different pictures or the name of a particular person- increased along the hierarchical structure within the areas they recorded from.

Moreover, Professor Quian Quiroga found neurons responding to his own pictures and name, thus suggesting that such neuronal representations can be generated relatively fast, because he was unknown to the patient a day or two before the recording took place.

Said Professor Quian Quiroga: "These results demonstrate that single neurons can encode concepts in a very abstract way, even if evoked by different sensory modalities"

The study breaks new ground by demonstrating how neurons previously studied by the team respond not only to picture, but to written and spoken names too.

Professor Quian Quiroga said: "The processing of visual and auditory information follows completely different cortical pathways in the brain, but we are showing that this information converges into single neurons in the hippocampus, at the very end of these pathways for processing sensory information.

"This work gives us further understandings of how information is processed in the brain, by creating a high level of abstraction which is important for perception and memory formation given that we tend to remember abstract concepts and forget irrelevant details."

Source: University of Leicester

A study by neuroscientist Heather Rupp and her team found that a woman's partner status influenced her interest in the opposite sex.

In the study, published in the March issue of Human Nature, women both with and without sexual partners showed little difference in their subjective ratings of photos of men when considering such measures as masculinity and attractiveness. However, the women who did not have sexual partners spent more time evaluating photos of men, demonstrating a greater interest in the photos. No such difference was found between men who had sexual partners and those who did not.

"These findings may reflect sex differences in reproductive strategies that may act early in the cognitive processing of potential partners and contribute to sex differences in sexual attraction and behavior," said Rupp, assistant scientist at The Kinsey Institute for Research in Sex, Gender and Reproduction at Indiana University in the US.

For the study, 59 men and 56 women rated 510 photos of opposite-sex faces for realism, masculinity/femininity, attractiveness, or affect. Participants were instructed to give their "gut" reaction and to rate the pictures as quickly as possible. The men and women ranged in age from 17 to 26, were heterosexual, from a variety of ethnic backgrounds and were not using hormonal contraception. Of the women, 21 reported they had a current sexual partner; 25 of the men reported having a sexual partner. This is the first study to report whether having a current sexual partner influences interest in the opposite sex. Other studies have demonstrated that hormones, relationship goals and social context influence such interest.

"That there were no detectable effects of sexual partner status on women's subjective ratings of male faces, but there were on response times, which emphasizes the subtlety of this effect and introduces the possibility that sexual partner status impacts women's cognitive processing of novel male faces but not necessarily their conscious subjective appraisal," the authors wrote in the journal article. The researchers also note that influence of partner status in women could reflect that women, on average, are relatively committed in their romantic relationships, "which possibly suppresses their attention to and appraisal of alternative partners."

Source: Springer

 

 

 

 

After 24 hours of starvation, neurons from females (left panel) mobilize free fatty acids and form lipid droplets (bright green), keeping them alive. In contrast, neurons from males (right panel) begin eating themselves from the inside to break down proteins, presumably to use as fuel. Credit: Robert S.B. Clark

When it comes to keeping brains alive, it seems nature has deemed that females are more valuable then males. As reported in this weeks' JBC, researchers found that nutrient deprivation of neurons produced sex-dependent effects. Male neurons more readily withered up and died, while female neurons did their best to conserve energy and stay alive.

The idea that the sexes respond differently to nutrient depravation is not new, and revolves around the male preferences to conserve protein and female preferences to conserve fat. However, these metabolic differences have really only been examined in nutrient-rich tissues like muscles, fat deposits, and the liver.

Robert Clark and colleagues at the Children's Hospital of Pittsburgh of University of Pittsburgh Medical Center examined whether this sex-dependent response in starvation could manifest in brain cells. They grew neurons taken separately from male and female rats or mice in lab dishes and subjected them to starvation over 72 hours.

After 24 hours, the male neurons experienced significantly more cell dysfunction (measured by analyzing cell respiration, which decreased by over 70% in male cells compared to 50% in female cells) and death. Visually, male neurons also displayed more abundant signs of autophagy, whereby a cell breaks down its components as a fuel source, while female neurons created more lipid droplets to store fat reserves.

As with other cell culture studies, the researchers note these results may not be truly indicative of what happens in living animals during starvation, but it allows them to look at the neurons independent of external factors like circulating hormones.

Article: "Starving Neurons Show Sex Difference in Autophagy" by Lina Du, Robert W. Hickey, Hülya Bayır, Simon C. Watkins, Vladimir Tyurin, Fengli Guo, Patrick M. Kochanek, Larry W. Jenkins, Jin Ren, Greg Gibson, Charleen T. Chu, Valerian E. Kagan, and Robert S. B. Clark
http://www.jbc.org/cgi/content/full/284/4/2383

Source: American Society for Biochemistry and Molecular Biology

When we watch a movie, we're usually not conscious of the cuts made by the editor. The camera angle may change dozens of times during a scene, and we follow along as if the flashing from one viewpoint to another wasn't at all unusual. You might think this is just because we've been accustomed to watching TV and movies, but researchers have found that even people who've never seen a motion picture have no difficulty following along with the cuts and different camera angles in a video.

But little research has actually been done on the impact of changing camera angles in a movie on our perception and memory of a scene. While cutting abruptly between camera angles seems unnatural, moving a camera from place to place while filming can be quite realistic: after all, people walk around all the time; their own viewpoint is constantly changing. One study did find that people have better memories for a static scene filmed with a moving camera, compared to two still shots taken from the beginning and end- points of the camera's motion.

But what about dynamic scenes? If the people in a scene are themselves moving, will an abrupt cut to a new camera angle disorient the viewer? Filmmakers have found anecdotally that a 180-degree shift in a cut can be extremely disorienting -- that's why when watching a football or basketball game we usually see the action from just one side of the field or court. But do smaller cuts have a similar impact?

A team led by Bärbel Garsoffky showed computer-generated ten-second movies of a half-court basketball game to 12 volunteers. In some of the movies, the camera maintained a steady position either at the side of the court or midcourt, looking straight at the hoop, like this:

In some movies, the camera angle abruptly changed form sidecourt to midcourt (or vice versa) four seconds into the film. In others, the camera moved smoothly between the two positions in a two-second-long pan. After watching each movie, viewers saw 24 still images. Twelve of the images represented actual court configurations from the movie they had just watched, while twelve images depicted the same players, but in positions they had never occupied during the movie. Viewers indicated whether each still shot represented a part of the game they had just watched.

Some of the still shots used the camera angle the viewer had originally seen them from, but others were from different camera angles: 45°, 90°, or 135° offset. Regardless of the camera angle in the test, viewers were equally accurate at remembering whether they had seen that still shot. But the camera motion during the original movie did matter:

There was no significant difference in the results for a static camera versus a moving camera, but viewers were significantly less accurate when they saw an abrupt cut in the movie. This decrease in accuracy was almost entirely found at the point in the movie immediately following the cut, suggesting quite strongly that the cut itself momentarily disoriented viewers. So although the perceptual system can handle cuts in a movie presentation, those cuts do have some cost.

I do wonder if the costs would be as evident in a longer scene. One reason movie editors like to make a lot of cuts is because it maintains visual interest. Perhaps at some point viewers would lose interest in a scene without cuts, and their memory for such a scene would actually be worse than a scene with cuts.

Over at Not Exactly Rocket Science, Ed Yong has a great summary of a new paper trying to figure out why information (at least in primates) can be just as rewarding as primal, biological rewards, such as calories and sex.

Ethan Bromberg-Martin and Okihide Hikosaka trained two thirsty rhesus monkeys to choose between two targets on a screen with a flick of their eyes; in return, they randomly received either a large drink or a small one after a few seconds. Their choice of target didn't affect which drink they received, but it did affect whether they got prior information about the size of their reward. One target brought up another symbol that told them how much water they would get, while the other brought up a random symbol.

After a few days of training, the monkeys almost always looked at the target that would give them advance intel, even though it never actually affected how much water they were given. They wanted knowledge for its own sake. What's more, even though the gap between picking a target and sipping some water was very small, the monkeys still wanted to know what was in store for them mere seconds later. To them, ignorance is far from bliss.

[SNIP]

This preference for knowledge about the future was intimately linked to the monkeys' desire for water. The same neurons in the middle of their brains signalled their expectations of both rewards - the watery prizes and knowledge about them.

All the neurons in question release the signalling chemical dopamine. While the monkeys were making their choices, Bromberg-Martin and Hikosaka recorded the activity of 47 dopamine neurons in their midbrains. These neurons became very excited when the monkeys saw a symbol that predicted a large amount of water, while the symbol that cued a smaller drink inhibited the neurons. The same dopamine neurons were excited during trials where the monkey only saw the symbol that heralded forthcoming information, and they were inhibited if they monkey only saw the other non-informative symbol.

So the same population of midbrain neurons signal changes in both the thirst for water and for knowledge. The more active they are, the stronger that thirst is. One monkey had a stronger preference for early information than the other and indeed, its dopamine neurons were more active when it saw the informative symbol. Even for each individual monkey, the neurons were more active on specific trials where they showed a preference for advanced knowledge.

These experiments elegantly demonstrate an essential feature of the human mind, which is how evolution bootstrapped our penchant for ideas to the same reward circuits that govern our animal appetites. In other words, the political activist on hunger strike might still be relying on his reward circuity, even though he's actually denying himself caloric treats: the cause is simply more important than food. That's what makes ideas so powerful: No matter how esoteric or ethereal or abstract they get, they are ultimately plugged back into the same system that makes us want sex and sugar. The end result is that we can crave knowledge and facts just like a thirsty person craves water.

UPDATE: And doesn't this also help explain the allure of suspenseful narratives? A good story, after all, is simply the artful denial of information - Will Elizabeth marry Darcy? Will Jason Bourne survive Moscow? - so that the audience craves resolution, which arrives in the form of information. The happy ending is a universal human reward.

For the last four years, Henry Markram has been building a biologically accurate artificial brain. Powered by a supercomputer, his software model closely mimics the activity of a vital section of a rat's gray matter.

Dubbed Blue Brain, the simulation shows some strange behavior. The artificial "cells" respond to stimuli and suddenly pulse and flash in spooky unison, a pattern that isn't programmed but emerges spontaneously.

"It's the neuronal equivalent of a Mexican wave," says Dr. Markram, referring to what happens when successive clusters of stadium spectators briefly stand and raise their arms, creating a ripple effect. Such synchronized behavior is common in flesh-and-blood brains, where it's believed to be a basic step necessary for decision making. But when it arises in an artificial system, it's more surprising.

Photo: Artificial Intelligence

Artificial neurons in Blue Brain, a biologically accurate artificial brain powered by a supercomputer.

Blue Brain Project

Scientists Create Artificial Brain

Meet Blue Brain, a "brain" made up entirely of silicon and housed inside an IBM supercomputer. An astonishing advance, the artificial brain may be the first step toward manmade higher behavior, WSJ's Gautam Naik reports.

Blue Brain is based at the École Polytechnique Fédérale de Lausanne in Switzerland. The project hopes to tackle one of the most perplexing mysteries of neuroscience: How does human intelligence emerge? The Blue Brain scientists hope their computer model can shed light on the puzzle, and possibly even replicate intelligence in some way.

"We're building the brain from the bottom up, but in silicon," says Dr. Markram, the leader of Blue Brain, which is powered by a supercomputer provided by International Business Machines Corp. "We want to understand how the brain learns, how it perceives things, how intelligence emerges."

Blue Brain is controversial, and its success is far from assured. Christof Koch of the California Institute of Technology, a scientist who studies consciousness, says the Swiss project provides vital data about how part of the brain works. But he says that Dr. Markram's approach is still missing algorithms, the biological programming that yields higher-level functions.

"You need to have a theory about how a particular circuit in the brain" can trigger complex, higher-order properties, Dr. Koch argues. "You can't assemble ever larger data fields and shake it and say, 'Ah, that's how consciousness emerges.'"

Despite the challenges, the push to understand, replicate and even re-enact higher behaviors in the brain has become one of the hottest areas of neuroscience. With the help of a $4.9 million grant from the U.S. Department of Defense, IBM is working on a separate project with five U.S. universities to build a tiny, low-power microchip that simulates the behavior of one million neurons and ten billion synapses. The goal, says IBM, is to develop brainy computers that can better predict the behavior of complex systems, such as weather or the financial markets.

The Chinese government has provided about $1.5 million to a team at Xiamen University to create artificial-brain robots with microcircuits that evolve, learn and adapt to real-world situations. Similarly, Jeff Krichmar and colleagues at the University of California, Irvine, Calif., have built an artificial-brain robot that learns to sharpen its visual perception when moving around in a lab environment, another form of emergent behavior, a form of spontaneous self-organization. And researchers at Sensopac, a project backed by a grant of €6.7 million ($9.3 million) from the European Union, have built part of an artificial mouse brain.

The scientists behind Blue Brain hope to have a virtual human brain functioning in ten years -- a lengthy time period that underscores the scientific challenge. The human brain has 100 billion neurons that send electrical signals to each other via a network of at least 100 trillion connections, or synapses. How could this dizzying complexity ever be recreated in a virtual model?

Dr. Markram has adopted a systematic, if painstaking approach. He decided to work out the blueprint of its wiring and then use that map to rebuild the brain in an artificial form. He focused on a rat's neocortical column, or NCC, an elementary building block of the brain's neocortex, which is responsible for higher functions and thought. In a rat's case, that includes planning to obtain food.

A rat's NCC, comprised of about 10,000 neurons and their 10 million connections, functions much like a computer microprocessor. All mammals have NCCs, and the ones in humans aren't all that different from the ones in rats. However, humans have far more NCCs, which means far greater brain power. Dr. Markram figured that if a rat simulation did a good job of correctly mimicking activity in a real rat's brain, he could use the same model as a road map for simulating the human brain.

Dr. Markram began by collecting detailed information about the rat's NCC, down to the level of genes, proteins, molecules and the electrical signals that connect one neuron to another. These complex relationships were then turned into millions of equations, written in software. He then recorded real-world data -- the strength and path of each electrical signal -- directly from rat brains to test the accuracy of the software.

At the Lausanne lab one recent afternoon, a pink sliver of rat brain sat in a beaker containing a colorless liquid. The neurons in the brain slice were still alive and actively communicating with each other. Nearby, a modified microscope recorded some of this inner activity in another brain slice. "We're intercepting the electro-chemical messages" in the cells, then testing the software against it for accuracy, said Dr. Markram.

The rat's NCC has 10,000 neurons, and it takes the power of one desktop computer to mimic the behavior of a single neuron. To model the entire NCC, Dr. Markram relies on an IBM computer that can perform 22.8 trillion operations a second. This enables the simulation to be rendered as a three-dimensional object. Thus, when Blue Brain is running, its deepest inner workings are seen in astonishing detail, in the form of a 3-D simulation that unfolds on a computer screen.

In a darkened room, Blue Brain displays a virtual NCC as a column-like structure, its blue color signifying a state of rest. When zapped by a simulated electrical current, the neurons start to signal to each other and their wiring progressively sparks to life different colors. Tests indicate the same areas light up in the model as do in a real rat's brain, suggesting that Blue Brain is accurate, says Dr. Markram.

More complex things start to happen. First there's a burst of red, then white, then red again, as the NCC's wiring fills up with a cascade of myriad signals. There are so many connections, the NCC looks like an incredibly dense tangle of undergrowth.

Then, two successive waves of yellow color suddenly race through Blue Brain. It's a sign that the neurons have synchronized their behavior on their own. "The cells start to take on a life of their own," says Dr. Markram. "That's what your brain is [and when such patterns become sophisticated] it becomes your personality."

If Blue Brain ever gets sophisticated enough to closely mimic the human brain, will it exhibit consciousness? Says Dr. Markram: "If it does emerge, we'll be able to tell you how it emerged. If it doesn't, we'll know that it's the result of more than just 100 million neurons interacting."

To me, and I suspect many readers, the quest for information can be an intensely rewarding experience. Discovering a previously elusive fact or soaking up a finely crafted argument can be as pleasurable as eating a fine meal when hungry or dousing a thirst with drink. This isn't just a fanciful analogy - a new study suggests that the same neurons that process the primitive physical rewards of food and water also signal the more abstract mental rewards of information.

Humans generally don't like being held in suspense when a big prize is on the horizon. If we get wind of a raise or a new job, we like to get advance information about what's in store. It turns out that monkeys feel the same way and like us, they find that information about a reward is rewarding in itself.

Ethan Bromberg-Martin and Okihide Hikosaka trained two thirsty rhesus monkeys to choose between two targets on a screen with a flick of their eyes; in return, they randomly received either a large drink or a small one after a few seconds. Their choice of target didn't affect which drink they received, but it did affect whether they got prior information about the size of their reward. One target brought up another symbol that told them how much water they would get, while the other brought up a random symbol.

After a few days of training, the monkeys almost always looked at the target that would give them advance intel, even though it never actually affected how much water they were given. They wanted knowledge for its own sake. What's more, even though the gap between picking a target and sipping some water was very small, the monkeys still wanted to know what was in store for them mere seconds later. To them, ignorance is far from bliss.

Bromberg-Martin and Hikosaka demonstrated that even more clearly with a second, slightly different task. This time, the monkeys always received information about their watery rewards and the initial choice of symbol simply determined how quickly this information was provided. After a few goes, the monkeys clearly wanted their info immediately. If the researchers swapped the target that provided the most instant information, the monkeys swapped the direction of their gaze.

This preference for knowledge about the future was intimately linked to the monkeys' desire for water. The same neurons in the middle of their brains signalled their expectations of both rewards - the watery prizes and knowledge about them.

All the neurons in question release the signalling chemical dopamine. While the monkeys were making their choices, Bromberg-Martin and Hikosaka recorded the activity of 47 dopamine neurons in their midbrains. These neurons became very excited when the monkeys saw a symbol that predicted a large amount of water, while the symbol that cued a smaller drink inhibited the neurons. The same dopamine neurons were excited during trials where the monkey only saw the symbol that heralded forthcoming information, and they were inhibited if they monkey only saw the other non-informative symbol.

So the same population of midbrain neurons signal changes in both the thirst for water and for knowledge. The more active they are, the stronger that thirst is. One monkey had a stronger preference for early information than the other and indeed, its dopamine neurons were more active when it saw the informative symbol. Even for each individual monkey, the neurons were more active on specific trials where they showed a preference for advanced knowledge.

Dopamine neurons are thought to be involved in learning about rewards - by adjusting the connections between other neurons, they "teach" the brain to seek basic rewards like food and water. Bromberg-Martin and Hikosaka think that these neurons also teach the brain to seek out information so that their activity becomes a sort of "common currency" that governs both basic needs and a quest for knowledge.

Reference: Neuron 10.1016/j.neuron.2009.06.009

US scientists conducting the largest ever imaging study of depression found that a thinning of the brain's cortex in the right hemisphere appeared to be linked to inherited or the familial form of depression.

The research was led by Dr Myrna Weissman, professor of epidemiology in psychiatry, Columbia University College of Physicians and Surgeons, and director of the Division of Epidemiology at the New York State Psychiatric Institute and is to be published online in the Proceedings of the National Academy of Sciences (PNAS).

The first author of the study was Dr Bradley Peterson, director of Child & Adolescent Psychiatry and director of MRI Research in the Department of Psychiatry at Columbia University Medical Center and the New York State Psychiatric Institute.

Weissman, Peterson and colleagues found that the right brain cortex of people at high risk of developing depression was 28 per cent thinner compared with that of people with no known risk. The cortex is the outermost layer of the brain.

The researchers said they were amazed by this result: this amount of thinning is on a par with the amount of brain loss they see in people with Alzheimer's disease and schizophrenia.

Peterson told the press that:

"The difference was so great that at first we almost didn't believe it."

"But we checked and re-checked all of our data, and we looked for all possible alternative explanations, and still the difference was there," he said.

Speculating on how a thinner cortex may be linked to depression, Peterson said perhaps it disrupts a person's ability to pay attention to and make sense of social and emotional cues from others.

The researchers also tested participants' level of inattention to and memory of social cues and they found that the ones who performed the worst had the least brain matter in the right cortex.

For the study, using MRI brain imaging, Weissman, Peterson and colleagues compared the thickness of the cortex in 131 people aged between 6 and 54 with and without a family history of depression.

The participants were pulled from an earlier study which Weissman had started 27 years ago: the Children at High and Low Risk of Depression study. Weissman had identified people with moderate to severe depression, and those with no such history, and followed their families for 25 years. She found that depression was handed down in the high risk families. This latest imaging study is part of the 20 year follow up, when Weissman asked Peterson to collaborate on the imaging. The cohort now includes three generations.

The brain imaging showed that the brains of biological offspring of depressed people had structural differences that didn't show up in the offspring of people with no history of mental illness.

The researchers found that thinning on the right side of the brain was linked to a raised risk of depression, it was not linked to higher incidence of depression itself. It was only those people who also had less brain matter on the left side who went on to develop depression or anxiety.

Peterson said:

"Our findings suggest rather strongly that if you have thinning in the right hemisphere of the brain, you may be predisposed to depression and may also have some cognitive and inattention issues."

But he went on to explain that:

"The more thinning you have, the greater the cognitive problems. If you have additional thinning in the same region of the left hemisphere, that seems to tip you over from having a vulnerability to developing symptoms of an overt illness."

Peterson suggested that if the way the illness develops starts with thinning of the cortex, then maybe treatments can target this. For example, perhaps current methods for improving attention and memory, with and without drugs used to treat ADHD, could turn out to be effective for people who have familial depression and this pattern of cortical thinning.

Perhaps treating their inattention could improve the way they process social information. But he said although it might be a plausible hypothesis, it was also highly speculative.

Peterson and Weissman plan to look at more brain images, this time using fMRI, to examine more closely how particular patterns of thinning affect how the brain behaves during attentional tasks in people with and without a history of familial depression.

They also hope to find out which types of cells are most affected by the reduced brain matter, and the causal pathways that lead from cortical thinning to depression, plus by studying DNA of participants, discover any genes that might raise the risk of developing depression and/or the risk of having more thinning in the cortex.

The study was sponsored by the National Institute of Mental Health of the National Institutes of Health.

"Cortical thinning in persons at increased familial risk for major depression."
Peterson BS, et al
PNAS 2009.

Sources: Columbia University Medical Center.

Written by: Catharine Paddock, PhD