Arquivo da tag: neurociências

The eyes have it: Men do see things differently to women (BioMed Central)

By Hilary Glover

BioMed Central

The way that the visual centers of men and women’s brains works is different, finds new research published in BioMed Central’s open access journal Biology of Sex Differences. Men have greater sensitivity to fine detail and rapidly moving stimuli, but women are better at discriminating between colors.

In the brain there are high concentrations of male sex hormone (androgen) receptors throughout cerebral cortex, especially in the visual cortex which is responsible for processing images. Androgens are also responsible for controlling the development of neurons in the visual cortex during embryogenesis, meaning that males have 25% more of these neurons than females.

Researchers from Brooklyn and Hunter Colleges of the City University of New York compared the vision of men and women aged over 16 from both college and high school, including students and staff. All volunteers were required to have normal color vision and 20/20 sight (or 20/20 when corrected by glasses or contact lenses).

When the volunteers were required to describe colors shown to them across the visual spectrum it became obvious that the color vision of men was shifted, and that they required a slightly longer wavelength to experience the same hue as the women. The males also had a broader range in the center of the spectrum where they were less able to discriminate between colors.

An image of light and dark bars was used to measure contrast-sensitivity functions (CSF) of vision; the bars were either horizontal or vertical and volunteers had to choose which one they saw. In each image, when the light and dark bars were alternated the image appeared to flicker.

By varying how rapidly the bars alternated or how close together they were, the team found that at moderate rates of image change, observers lost sensitivity for close together bars, and gained sensitivity when the bars were farther apart. However when the image change was faster both sexes were less able to resolve the images over all bar widths. Overall the men were better able to resolve more rapidly changing images that were closer together than the women.

Prof Israel Abramov, who led this study commented, “As with other senses, such as hearing and the olfactory system, there are marked sex differences in vision between men and women. The elements of vision we measured are determined by inputs from specific sets of thalamic neurons into the primary visual cortex. We suggest that, since these neurons are guided by the cortex during embryogenesis, that testosterone plays a major role, somehow leading to different connectivity between males and females. The evolutionary driving force between these differences is less clear.”


Sex & vision I: Spatio-temporal resolution Israel Abramov, James Gordon, Olga Feldman and Alla Chavarga Biology of Sex Differences (in press)

Sex and vision II: Color appearance of monochromatic lights Israel Abramov, James Gordon, Olga Feldman and Alla Chavarga Biology of Sex Differences (in press)

Why Are Elderly Duped? Area in Brain Where Doubt Arises Changes With Age (Science Daily)

ScienceDaily (Aug. 16, 2012) — Everyone knows the adage: “If something sounds too good to be true, then it probably is.” Why, then, do some people fall for scams and why are older folks especially prone to being duped?

An answer, it seems, is because a specific area of the brain has deteriorated or is damaged, according to researchers at the University of Iowa. By examining patients with various forms of brain damage, the researchers report they’ve pinpointed the precise location in the human brain, called the ventromedial prefrontal cortex, that controls belief and doubt, and which explains why some of us are more gullible than others.

“The current study provides the first direct evidence beyond anecdotal reports that damage to the vmPFC (ventromedial prefrontal cortex) increases credulity. Indeed, this specific deficit may explain why highly intelligent vmPFC patients can fall victim to seemingly obvious fraud schemes,” the researchers wrote in the paper published in a special issue of the journal Frontiers in Neuroscience.

A study conducted for the National Institute of Justice in 2009 concluded that nearly 12 percent of Americans 60 and older had been exploited financially by a family member or a stranger. And, a report last year by insurer MetLife Inc. estimated the annual loss by victims of elder financial abuse at $2.9 billion.

The authors point out their research can explain why the elderly are vulnerable.

“In our theory, the more effortful process of disbelief (to items initially believed) is mediated by the vmPFC, which, in old age, tends to disproportionately lose structural integrity and associated functionality,” they wrote. “Thus, we suggest that vulnerability to misleading information, outright deception and fraud in older adults is the specific result of a deficit in the doubt process that is mediated by the vmPFC.”

The ventromedial prefrontal cortex is an oval-shaped lobe about the size of a softball lodged in the front of the human head, right above the eyes. It’s part of a larger area known to scientists since the extraordinary case of Phineas Gage that controls a range of emotions and behaviors, from impulsivity to poor planning. But brain scientists have struggled to identify which regions of the prefrontal cortex govern specific emotions and behaviors, including the cognitive seesaw between belief and doubt.

The UI team drew from its Neurological Patient Registry, which was established in 1982 and has more than 500 active members with various forms of damage to one or more regions in the brain. From that pool, the researchers chose 18 patients with damage to the ventromedial prefrontal cortex and 21 patients with damage outside the prefrontal cortex. Those patients, along with people with no brain damage, were shown advertisements mimicking ones flagged as misleading by the Federal Trade Commission to test how much they believed or doubted the ads. The deception in the ads was subtle; for example, an ad for “Legacy Luggage” that trumpets the gear as “American Quality” turned on the consumer’s ability to distinguish whether the luggage was manufactured in the United States versus inspected in the country.

Each participant was asked to gauge how much he or she believed the deceptive ad and how likely he or she would buy the item if it were available. The researchers found that the patients with damage to the ventromedial prefrontal cortex were roughly twice as likely to believe a given ad, even when given disclaimer information pointing out it was misleading. And, they were more likely to buy the item, regardless of whether misleading information had been corrected.

“Behaviorally, they fail the test to the greatest extent,” says Natalie Denburg, assistant professor in neurology who devised the ad tests. “They believe the ads the most, and they demonstrate the highest purchase intention. Taken together, it makes them the most vulnerable to being deceived.” She added the sample size is small and further studies are warranted.

Apart from being damaged, the ventromedial prefrontal cortex begins to deteriorate as people reach age 60 and older, although the onset and the pace of deterioration varies, says Daniel Tranel, neurology and psychology professor at the UI and corresponding author on the paper. He thinks the finding will enable doctors, caregivers, and relatives to be more understanding of decision making by the elderly.

“And maybe protective,” Tranel adds. “Instead of saying, ‘How would you do something silly and transparently stupid,’ people may have a better appreciation of the fact that older people have lost the biological mechanism that allows them to see the disadvantageous nature of their decisions.”

The finding corroborates an idea studied by the paper’s first author, Erik Asp, who wondered why damage to the prefrontal cortex would impair the ability to doubt but not the initial belief as well. Asp created a model, which he called the False Tagging Theory, to separate the two notions and confirm that doubt is housed in the prefrontal cortex.

“This study is strong empirical evidence suggesting that the False Tagging Theory is correct,” says Asp, who earned his doctorate in neuroscience from the UI in May and is now at the University of Chicago.

Kenneth Manzel, Bryan Koestner, and Catherine Cole from the UI are contributing authors on the paper. The National Institute on Aging and the National Institute of Neurological Disorders and Stroke funded the research.

Researchers Produce First Complete Computer Model of an Organism (Science Daily)

ScienceDaily (July 21, 2012) — In a breakthrough effort for computational biology, the world’s first complete computer model of an organism has been completed, Stanford researchers reported last week in the journal Cell.

The Covert Lab incorporated more than 1,900 experimentally observed parameters into their model of the tiny parasite Mycoplasma genitalium. () (Credit: Illustration by Erik Jacobsen / Covert Lab)

A team led by Markus Covert, assistant professor of bioengineering, used data from more than 900 scientific papers to account for every molecular interaction that takes place in the life cycle of Mycoplasma genitalium, the world’s smallest free-living bacterium.

By encompassing the entirety of an organism in silico, the paper fulfills a longstanding goal for the field. Not only does the model allow researchers to address questions that aren’t practical to examine otherwise, it represents a stepping-stone toward the use of computer-aided design in bioengineering and medicine.

“This achievement demonstrates a transforming approach to answering questions about fundamental biological processes,” said James M. Anderson, director of the National Institutes of Health Division of Program Coordination, Planning and Strategic Initiatives. “Comprehensive computer models of entire cells have the potential to advance our understanding of cellular function and, ultimately, to inform new approaches for the diagnosis and treatment of disease.”

The research was partially funded by an NIH Director’s Pioneer Award from the National Institutes of Health Common Fund.

From information to understanding

Biology over the past two decades has been marked by the rise of high-throughput studies producing enormous troves of cellular information. A lack of experimental data is no longer the primary limiting factor for researchers. Instead, it’s how to make sense of what they already know.

Most biological experiments, however, still take a reductionist approach to this vast array of data: knocking out a single gene and seeing what happens.

“Many of the issues we’re interested in aren’t single-gene problems,” said Covert. “They’re the complex result of hundreds or thousands of genes interacting.”

This situation has resulted in a yawning gap between information and understanding that can only be addressed by “bringing all of that data into one place and seeing how it fits together,” according to Stanford bioengineering graduate student and co-first author Jayodita Sanghvi.

Integrative computational models clarify data sets whose sheer size would otherwise place them outside human ken.

“You don’t really understand how something works until you can reproduce it yourself,” Sanghvi said.

Small is beautiful

Mycoplasma genitalium is a humble parasitic bacterium known mainly for showing up uninvited in human urogenital and respiratory tracts. But the pathogen also has the distinction of containing the smallest genome of any free-living organism — only 525 genes, as opposed to the 4,288 of E. coli, a more traditional laboratory bacterium.

Despite the difficulty of working with this sexually transmitted parasite, the minimalism of its genome has made it the focus of several recent bioengineering efforts. Notably, these include the J. Craig Venter Institute’s 2008 synthesis of the first artificial chromosome.

“The goal hasn’t only been to understand M. genitalium better,” said co-first author and Stanford biophysics graduate student Jonathan Karr. “It’s to understand biology generally.”

Even at this small scale, the quantity of data that the Stanford researchers incorporated into the virtual cell’s code was enormous. The final model made use of more than 1,900 experimentally determined parameters.

To integrate these disparate data points into a unified machine, the researchers modeled individual biological processes as 28 separate “modules,” each governed by its own algorithm. These modules then communicated to each other after every time step, making for a unified whole that closely matched M. genitalium‘s real-world behavior.

Probing the silicon cell

The purely computational cell opens up procedures that would be difficult to perform in an actual organism, as well as opportunities to reexamine experimental data.

In the paper, the model is used to demonstrate a number of these approaches, including detailed investigations of DNA-binding protein dynamics and the identification of new gene functions.

The program also allowed the researchers to address aspects of cell behavior that emerge from vast numbers of interacting factors.

The researchers had noticed, for instance, that the length of individual stages in the cell cycle varied from cell to cell, while the length of the overall cycle was much more consistent. Consulting the model, the researchers hypothesized that the overall cell cycle’s lack of variation was the result of a built-in negative feedback mechanism.

Cells that took longer to begin DNA replication had time to amass a large pool of free nucleotides. The actual replication step, which uses these nucleotides to form new DNA strands, then passed relatively quickly. Cells that went through the initial step quicker, on the other hand, had no nucleotide surplus. Replication ended up slowing to the rate of nucleotide production.

These kinds of findings remain hypotheses until they’re confirmed by real-world experiments, but they promise to accelerate the process of scientific inquiry.

“If you use a model to guide your experiments, you’re going to discover things faster. We’ve shown that time and time again,” said Covert.


Much of the model’s future promise lies in more applied fields.

CAD — computer-aided design — has revolutionized fields from aeronautics to civil engineering by drastically reducing the trial-and-error involved in design. But our incomplete understanding of even the simplest biological systems has meant that CAD hasn’t yet found a place in bioengineering.

Computational models like that of M. genitalium could bring rational design to biology — allowing not only for computer-guided experimental regimes, but also for the wholesale creation of new microorganisms.

Once similar models have been devised for more experimentally tractable organisms, Karr envisions bacteria or yeast specifically designed to mass-produce pharmaceuticals.

Bio-CAD could also lead to enticing medical advances — especially in the field of personalized medicine. But these applications are a long way off, the researchers said.

“This is potentially the new Human Genome Project,” Karr said. “It’s going to take a really large community effort to get close to a human model.”

Stanford’s Department of Bioengineering is jointly operated by the School of Engineering and the School of Medicine.

Scientists Read Monkeys’ Inner Thoughts: Brain Activity Decoded While Monkeys Avoid Obstacle to Touch Target (Science Daily)

ScienceDaily (July 19, 2012) — By decoding brain activity, scientists were able to “see” that two monkeys were planning to approach the same reaching task differently — even before they moved a muscle.

The obstacle-avoidance task is a variation on the center-out reaching task in which an obstacle sometimes prevents the monkey from moving directly to the target. The monkey must first place a cursor (yellow) on the central target (purple). This was the starting position. After the first hold, a second target appeared (green). After the second hold an obstacle appeared (red box). After the third hold, the center target disappeared, indicating a “go” for the monkey, which then moved the cursor out and around the obstacle to the target. (Credit: Moran/Pearce)

Anyone who has looked at the jagged recording of the electrical activity of a single neuron in the brain must have wondered how any useful information could be extracted from such a frazzled signal.

But over the past 30 years, researchers have discovered that clear information can be obtained by decoding the activity of large populations of neurons.

Now, scientists at Washington University in St. Louis, who were decoding brain activity while monkeys reached around an obstacle to touch a target, have come up with two remarkable results.

Their first result was one they had designed their experiment to achieve: they demonstrated that multiple parameters can be embedded in the firing rate of a single neuron and that certain types of parameters are encoded only if they are needed to solve the task at hand.

Their second result, however, was a complete surprise. They discovered that the population vectors could reveal different planning strategies, allowing the scientists, in effect, to read the monkeys’ minds.

By chance, the two monkeys chosen for the study had completely different cognitive styles. One, the scientists said, was a hyperactive type, who kept jumping the gun, and the other was a smooth operator, who waited for the entire setup to be revealed before planning his next move. The difference is clearly visible in their decoded brain activity.

The study was published in the July 19th advance online edition of the journal Science.

All in the task

The standard task for studying voluntary motor control is the “center-out task,” in which a monkey or other subject must move its hand from a central location to targets placed on a circle surrounding the starting position.

To plan the movement, says Daniel Moran, PhD, associate professor of biomedical engineering in the School of Engineering & Applied Science and of neurobiology in the School of Medicine at Washington University in St. Louis, the monkey needs three pieces of information: current hand and target position and the velocity vector that the hand will follow.

In other words, the monkey needs to know where his hand is, what direction it is headed and where he eventually wants it to go.

A variation of the center-out task with multiple starting positions allows the neural coding for position to be separated from the neural coding for velocity.

By themselves, however, the straight-path, unimpeded reaches in this task don’t let the neural coding for velocity to be distinguished from the neural coding for target position, because these two parameters are always correlated. The initial velocity of the hand and the target are always in the same direction.

To solve this problem and isolate target position from movement direction, doctoral student Thomas Pearce designed a novel obstacle-avoidance task to be done in addition to the center-out task.

Crucially, in one-third of the obstacle-avoidance trials, either no obstacle appeared or the obstacle didn’t block the monkey’s path. In either case, the monkey could move directly to the target once he got the “go” cue.

The population vector corresponding to target position showed up during the third hold of the novel task, but only if there was an obstacle. If an obstacle appeared and the monkey had to move its hand in a curved trajectory to reach the target, the population vector lengthened and pointed at the target. If no obstacle appeared and the monkey could move directly to the target, the population vector was insignificant.

In other words, the monkeys were encoding the position of the target only when it did not lie along a direct path from the starting position and they had to keep its position “in mind” as they initially moved in the “wrong” direction.

“It’s all,” Moran says, “in the design of the task.”

And then some magic happens

Pearce’s initial approach to analyzing the data from the experiment was the standard one of combining the data from the two monkeys to get a cleaner picture.

“It wasn’t working,” Pearce says, “and I was frustrated because I couldn’t figure out why the data looked so inconsistent. So I separated the data by monkey, and then I could see, wow, they’re very different. They’re approaching this task differently and that’s kind of cool.”

The difference between the monkey’s’ styles showed up during the second hold. At this point in the task, the target was visible, but the obstacle had not yet appeared.

The hyperactive monkey, called monkey H, couldn’t wait. His population vector during that hold showed that he was poised for a direct reach to the target. When the obstacle was then revealed, the population vector shortened and rotated to the direction he would need to move to avoid the obstacle.

The smooth operator, monkey G, in the meantime, idled through the second hold, waiting patiently for the obstacle to appear. Only when it was revealed did he begin to plan the direction he would move to avoid the obstacle.

Because he didn’t have to correct course, monkey G’s strategy was faster, so what advantage was it to monkey H to jump the gun? In the minority of trials where no obstacle appeared, monkey H approached the target more accurately than monkey G. Maybe monkey H is just cognitively adapted to a Whac-A-Mole world. And monkey G, when caught without a plan, was at a disadvantage.

Working with the monkeys, the scientists had been aware that they had very different personalities, but they had no idea this difference would show up in their neural recordings.

“That’s what makes this really interesting,” Moran says.

Human brains unlikely to evolve into a ‘supermind’ as price to pay would be too high (University of Warwick)

University of Warwick

Human minds have hit an evolutionary “sweet spot” and – unlike computers – cannot continually get smarter without trade-offs elsewhere, according to research by the University of Warwick.

Researchers asked the question why we are not more intelligent than we are given the adaptive evolutionary process. Their conclusions show that you can have too much of a good thing when it comes to mental performance.

The evidence suggests that for every gain in cognitive functions, for example better memory, increased attention or improved intelligence, there is a price to pay elsewhere – meaning a highly-evolved “supermind” is the stuff of science fiction.

University of Warwick psychology researcher Thomas Hills and Ralph Hertwig of the University of Basel looked at a range of studies, including research into the use of drugs like Ritalan which help with attention, studies of people with autism as well as a study of the Ashkenazi Jewish population.

For instance, among individuals with enhanced cognitive abilities- such as savants, people with photographic memories, and even genetically segregated populations of individuals with above average IQ, these individuals often suffer from related disorders, such as autism, debilitating synaesthesia and neural disorders linked with enhanced brain growth.

Similarly, drugs like Ritalan only help people with lower attention spans whereas people who don’t have trouble focusing can actually perform worse when they take attention-enhancing drugs.

Dr Hills said: “These kinds of studies suggest there is an upper limit to how much people can or should improve their mental functions like attention, memory or intelligence.

“Take a complex task like driving, where the mind needs to be dynamically focused, attending to the right things such as the road ahead and other road users – which are changing all the time.

“If you enhance your ability to focus too much, and end up over-focusing on specific details, like the driver trying to hide in your blind spot, then you may fail to see another driver suddenly veering into your lane from the other direction.

“Or if you drink coffee to make yourself more alert, the trade-off is that it is likely to increase your anxiety levels and lose your fine motor control. There are always trade-offs.

“In other words, there is a ‘sweet spot’ in terms of enhancing our mental abilities – if you go beyond that spot – just like in the fairy-tales – you have to pay the price.”

The research, entitled ‘Why Aren’t We Smarter Already: Evolutionary Trade-Offs and Cognitive Enhancements,’ is published in Current Directions in Psychological Science, a journal of the Association for Psychological Science.