We find different pitches attractive because of the body size they signal—and a touch of breathiness is crucial to take the edge off a man’s deep voice. Image via Flickr user linda

Who you’re physically attracted to might seem like a frivolous, random preference. In recent years, though, science has told us that our seemingly arbitrary tastes often reflect unconscious choices that are based upon very relevant biological traits.

In general, we find symmetric faces more attractive, likely because they reflect a healthy underlying genome. Women typically prefer men with more distinctively masculine facial features because they indicate high testosterone levels and physical strength, while men prefer women with exaggerated youthful features, possibly because of the evolutionary advantages a male gets when coupling with a younger mate.

Despite all this research into our visual appearances, though, scientists have done relatively little digging into our auditory preferences when it comes to sexual attraction. Why do we find certain peoples’ voices attractive–and why do we sometimes find other types of voices such a turn-off? Specifically, why do women generally prefer men with deep voices, and men prefer women with higher ones?

At least according to a paper published today in PLOS ONE, the explanation is relatively simple: It’s all about body size. Researchers from University College London found that, at least among a sample of 32 participants, high-pitched female voices females were found to be attractive because they indicated the speaker had a small body. Deep male voices, on the other hand, were judged as more attractive because they conveyed that the speaker had a large frame—but were found to be most attractive when tempered by a touch of “breathiness,” suggesting the speaker had a low level of aggression despite his large size.

The group, led by Yi Xu, figured this out by playing recordings of digitally manipulated voices to the participants. The males in the study heard a computer-generated female voice saying phrases such as “I owe you a yo-yo” in which the voice was manipulated with a number of digital alterations in terms of pitch, formant (the particular peaks and valleys in a sound’s frequency spectrum) and other qualities.

The specific manipulations either conveyed a smaller body size or a larger one, based upon previous research that matched various voice qualities with different body sizes in humans. When asked to rate the voice’s attractiveness on a 1 to 5 scale, the men preferred the voices that suggested a smaller female. Past a certain point, though, higher voices were judged as no more attractive that slightly deeper ones. Listen to the most and least attractive (both, admittedly creepy) voices below:

The female participants’ voice preferences were similar, but slightly more nuanced. On the whole, they preferred deeper voices, which signaled a large body size, but another trait was also crucial: “breathiness.” The researchers hypothesized that this breathiness effectively takes the edge off a voice, making a man with a presumed large frame seem less aggressive and angry. They also polled the participants on whether they thought the simulated voices sounded angry or happy, and the breathy deep males voices were generally perceived as much happier and less angry than the less breathy (i.e. “pressed”) deep ones. Listen to the most and least attractive male voices below:

Beyond explaining the popularity of Barry White, the researchers say these findings correspond to much of what we know about voice preferences in the rest of the animal kingdom. Birds and other mammals, it turns out, have long been known to advertise their physical characteristics via the sound qualities in their mating calls.

All this points to an obvious question, though: Why would males prefer smaller females, and females prefer larger males in the first place? The researchers don’t attempt to address this question, but this duality reflects the sexual dimorphism present in most animal species. These differences generally result from sexual selection giving incentive to different mating strategies—so in this case, our voice preferences suggest that women benefit, in evolutionary terms, by mating with larger, but less aggressive men, while males benefit from mating with smaller females.

As the same time, what we commonly consider attractive varies dramatically over time and location—for example, dozens of prehistoric “Venus figurines,” discovered all over the world, portray extremely voluptuous female figures. So, if we tested the preferences of all humans throughout history, we might find a less obvious trend. This preference for small-voiced females and big-voiced males, then, might simply be an artifact of our contemporary cultural concepts of “attractiveness,” rather than a deep-seated evolutionary choice after all.

Brain scans show that the neurological patterns linked with pangs of empathy for humans also occur when we see a robot like WALL-E treated harshly. Image via Flickr user Rob Boudon

If, while watching WALL-E, your heart broke just a little bit when you saw the title character desperately travel across outer space in search of true love, it doesn’t mean you’re crazy. Sure, WALL-E is a robot. But its cute, anthropomorphized look and all too human desire to end its loneliness made us subconsciously forget that it is not human.

The ability to forget that key point wasn’t just a matter of clever storytelling. New research shows that, at least in a small sample of people tested, the same neural patterns that occur when we feel empathy for a human onscreen are present in our brains when we see a robot onscreen.

A robot is shaken and beat up during the videos viewed as part of the experiment. Image via Rosenthal-von der Pütten et al

A group of researchers from the University of Duisburg Essen in Germany used fMRI (functional magnetic resonance imaging) to come to the finding, tracking blood flow in the brains of 14 study participants when they were shown videos of humans, robots and inanimate objects being treated either affectionately or harshly. The researchers, who will present their findings at the June International Communication Association conference in London, found that when participants were shown videos of a robot (a product called Pleo, which resembles a dinosaur) petted, tickled and fed, areas in their limbic structures—a region of the brain believed to be involved in emotional responses—activated. When they were shown videos of a human getting a massage, the same sorts of neural activity occurred.

The same pattern also occurred when the participants were shown videos of the robots and humans being treated harshly—shaken, dropped or suffocated with a plastic bag—but with a twist. Interestingly, their fMRI results showed levels of limbic activity much greater when they saw humans treated poorly than when they saw the robots. This correlated with the responses on surveys that the participants took after watching the videos, on which they reported some empathy for the robots, but more for the humans.

The results suggest that the reason we feel empathy for robots like WALL-E is that, when we see them treated a certain manner, it triggers the same sort of neural activity as seeing a human treated that way. In a sense, our mind interprets the robot to be human-like in a way that it doesn’t for, say, a rock. On the other hand, one possible explanation for why, despite this pattern, they still arouse less empathy than humans when being treated harshly is that we interpret them as something slightly less than human—something more like a pet.

Of course, this explanation comes with an important caveat: correlation vs. causation. We don’t know for sure that these neurological patterns cause empathy, per se, just that they reliably occur at the same time. (Further, we can’t say for sure that this effect is unique to robots—stuffed animals and dolls might engender the same feelings of empathy.)

Even if the patterns only correlate with empathy, though, they could be an effective objective measure of how much empathy people feel when observing various types of robots—and research into that area has practical implications that go far beyond Hollywood. One of the main areas, the scientists say, is in the engineering of robots that engage with humans on a frequent and long-term basis.

“One goal of current robotics research is to develop robotic companions that establish a long-term relationship with a human user, because robot companions can be useful and beneficial tools. They could assist elderly people in daily tasks and enable them to live longer autonomously in their homes, help disabled people in their environments, or keep patients engaged during the rehabilitation process,” Astrid Rosenthal-von der Pütten, the study’s lead author, said in a press statement. “A common problem is that a new technology is exciting at the beginning, but this effect wears off especially when it comes to tasks like boring and repetitive exercise in rehabilitation. The development and implementation of uniquely humanlike abilities in robots like theory of mind, emotion and empathy is considered to have the potential to solve this dilemma.”

In one previous long-term study, two out of six elderly participants appeared to develop emotional attachments with a companion robot—giving it a name, speaking to it and at times even smiling at it—while the other four did not. Further exploring our empathy for robots and figuring out just which of their characteristics (whether physical, such as having a human-like face, or behavioral, such as smiling or walking on two legs) lead more people to feel for them could help engineers design robotic devices that elicit more empathy over the long-term—and devices that people can readily connect with on an emotional level might make more effective rehab coaches and home companions over the long-term.

A learning algorithm, coupled with MRI readings, was able to predict the images seen by dreamers with a 60 percent accuracy. Image via Wikimedia Commons/Mark Sebastian

In today’s science-so-weird-it-absolutely-must-be-science-fiction contest, we have a clear winner: a new study in which a team of scientists use an MRI machine, a computer model and thousands of images from the internet to figure out what people see as they dream.

Unbelievable as it sounds, researchers from Kyoto, Japan, say that they’ve built something of a dream-reading machine, which learned enough about the neurological patterns of three research participants to predict their sleeptime visualizations with 60 percent accuracy. The study, published today in Science is believed to be the first case in which objective data has been culled about the contents of a dream.

The seemingly extraordinary idea is built from a straightforward concept: that our brains follow predictable patterns as they react to different kinds of visual stimuli, and over time, a learning algorithm can figure out how to correlate each of these patterns with different classes of visualizations. A 2005 study by one of the researchers accomplished this in a much more primitive way—while subjects were awake—with a learning program correctly using functional MRI readings (fMRI indicates blood flow to various parts of the brain) to determine in which direction a subject was looking.

This study followed the same principle but took it in a much more ambitious direction, seeking to match actual images—not just visual directions—with fMRI readings, and do it while the subjects were asleep.

The research was done on three participants, each of whom took turns sleeping in a MRI scanner for a number of 3-hour-blocks over the course of 10 days. The participants were also wired with an electroencephalography (EEG) machine, which tracks the overall level of electrical activity in the brain and was used to indicate what stage of sleep they were in.

The deepest, longest dreams occur during REM sleep, which typically begins after a few hours of sleeping. But quick, sporadic hallucinations also occur during stage 1 of non-REM sleep, which starts a few minutes after you drift off, and the researchers sought to track the visualizations during this stage.

As the fMRI monitored blood flow to different parts of the subjects’ brains, they drifted off to sleep; then, once the scientists noticed that they’d had entered stage 1, they woke them up and asked them to describe what they were previously seeing while dreaming. They repeated this process nearly 200 times for each of the participants.

Afterward, they recorded the 20 most common classes of items seen by each participant (“building,” “person” or “letter,” for example) and searched for photos on the Web that roughly matched the objects. They showed these images to the participants while they were awake, also in the MRI scanner, then compared the readings to the MRI readouts from when the people had seen the same objects in their dreams. This allowed them to isolate the particular brain activity patterns truly associated with seeing a given object from unrelated patterns that simply correlated with being asleep.

They fed all this data—the 20 most common types of objects that each participant had seen in their dreams, as represented by thousands of images from the Web, along with the participants’ brain activity (from the MRI readouts) that occurred as a result of seeing them—into a learning algorithm, capable of improving and refining its model based on the data. When they invited the three sleepers back into the MRI to test the newly refined algorithm, it generated videos like the one below, producing groups of related images (taken from thousands on the web) and selecting which of the 20 groups of items (the words at bottom) it thought were most likely the person was seeing, based on his or her MRI readings:

When they woke the subjects up this time and asked them to describe their dreams, it turned out that the machine’s predictions were better than chance, although by no means perfect. The researchers picked two classes of items—one the dreamer had reported seeing, and one he or she hadn’t—and checked, of the times the algorithm had reported just one of them, how often it predicted the correct one.

The algorithm got it right 60 percent of the time, a proportion the researchers say can’t be explained by chance. In particular, it was better at distinguishing visualizations from different categories than different images from the same category—that is, it had a better chance of telling whether a dreamer was seeing a person or a scene, but was less accurate at guessing whether a particular scene was a building or a street.

Although it’s only capable of relatively crude predictions, the system demonstrates something surprising: Our dreams might seem like subjective, private experiences, but they produce objective, consistent pieces of data that can be analyzed by others. The researchers say this work could be an initial foray into scientific dream analysis, eventually allowing more sophisticated dream interpretation during deeper stages of sleep.

Being socially isolated increases your chance of death, but not simply because you’re feeling lonely. Image via Flickr user eflon

One of the most unprecedented trends of modern society is the number of people who choose to live alone. As sociologist Eric Klinenberg observed in his 2012 book Going Solo, living alone was virtually unheard of in most world cultures throughout history prior to the 20th century, but an estimated 32.7 million people now live alone in the United States, accounting for about 28 percent of the country’s households today, compared with 17 percent in 1970.

The medical and mental effects of this shift are complex. As Klinenberg notes, many people who live alone still remain highly social and connected with friends and family, so living alone doesn’t necessarily mean that a person is isolated.

But what of those who live alone and are socially isolated? In a study published today in the Proceedings of the National Academy of Sciences, a group of researchers from University College London attempted to explore the health consequences of those who are isolated from others, and found that limited contact with others increases a person’s overall risk of death over time.

The group, led by Andrew Steptoe, examined data on the 6,500 older adults (aged 52 and up) who took part in the English Longitudinal Study of Ageing in 2004, and monitored which participants survived up until last March. The researchers specifically looked at the association between mortality (overall risk of death) and a pair of conditions: social isolation (as indicated by a lack of contact with others) and loneliness (as reflected by participants’ answers on a survey).

In total, 14.1 percent of the people who’d participated in the survey had died in the 8 years after the study was administered, but those who were classified as socially isolated had died at considerably higher rates. Of the most socially isolated respondents, 21.9 percent did not survive to March 2012, as compared with 12.3 percent of the least isolated. Even after the participants’ baseline health and demographic factors were taken into account, being socially isolated still correlated to an increase in their mortality.

Interestingly, though, defining oneself as lonely—via the answers about one’s emotions and psychological state on the survey—did not have the same effect. Those who were lonely did have overall higher mortality, but this was because on average, they were older and had poorer baseline health conditions at the start. When the researchers controlled for baseline health and age, the mortality gap between the lonely and the non-lonely largely vanished.

This indicates that the real danger of living alone is not feeling lonely per se, but having reduced contact with others. One possibility is that an older person who seldom sees friends and family is less likely to get the help they need in managing various ailments, and is probably also less likely to be encouraged to go see a doctor when new health problems pop up. The researchers speculate that living alone might even cause people to have poorer health habits, such as smoking, eating an unhealthy diet and getting less physical activity.

This jibes with previous work by other researchers, such as the fact that living alone with a serious cardiovascular problem makes you more likely to die, and a 2011 Finnish finding that living on your own increases your risk of mortality from an alcohol-related death. Being around others, it seems, helps us ensure that we take better care of ourselves—so if you’re planning on joining the many who have opted to live solo, you’re best off making sure you maintain frequent contact with friends and family.

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Psychologist B.F. Skinner taught these pigeons to play ping-pong in 1950. Photo via Psychology Pictures

B.F Skinner, a leading 20th century psychologist who hypothesized that behavior was caused only by external factors, not by thoughts or emotions, was a controversial figure in a field that tends to attract controversial figures. In a realm of science that has given us Sigmund Freud, Carl Jung and Jean Piaget, Skinner stands out by sheer quirkiness. After all, he is the scientist who trained rats to pull levers and push buttons and taught pigeons to read and play ping-pong.

Besides Freud, Skinner is arguably the most famous psychologist of the 20th century. Today, his work is basic study in introductory psychology classes across the country. But what drives a man to teach his children’s cats to play piano and instruct his beagle on how to play hide and seek? Last year, Norwegian researchers dove into his past to figure it out. The team combed through biographies, archival material and interviews with those who knew him, then tested Skinner on a common personality scale.

They found Skinner, who would be 109 years old today, was highly conscientious, extroverted and somewhat neurotic—a trait shared by as many as 45 percent of leading scientists. The analysis revealed him to be a tireless worker, one who introduced a new approach to behavioral science by building on the theories of Ivan Pavlov and John Watson.

Skinner wasn’t interested in understanding the human mind and its mental processes—his field of study, known as behaviorism, was primarily concerned with observable actions and how they arose from environmental factors. He believed that our actions are shaped by our experience of reward and punishment, an approach that he called operant conditioning. The term “operant” refers to an animal or person “operating” on their environment to affect change while learning a new behavior.

B.F. Skinner at the Harvard psychology department, circa 1950. Photo via Wikimedia

Operant conditioning breaks down a task into increments. If you want to teach a pigeon to turn in a circle to the left, you give it a reward for any small movement it makes in that direction. Soon, the pigeon catches onto this and makes larger movements to the left, which garner more rewards, until the bird completes the full circle. Skinner believed that this type of learning even relates to language and the way we learn to speak. Children are rewarded, through their parents’ verbal encouragement and affection, for making a sound that resembles a certain word until they can actually say that word.

Skinner’s approach introduced a new term into the literature: reinforcement. Behavior that is reinforced, like a mother excitedly drawing out the sounds of “mama” as a baby coos, tends to be repeated, and behavior that’s not reinforced tends to weaken and die out. “Positive” refers to the practice of encouraging a behavior by adding to it, such as rewarding a dog with a treat, and “negative” refers to encouraging a behavior by taking something away. For example, when a driver absentmindedly continues to sit in front of a green light, the driver waiting behind them honks his car horn. The first person is reinforced for moving when the honking stops. The phenomenon of reinforcement extends beyond babies and pigeons: we’re rewarded for going to work each day with a paycheck every two weeks, and likely wouldn’t step inside the office once they were taken away.

Today, the spotlight has shifted from such behavior analysis to cognitive theories, but some of Skinner’s contributions continue to hold water, from teaching dogs to roll over to convincing kids to clean their rooms. Here are a few:

1. The Skinner box. To show how reinforcement works in a controlled environment, Skinner placed a hungry rat into a box that contained a lever. As the rat scurried around inside the box, it would accidentally press the lever, causing a food pellet to drop into the box. After several such runs, the rat quickly learned that upon entering the box, running straight toward the lever and pressing down meant receiving a tasty snack. The rat learned how to use a lever to its benefit in an unpleasant situation too: in another box that administered small electric shocks, pressing the lever caused the unpleasant zapping to stop.

2. Project Pigeon. During World War II, the military invested Skinner’s project to train pigeons to guide missiles through the skies. The psychologist used a device that emitted a clicking noise to train pigeons to peck at a small, moving point underneath a glass screen. Skinner posited that the birds, situated in front of a screen inside of a missile, would see enemy torpedoes as specks on the glass, and rapidly begin pecking at it. Their movements would then be used to steer the missile toward the enemy: Pecks at the center of the screen would direct the rocket to fly straight, while off-center pecks would cause it to tilt and change course. Skinner managed to teach one bird to peck at a spot more than 10,000 times in 45 minutes, but the prospect of pigeon-guided missiles, along with adequate funding, eventually lost luster.

3. The Air-Crib. Skinner tried to mechanize childcare through the use of this “baby box,” which maintained the temperature of a child’s environment. Humorously known as an “heir conditioner,” the crib was completely humidity- and temperate-controlled, a feature Skinner believed would keep his second daughter from getting cold at night and crying. A fan pushed air from the outside through a linen-like surface, adjusting the temperature throughout the night. The air-crib failed commercially, and although his daughter only slept inside at night, many of Skinner’s critics believed it was a cruel and experimental way to raise a child.

4. The teaching box. Skinner believed using his teaching machine to break down material bit by bit, offering rewards along the way for correct responses, could serve almost like a private tutor for students.  Material was presented in sequence, and the machine provided hints and suggestions until students verbally explained a response to a problem (Skinner didn’t believe in multiple choice answers). The device wouldn’t allow students to move on in a lesson until they understood the material, and when students got any part of it right, the machine would spit out positive feedback until they reached the solution. The teaching box didn’t stick in a school setting, but many computer-based self-instruction programs today use the same idea.

5. The Verbal Summator. An auditory version of the Rorschach inkblot test, this tool allowed participants to project subconscious thoughts through sound. Skinner quickly abandoned this endeavor as personality assessment didn’t interest him, but the technology spawned several other types of auditory perception tests.

An intriguing new study suggests that infants dislike those who are different from themselves. Image via Flickr user paparutzi

In one of the fastest-growing areas in psychology, researchers are gaining insight into the mental processes of subjects that are barely able to communicate: babies. In recent years, innovative and playful experimental setups have suggested that infants as young as six months old have a sense of morality and fairness, and that 18-month-olds are capable of altruistically helping others.

Some of this research, though, has also shed light on babies’ dark side. A new study published in Psychological Science suggests that 9- to 14-month-olds exhibit a particularly unwelcome trait—in watching a puppet show, at least, they seem to prefer their own kind, and support puppets that pick on those who are different from them.

Because babies can’t communicate verbally, J. Kiley Hamlin of the University of British Columbia has pioneered the use of puppet shows to probe their psychology and better understand how they see the world. In this study, her research team put on an show in which 52 infant participants were led to identify themselves as similar to one of the characters in the show and different from the other.

To accomplish this, the researchers started off by asking the infants to pick a food, either graham crackers or green beans (a little surprisingly, a full 42 percent chose the vegetables). Then, the infants were shown a pair of rabbit puppets, one who liked graham crackers and one who liked green beans:

Once they’d solidly demonstrated each rabbit’s choice, one of them—either the one with the same preference as the infant observer, or the one with an opposite preference—would be randomly chosen to encounter a pair of new characters: one dog, termed a “helper,” and another, called a “harmer.” As the rabbit played with a ball and dropped it, the nice “helper” dog threw it back, but the mean “harmer” dog (below) held onto the ball:

After both of the scenes were over, both dogs were presented to the infant, and the particular dog that the baby first reached for was interpreted as the character it preferred.

The results were a bit startling: When the infants had watched a play involving a rabbit with a food choice that matched theirs, 83 percent preferred the “helper” dog. When they’d watched a play with a rabbit who liked a different food, 88 percent chose the “harmer” dog. This held true regardless of the babies’ original food choices—the only thing that mattered was whether the rabbit’s identity, it terms of food choice, matched their own.

To further parse the motivations underlying the infants’ choices, the researchers conducted a similar experiment that involved a neutral dog that neither help nor harmed the rabbit. In this part of the study, the older infants’ preferences revealed that when watching rabbits who had different favorite foods than them, they not only liked “harmer” dogs more than neutral dogs, but strongly preferred even neutral dogs when compared to “helpers” (this was true among the 14-month-olds, but not the 9-month-olds). In other words, it seemed that they not only wanted to see the rabbit treated poorly, but also would rather see it treated neutrally than get some help.

Of course, when designing experiments for subjects that can’t use words to communicate, the simplest of variables could potentially throw off the results. It’s unclear, for example, if the researchers alternated which side the “helper” and “harmer” puppets appeared on, so the babies could have been influenced by their emerging sense of handedness. In the past, critics of such puppet show experiments have also charged that a baby merely reaching for one puppet or another might be an impulsive reflex, rather than reflecting an underlying moral judgement.

What’s clear, though, is that this experiment demonstrated a consistent reflex across the babies tested. While extrapolating this to mean that the babies are racist or bigoted is probably a step too far—for one, they were merely considering individual puppets, not groups of puppets with similar characteristics—it does raise interesting questions about the origins of xenophobia in an individual’s lifetime.

What can brain scans reveal about a person’s political beliefs? Photo by Roger Ressmeyer/CORBIS

If you want to know people’s politics, tradition said to study their parents. In fact, the party affiliation of someone’s parents can predict the child’s political leanings about around 70 percent of the time.

But new research, published yesterday in the journal PLOS ONE, suggests what mom and dad think isn’t the endgame when it comes to shaping a person’s political identity. Ideological differences between partisans may reflect distinct neural processes, and they can predict who’s right and who’s left of center with 82.9 percent accuracy, outperforming the “your parents pick your party” model. It also out-predicts another neural model based on differences in brain structure, which distinguishes liberals from conservatives with 71.6 percent accuracy.

The study matched publicly available party registration records with the names of 82 American participants whose risk-taking behavior during a gambling experiment was monitored by brain scans. The researchers found that liberals and conservatives don’t differ in the risks they do or don’t take, but their brain activity does vary while they’re making decisions.

The idea that the brains of Democrats and Republicans may be hard-wired to their beliefs is not new. Previous research has shown that during MRI scans, areas linked to broad social connectedness, which involves friends and the world at large, light up in Democrats’ brains. Republicans, on the other hand, show more neural activity in parts of the brain associated with tight social connectedness, which focuses on family and country.

Other scans have shown that brain regions associated with risk and uncertainty, such as the fear-processing amygdala, differ in structure in liberals and conservatives. And different architecture means different behavior. Liberals tend to seek out novelty and uncertainty, while conservatives exhibit strong changes in attitude to threatening situations. The former are more willing to accept risk, while the latter tends to have more intense physical reactions to threatening stimuli.

Building on this, the new research shows that Democrats exhibited significantly greater activity in the left insula, a region associated with social and self-awareness, during the task. Republicans, however, showed significantly greater activity in the right amygdala, a region involved in our fight-or flight response system.

“If you went to Vegas, you won’t be able to tell who’s a Democrat or who’s a Republican, but the fact that being a Republican changes how your brain processes risk and gambling is really fascinating,” says lead researcher Darren Schreiber, a University of Exeter professor who’s currently teaching at Central European University in Budapest. “It suggests that politics alters our worldview and alters the way our brains process.”

Politics isn’t the first to cause structural changes in the brain. More than a decade ago, researchers used brain scans to show that London cab drivers’ gray matter grew larger to help them store a mental map of the city. There more time they spent on the road, the bigger their hippocampi, an area associated with navigation, became.

This implies that despite the political leanings seen through our brains, how we vote—and thus the cause of our political affiliations—may not be set in stone, Schreiber says.

“If we believe that we’re hardwired for our political views, then it’s really easy for me to discount in you in a conversation. ‘Oh, you’re just a conservative because you have a red brain,’ or ‘Oh, you’re a liberal because you have a blue brain,’” Schreiber explains. “But that’s just not the case. The brain changes. The brain is dynamic.”

A subject uses a helmet and gloves in the real world to enter a virtual world. Photo via Flickr user caseorganic

Action-centric video games have gotten a bad rap for their often violent content. Previous research says the brutal material can leak into real-world behavior, producing more aggression and triggering physiological changes in children’s brains. But what about virtual reality situations that put players in rescue-mode without the gore and pillaging?

What happens in these types of fantasy worlds also translates into real-life behavior, but in a different way: People who are given superpowers meant to save someone in virtual reality are more helpful outside of it.

This finding, reached Robin Rosenberg and colleagues from Stanford University’s Virtual Human Interaction Lab and published yesterday in a PLOS ONE study, relies on the illusion that what happens in virtual reality is real. Participants viewed the world through a head-mounted display, a helmet that provides three-dimensional stereoscopic views of a high-resolution rendered environment. An orientation sensor on the helmet tracked participants’ physical head movements and updated their rendered first-person perspective. To enhance the seeming reality of the the experience, virtual sound was added to match the movement of objects and the vibration associated with action.

In the study, each participant was placed separately in a virtual environment and either given the power of flight, a la Superman, or was a passenger in a helicopter. They were then assigned to one of two tasks. The first involved searching through a virtual city for a young, lost diabetic child in need of life-saving insulin, which they were told they held in a vial in their pocket. After three minutes of searching either via  human flight or by helicopter, the child appeared, and an end sequence commenced showing its life had been saved. The second involved touring the virtual city, which was designed to be foggy and devoid of cars and people. The city in both circumstances had been evacuated due to an earthquake, participants were told.

After the virtual experience, the experimenter assisting participants “accidentally” knocked over a cup of pens, allowing the participants the opportunity to help pick them up. The researchers found that regardless of the task, those who used superpowers to fly through the fantasy world were quicker to help pick up the pens compared to those who rode in the virtual helicopter. These participants also picked up more pens than their helicopter-riding counterparts. Six participants out of 60 (30 males and 30 females) didn’t help at all–all six had cruised through the fantasy world in a helicopter.

Credit: Flickr user Xurble

How can a simulation trigger such prosocial behavior? The researchers suggest that embodying a superhuman quality in virtual reality primes people to think like superheros, such as Superman. Researchers made no mention of the word “superhero” or the prefix “super” at any point during the experiment. But by simply possessing a superhuman ability, participants seemed to tap into what they know about the characters that have them—that they use their power for the greater good rather than personal gain. Researchers believe cognitive channels linking “super” activity and its related stereotypes to heroism and helping behavior may have opened up, influencing participants’ decision to help.

And it doesn’t seem difficult for people to internalize what they see happening to their avatars (their computer-rendered, 3D selves) in virtual reality. For instance, people walking on top of a virtual log to cross a rendered chasm exhibit increased levels of stress measured by skin conductance. They know they’re not actually balancing atop a pit, about to fall, yet they experience multiple psychological symptoms associated with that fear.

Virtual reality’s penchant for inducing behavioral changes has been studied before, and the resulting good behavior moves beyond just picking up pens. A 2011 study found participants in a weight-loss program involving traditional gym sessions lost similar amounts of weight and body fat as those whose workouts were delivered online in a 3D virtual world.

In another study published in 2011, also conducted by the Virtual Human Interaction Lab at Stanford University, researchers found that virtual behavior affected people’s feelings about helping the environment. Participants were forced to saw down virtual trees using a joystick called a haptic device, which vibrated in their hands to simulate the real feeling of cutting through wood. Following the task, participants believed more strongly that they could personally improve environmental conditions than those who simply read a detailed description of deforestation. They also used less paper when cleaning up an “accidental” water spill in the physical world.

Researchers in the recent study suggest there may be more to the resulting prosocial effects than just priming effects. Pretending to possess a superpower may shift a person’s self-concept so he or she sees himself or herself as “someone who helps,” an identify change that could have lasting effects on behavior.

Image via Flickr user .reid

A new study by a team of researchers from the University of Montreal seems to scientifically support what many have long suspected: For lesbian, gay and bisexual individuals, coming out provides a tangible benefit in terms of both biological and mental health.

The findings, published today in the journal Psychosomatic Medicine (the paper is not yet linked online), are the result of a study originally intended to see if, overall, lesbian, gay and bisexual individuals had higher levels of cortisol—a hormone whose presence in the body reflects chronic stress—as well as a greater chance of self-reported negative psychiatric symptoms such as anxiety and depression. The researchers’ original hypothesis was that people in this group would be more likely to suffer from these symptoms.

Their main findings were something of a surprise—among their sample of 87 participants, gay and bisexual men actually had a slightly lesser chance of depression and anxiety, along with lower stress levels (as indicated by cortisol and 20 other biomarkers) than heterosexual men.

Perhaps most significant, though, was the secondary finding that they hadn’t even been searching for: In their study, lesbian, gay and bisexual individuals all tended to have lower stress levels and a smaller chance of depressive symptoms if they’d come out to friends and family than those who’d kept their sexual orientation a secret. “Coming out,” the authors write, “may no longer be a matter of popular debate, but of public health.”

The research team, in a study led by Robert-Paul Juster, came to the conclusion after inviting Montreal residents of diverse sexual orientations to participate in a series of health assessments. The participants—all around 25 years old—filled out surveys about their mental health and provided saliva, blood and urine samples so that the researchers could examine a range of chemical biomarkers that reflect chronic stress. These biomarkers–cortisol, along with insulin, sugar, cholesterol, adrenaline and inflammation levels–together are known as an allostatic load.

They found that, within the group of 46 lesbian, gay or bisexual participants, the 31 individuals who’d come out had noticeably lower cortisol levels than the 15 who hadn’t disclosed their orientation to others. Additionally, survey answers indicated that the first group had fewer symptoms of depression or anxiety than the other group.

Admittedly, the study’s limited sample size means that these results can’t be interpreted as definitive, and further study is needed to confirm that they hold true on a widespread level. But the results are still fascinating, and could  have important medical implications. A higher level of stress, measured in terms of allostatic load, has been linked to everything from cardiovascular disease to an increased overall risk of death.

If coming out provides a means of reducing the risks of these health-related ailments, the researchers write, it provides yet another reason why, as Juster stated, “internationally, societies must endeavor to facilitate self-acceptance among LGBs [lesbian, gay and bisexual individuals] by promoting tolerance, progressing policy and dispelling stigma.”