Here’s a good idea for the next presidential candidate debate: They can insult each other about their ignorance of statistics.
Actually, it’s a pertinent topic for political office seekers, as public opinion polls use statistical methods to measure the electorate’s support (or lack thereof) for a particular candidate. But such polls are notoriously unreliable, as Hillary Clinton found out in Michigan.
It probably wouldn’t be a very informative debate, of course — just imagine how Donald Trump would respond to a question asking what he thought about P values. Sadly, though, he and the other candidates might actually understand P values just about as well as many practicing scientists — which is to say, not very well at all. In recent years criticism about P values — statistical measures widely used to analyze experimental data in most scientific disciplines — has finally reverberated loudly enough for the scientific community to listen. A watershed acknowledgment of P value problems appeared this week when the American Statistical Association issued a statement warning the rest of the world about the limitations of P values and their widespread misuse.
“While the p-value can be a useful statistical measure, it is commonly misused and misinterpreted,” the statistical association report stated. “This has led to some scientific journals discouraging the use of p-values, and some scientists and statisticians recommending their abandonment.”
In light of these issues, the association convened a group of experts to formulate a document listing six “principles” regarding P values for the guidance of “researchers, practitioners and science writers who are not primarily statisticians.” Of those six principles, the most pertinent for people in general (and science journalists in particular) is No. 5: “A p-value, or statistical significance, does not measure the size of an effect or the importance of a result.”
What, then, does it measure? That’s principle No. 1: “… how incompatible the data are with a specified statistical model.” But note well principle No. 2: “P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.” And therefore, always remember principle No. 3: “Scientific conclusions … or policy decisions should not be based only on whether a p-value passes a specific threshold.”
In other words, the common convention of judging a P value less than .05 to be “statistically significant” is not really a proper basis for assigning significance at all. Except that scientific journals still regularly use that criterion for deciding whether a paper gets published. Which in turn drives researchers to finagle their data to get a P value of less than .05. As a result, the scientific process is tarnished and the published scientific literature is often unreliable. As the statistical association statement points out, this situation is far from merely of academic concern.
“The issues touched on here affect not only research, but research funding, journal practices, career advancement, scientific education, public policy, journalism, and law,” the authors point out in the report, published online March 7 in The American Statistician.
Many of the experts who participated in the process wrote commentaries on the document, some stressing that it did not go far enough in condemning P values’ pernicious influences on science.
“Viewed alone, p-values calculated from a set of numbers and assuming a statistical model are of limited value and frequently are meaningless,” wrote biostatistician Donald Berry of MD Anderson Cancer Center in Houston. He cited the serious negative impact that misuse and misinterpretation of P values has had not only on science, but also on society. “Patients with serious diseases have been harmed. Researchers have chased wild geese, finding too often that statistically significant conclusions could not be reproduced. The economic impacts of faulty statistical conclusions are great.”
Echoing Berry’s concerns was Boston University epidemiologist Kenneth Rothman. “It is a safe bet that people have suffered or died because scientists (and editors, regulators, journalists and others) have used significance tests to interpret results,” Rothman wrote. “The correspondence between results that are statistically significant and those that are truly important is far too low to be useful. Consequently, scientists have embraced and even avidly pursued meaningless differences solely because they are statistically significant, and have ignored important effects because they failed to pass the screen of statistical significance.”
Stanford University epidemiologist John Ioannidis compared the scientific community’s attachment to P values with drug addiction, fueled by the institutional rewards that accompany the publication process.
“Misleading use of P-values is so easy and automated that, especially when rewarded with publication and funding, it can become addictive,” Ioannidis commented. “Investigators generating these torrents of P-values should be seen with sympathy as drug addicts in need of rehabilitation that will help them live a better, more meaningful scientific life in the future.”
Although a handful of P value defenders can still be found among the participants in this discussion, it should be clear by now that P values, as currently used in science, do more harm than good. They may be valid and useful under certain specific circumstances, but those circumstances are rarely relevant in most experimental contexts. As Berry notes, statisticians can correctly define P values in a technical sense, but “most statisticians do not really understand the issues in applied settings.”
In its statement, the statistical association goes a long way toward validating the concerns about P values that have been expressed for decades by many critical observers. This validation may succeed in initiating change where previous efforts have failed. But that won’t happen without identifying some alternative to the P value system, and while many have been proposed, no candidate has emerged as an acceptable nominee for a majority of the scientific world’s electorate. So the next debate should not be about P values — it should be about what to replace them with.
Modern-day Melanesians carry a two-pronged genetic legacy of ancient interbreeding that still affects their health and well-being, researchers say.
Unlike people elsewhere in the world, these Pacific islanders possess nuclear DNA that they inherited from two Stone Age hominid populations, say population geneticist Benjamin Vernot, formerly of the University of Washington in Seattle, and his colleagues. At least some of that ancient DNA contains genes involved in important biological functions, the researchers find. Nuclear DNA is passed from both parents to their children. The finding means that ancestors of people now living in the Bismarck Archipelago, a group of islands off Papua New Guinea’s northeastern coast, mated with Neandertals as well as with mysterious Neandertal relatives called Denisovans, the scientists conclude online March 17 in Science.
In support of previous research, the researchers find that non-Africans — including Melanesians — have inherited an average of between 1.5 and 4 percent of their DNA from Neandertals. But only Melanesians display substantial Denisovan ancestry, which makes up 1.9 to 3.4 percent of their DNA, the researchers say. (Present-day African populations possess little to no Neandertal or Denisovan DNA.)
The bits of Neandertal and Denisovan DNA carried by Melanesians encompass genes involved in metabolism and immunity, indicating that interbreeding influenced the evolutionary success of ancient humans, Vernot’s group reports.
The new study reconstructs the microscopic landscape of Neandertals’ and Denisovans’ contributions to Melanesians’ DNA “in impressive detail,” says Harvard University paleogeneticist Pontus Skoglund.
Vernot’s team studied DNA from 35 Melanesians at 11 locations in the Bismarck Archipelago. Analyses concentrated on DNA from 27 unrelated individuals. The researchers also looked for evidence of ancient interbreeding in previously acquired genomes of close to 1,500 modern-day individuals from different parts of the world. Denisovan DNA for comparisons came from fragmentary fossils found in a Siberian cave; comparative Neandertal DNA came from a genome previously extracted from a 50,000-year-old woman’s toe bone. Among Melanesians, DNA sequences attributed to Neandertals and Denisovans encompassed several metabolism genes. One of those genes influences a hormone that increases blood glucose levels. Another affects the chemical breakdown of lipids. Other Melanesian genetic sequences acquired through ancient interbreeding either include or adjoin genes that help to marshal the body’s defenses against illness.
These findings follow evidence suggesting that once-useful genes that ancient humans inherited from Neandertals now raise the risk of contracting certain diseases (SN: 3/5/16, p. 18). Vernot’s group reaches no conclusions about good or bad effects of ancient hybrid genes in Melanesians.
No sign of Neandertal or Denisovan DNA appears in areas of Melanesians’ genomes involved in brain development, the scientists say. So brain genetics, for better or worse, apparently evolved along a purely human path.
Denisovans’ evolutionary history remains poorly understood. Previous DNA comparisons suggest that Denisovans must have reached Southeast Asia. Skoglund suspects that’s where the ancestors of Melanesians bred with Denisovans.
Substantial interbreeding of humans with Denisovans probably occurred only once, Vernot and his colleagues suspect. Genetic exchanges of humans with Neandertals took place at least three times, they add. These estimates are derived from comparisons of shared Denisovan and Neandertal DNA sequences among individuals in different parts of the world.
Clownfish and anemones depend on one another. The stinging arms of the anemones provide clownfish with protection against predators. In return, the fish keep the anemone clean and provide nutrients, in the form of poop. Usually, several individual clownfish occupy a single anemone — a large and dominant female, an adult male and several subordinates — all from the same species. But with 28 species of clownfish and 10 species of anemone, there can be a lot of competition for who gets to occupy which anemone.
In the highly diverse waters of the Coral Triangle of Southeast Asia, however, clownfish have figured out how to share, researchers report March 30 in the Proceedings of the Royal Society B. Anemones in these waters are often home to multiple species of clownfish that live together peacefully.
From 2005 to 2014, Emma Camp, of the University of Technology Sydney and colleagues gathered data on clownfish and their anemone homes from 20 locations that had more than one species of clownfish residents. In 981 underwater survey transects, they encountered 1,508 clownfish, 377 of which lived in groups consisting of two or more fish species in a single anemone.
Most of those cohabiting clownfish could be found in the waters of the Coral Triangle, the team found, with the highest levels of species cohabitation occurring off Hoga Island in Indonesia. There, the researchers found 437 clownfish from six species living among 114 anemones of five species. Every anemone was occupied by clownfish, and half had two species of the fish.
In general, “when the number of clownfish species exceeded the number of host anemone species, cohabitation was almost always documented,” the researchers write.
The multiple-species groups divvied up space in an anemone similar to the way that a single-species group does, with subordinate fish sticking to the peripheries. That way, those subordinate fish can avoid fights — and potentially getting kicked off the anemone or even dying. “Living on the periphery of an anemone, despite the higher risk of predation, is a better option than having no host anemone,” the team writes.
These multi-species groups might even be better for both of the clownfish species, since they wouldn’t have to compete so much over mates, and perhaps even less over food, if the species had different diets.
This isn’t the first time that scientists have found cohabitation to be an effective strategy in an area of high biodiversity. This has also been demonstrated with scorpions in the Amazon. But it does show how important it is to conserve species in regions such as this, the researchers say — because losing one species can easily wipe out several more.
NEW YORK — Lip-readers’ minds seem to “hear” the words their eyes see being formed. And the better a person is at lipreading, the more neural activity there is in the brain’s auditory cortex, scientists reported April 4 at the annual meeting of the Cognitive Neuroscience Society.
Earlier studies have found that auditory brain areas are active during lipreading. But most of those studies focused on small bits of language — simple sentences or even single words, said study coauthor Satu Saalasti of Aalto University in Finland. In contrast, Saalasti and colleagues studied lipreading in more natural situations. Twenty-nine people read the silent lips of a person who spoke Finnish for eight minutes in a video. “We can all lip-read to some extent,” Saalasti said, and the participants, who had no lipreading experience, varied widely in their comprehension of the eight-minute story.
In the best lip-readers, activity in the auditory cortex was quite similar to that evoked when the story was read aloud, brain scans revealed. The results suggest that lipreading success depends on a person’s ability to “hear” the words formed by moving lips, Saalasti said.
Bacterium effective when dusted on plants — The successful agent for destroying pesty insects, the microscopic bacterium, Bacillus thuringiensis, is most effective when it is dusted onto tobacco or other plants…. The bacteria are now recommended for use against tobacco budworms and hornworms. From known results …. they look promising as biological control agents. — Science News, April 30, 1966
Update Bacillus thuringiensis, or Bt, is still used to combat agricultural pests. Different strains of the bacterium target different insects; one strain can even kill mosquito larvae in water. Organic farmers dust or spray Bt on crops and consider it a natural insecticide. In conventional farming, Bt DNA is often inserted into a plant’s genome, creating genetically modified crops that make their own pesticide (SN: 2/6/16, p. 22). In 2015, 81 percent of U.S. corn and 84 percent of U.S. upland cotton contained Bt genes.
To rewrite an Alanis Morissette song, the brain has a funny way of waking you up (and putting you to sleep). Isn’t it ionic? Some scientists think so.
Changes in ion concentrations, not nerve cell activity, switch the brain from asleep to awake and back again, researchers report in the April 29 Science. Scientists knew that levels of potassium, calcium and magnesium ions bathing brain cells changed during sleep and wakefulness. But they thought neurons — electrically active cells responsible for most of the brain’s processing power — drove those changes. Instead, the study suggests, neurons aren’t the only sandmen or roosters in the brain. “Neuromodulator” brain chemicals, which pace neuron activity, can bypass neurons altogether to directly wake the brain or lull it to sleep by changing ion concentrations.
Scientists hadn’t found this direct connection between ions and sleep and wake before because they were mostly focused on what neurons were doing, says neuroscientist Maiken Nedergaard, who led the study. She got interested in sleep after her lab at the University of Rochester in New York found a drainage system that washes the brain during sleep (SN: 11/16/13, p. 7).When measuring changes in the fluid between brain cells, Nedergaard and colleagues realized that ion changes followed predictable patterns: Potassium ion levels are high when mice (and presumably people) are awake, and drop during sleep. Calcium and magnesium ions follow the opposite pattern; they are higher during sleep and lower when mice are awake. In the study, Nedergaard’s group administered a “wake cocktail” of neuromodulator chemicals to mouse brains. Levels of potassium ions floating between brain cells increased rapidly after the treatment, the researchers found. That ion change happened even when the researchers added tetrodotoxin to stop neuron activity. The results suggest that the brain chemicals — norepinephrine, acetylcholine, dopamine, orexin and histamine — directly affect ion levels with no help from neurons. Exactly how the chemicals manage ion levels still isn’t known. Similar changes happen under anesthesia. When awake mice were anesthetized, potassium ion levels in their brains dropped sharply, while levels of calcium and magnesium rose, the researchers found. As mice awoke from anesthesia, potassium ion levels rose quickly. But calcium and magnesium levels took longer to drop. As a result, the mice “are totally confused,” says Nedergaard. “They bump into their cages, they run around and they don’t know what they are doing.”
Those results may help explain why people are groggy after waking up from anesthesia; their ion levels haven’t returned to “awake” levels yet, says Amita Sehgal, a sleep researcher at the University of Pennsylvania School of Medicine.
Learning more about how ions affect wake and sleep may eventually lead to a better understanding of sleep, consciousness and coma, Nedergaard says.
But, says neuroscientist Chiara Cirelli of the University of Wisconsin‒Madison, practical implications of the work, such as improved sleep drugs, are probably far in the future. “How they make use of it will take some time, but just knowing this is certainly very eye-opening.” It would be interesting to find out what happens to ion concentrations during REM sleep, when neurons are as active as they are when a person is awake, she says.
You wouldn’t expect wardrobe classics like leather jackets or denim jeans at an exhibit celebrating fashion at its most forward. But “#techstyle” at the Museum of Fine Arts in Boston features those sartorial mainstays and others, each with a technological twist.
A feast for the eyes, the diversity of pieces is matched by the diversity of artists and approaches. Yet a single theme unites: The fusion of technology and fashion will increasingly influence both. Visitors are introduced to this theme via a room featuring works by prominent designers already known for merging fashion and tech: A digitally printed silk dress by Alexander McQueen hangs next to a fiberglass “airplane dress” by Hussein Chalayan that has flaps that open and shut via remote control. The largest part of the exhibit focuses on how technology is changing design and construction strategies. In addition to clothes made with mainstream techniques like laser-cutting, several 3-D printed garments are on display. These include a kinematic dress made of more than 1,600 interlocking pieces that can be customized to a wearer’s body via a 3-D scan. The dress comes off the printer fully assembled. Other pieces are made with technologies still being developed, such as the laser-welded fabrics from sustainable textile researcher Kate Goldsworthy. The real standouts are in the “Performance” section, which displays attire that uses data from the immediate environment to generate some visible aspect of the garment. These interactive pieces “reveal something to the eye that you wouldn’t see normally, something that science often captures with graphs and charts,” says Pamela Parmal, a curator of the exhibit. For instance, the interactive dress “Incertitudes” is adorned with pins that flex in response to nearby voices, creating waves in the fabric; a dress embedded with thousands of tiny LEDs can display tweeted messages or other illuminated patterns. And there are two leather jackets that, at first glance, look like their innovation is merely a stylish cut. But the jackets are coated in reactive inks that shimmer with iridescent colors in response to the wind and heat generated by heat guns in the display case. (These creations were born after designer and trained chemist Lauren Bowker used the reactive compounds to reveal the aerodynamics of race cars in a wind tunnel in a project for Formula One.)
Visitors seeking in-depth explanations of the science behind the fashions will have to look elsewhere. But “#techstyle” still has something for everyone, whether fashionista or engineer. And while the fashions represented are all cutting edge, the show harks back to an era when clothes were custom-made. Technology might have brought us mass-produced cookie-cutter clothing, but it can also enable clothing tailored to the individual.
Lead contamination in drinking water can change with the seasons. Tracking lead levels in water pipes over several months, researchers discovered three times as much dissolved lead and six times as much undissolved lead in summer than in winter. The finding could help improve water testing, says study coauthor Sheldon Masters, an environmental engineer at Virginia Tech and Corona Environmental Consulting in Philadelphia.
Masters and colleagues analyzed water contamination data collected from pipes in Washington, D.C., and Providence, R.I., and tested the dissolvability of lead in different water conditions. In many, but not all, homes and lab tests, the amount of lead leaching into drinking water rose as water temperature increased.
For pipes in Washington, average wintertime dissolved lead levels were 3.6 parts per billion, compared with 10.8 ppb during summer. Average undissolved lead concentrations varied from 7.6 ppb during winter to 48.4 ppb during summer. Each 1 degree Celsius rise in water temperature boosted dissolved lead levels by about 17 percent and lead particles by about 36 percent, the researchers report online April 14 in Environmental Science & Technology. Washington water temperature varied from about 5° to 30° C. Seasonal variations in lead were smaller than those expected from temperature changes alone, since other factors such as the amount of organic matter in water can also influence lead levels.
Some water systems could meet the regulatory standard of less than 15 ppb in winter while exceeding that threshold during warmer months, the researchers warn. Water testing prioritizes conditions with the highest risk for lead leaching. However, no current guidelines explicitly address seasonal variability. Lead consumption can cause severe health problems including birth defects, anemia and brain damage (SN: 3/19/16, p. 8).
From within the dark confines of the skull, the brain builds its own version of reality. By weaving together expectations and information gleaned from the senses, the brain creates a story about the outside world. For most of us, the brain is a skilled storyteller, but to spin a sensible yarn, it has to fill in some details itself.
“The brain is a guessing machine, trying at each moment of time to guess what is out there,” says computational neuroscientist Peggy Seriès. Guesses just slightly off — like mistaking a smile for a smirk — rarely cause harm. But guessing gone seriously awry may play a part in mental illnesses such as schizophrenia, autism and even anxiety disorders, Seriès and other neuroscientists suspect. They say that a mathematical expression known as Bayes’ theorem — which quantifies how prior expectations can be combined with current evidence — may provide novel insights into pernicious mental problems that have so far defied explanation. Bayes’ theorem “offers a new vocabulary, new tools and a new way to look at things,” says Seriès, of the University of Edinburgh.
Experiments guided by Bayesian math reveal that the guessing process differs in people with some disorders. People with schizophrenia, for instance, can have trouble tying together their expectations with what their senses detect. And people with autism and high anxiety don’t flexibly update their expectations about the world, some lab experiments suggest. That missed step can muddy their decision-making abilities. Given the complexity of mental disorders such as schizophrenia and autism, it is no surprise that many theories of how the brain works have fallen short, says psychiatrist and neuroscientist Rick Adams of University College London. Current explanations for the disorders are often vague and untestable. Against that frustrating backdrop, Adams sees great promise in a strong mathematical theory, one that can be used to make predictions and actually test them.
“It’s really a step up from the old-style cognitive psychology approach, where you had flowcharts with boxes and labels on them with things like ‘attention’ or ‘reading,’ but nobody having any idea about what was going on in [any] box,” Adams says.
Applying math to mental disorders “is a very young field,” he adds, pointing to Computational Psychiatry, which plans to publish its first issue this summer. “You know a field is young when it gets its first journal.”
A mind for math Bayesian reasoning may be new to the mental illness scene, but the math itself has been around for centuries. First described by the Rev. Thomas Bayes in the 18th century, this computational approach truly embraces history: Evidence based on previous experience, known as a “prior,” is essential to arriving at a good answer, Bayes argued. He may have been surprised to see his math meticulously applied to people with mental illness, but the logic holds. To make a solid guess about what’s happening in the world, the brain must not rely just on current input from occasionally unreliable senses. The brain must also use its knowledge about what has happened before. Merging these two streams of information correctly is at the heart of perceiving the world as accurately as possible.
Bayes figured out a way to put numbers to this process. By combining probabilities that come from prior evidence and current observations, Bayes’ formula can be used to calculate an overall estimate of the likelihood that a given suspicion is true. A properly functioning brain seems to do this calculation intuitively, behaving in many cases like a skilled Bayesian statistician, some studies show (SN: 10/8/11, p. 18).
This reckoning requires the brain to give the right amount of weight to prior expectations and current information. Depending on the circumstances, those weights change. When the senses falter, for instance, the brain should lean more heavily on prior expectations. Say the mail carrier comes each day at 4 p.m. On a stormy afternoon when visual cues are bad, we rely less on sight and more on prior knowledge to guess that the late-afternoon noise on the front porch is probably the mail carrier delivering letters. In certain mental illnesses, this flexible balancing act may falter.
People with schizophrenia often suffer from hallucinations and delusions, debilitating symptoms that arise when lines between reality and imagination blur. That confusion can lead to hearing voices that aren’t there and believing things that can’t possibly be true. These departures from reality could arise from differences in how people integrate new evidence with previous beliefs. There’s evidence for such distorted calculations. People with schizophrenia don’t fall for certain visual illusions that trick most people, for instance. When shown a picture of the inside of a hollowed-out face mask, most people’s brains mistakenly convert the image to a face that pops outward off the page. People with schizophrenia, however, are more likely to see the face as it actually is — a concave mask. In that instance, people with schizophrenia give more weight to information that’s coming from their eyes than to their expectation that noses protrude from the rest of the face. To complicate matters, the opposite can be true, too, says neuropsychologist Chris Frith of the Wellcome Trust Centre for Neuroimaging at University College London. “In this case, their prior is too weak, but in other cases, their prior is too strong,” he says.
In a recent study, healthy people and those who recently began experiencing psychosis, a symptom of schizophrenia, were shown confusing shadowy black-and-white images. Participants then saw color versions of the images that were easier to interpret. When shown the black-and-white images again, people with early psychosis were better at identifying the images, suggesting that they used their prior knowledge — the color pictures — to truly “see” the images. For people without psychosis, the color images weren’t as much help. That difference suggests that the way people with schizophrenia balance past knowledge and present observations is distinct from the behavior of people without the disorder. Sometimes the balance tips too far — in either direction.
In a talk at the annual Computational and Systems Neuroscience meeting in February in Salt Lake City, Seriès described the results of a different visual test: A small group of people with schizophrenia had to describe which way a series of dots were moving on a screen. The dots moved in some directions more frequently than others — a statistical feature that let the scientists see how well people could learn to predict the dots’ directions. The 11 people with schizophrenia seemed just as good at learning which way the dots were likely to move as the 10 people without, Seriès said. In this situation, people with schizophrenia seemed able to learn priors just fine.
But when another trick was added, a split between the two groups emerged. Sometimes, the dots were almost impossible to see, and sometimes, there were no dots at all. People with schizophrenia were less likely to claim that they saw dots when the screen was blank. Perhaps they didn’t hallucinate dots because of the medication they were on, Seriès says. In fact, very early results from unmedicated people with schizophrenia suggest that they actually see dots that aren’t there more than healthy volunteers. Preliminary results so far on schizophrenia are sparse and occasionally conflicting, Seriès admits. “It’s the beginning,” she says. “We don’t understand much.”
The research is so early that no straightforward story exists yet. But that’s not unexpected. “If 100 years of schizophrenia research have taught us anything, it’s that there’s not going to be a nice, simple explanation,” Adams says. But using math to describe how people perceive the world may lead to new hunches about how that process goes wrong in mental illnesses, he argues.
“You can instill expectations in subjects in many different ways, and you can control what evidence they see,” Adams says. Bayesian theory “tells you what they should conclude from those prior beliefs and that evidence.” If their conclusions diverge from predictions, scientists can take the next step. Brain scans, for instance, may reveal how the wrong answers arise. With a clear description of these differences, he says, “we might be able to measure people’s cognition in a new way, and diagnose their disorders in a new way.”
Now vs. then The way the brain combines incoming sensory information with existing knowledge may also be different in autism, some researchers argue. In some cases, people with autism might put excess weight on what their senses take in about the world and rely less on their expectations. Old observations fit with this idea. In the 1960s, psychologists had discovered that children with autism were just as good at remembering nonsense sentences (“By is go tree stroke lets”) as meaningful ones (“The fish swims in the pond”). Children without autism struggled to remember the non sequiturs. But the children with autism weren’t thrown by the random string of words, suggesting that their expectations of sentence meaning weren’t as strong as their ability to home in on each word in the series.
Another study supports the notion that sensory information takes priority in people with autism. People with and without autism were asked to judge whether a sight and a sound happened at the same time. They saw a white ring on a screen, and a tone played before, after or at the same time. Adults without autism were influenced by previous trials in which the ring and tone were slightly off. But adults with autism were not swayed by earlier trials, researchers reported in February in Scientific Reports.
This literal perception might get in the way of speech perception, Marco Turi of the University of Pisa in Italy and colleagues suggest. Comprehending speech requires a listener to mentally stitch together sights and sounds that may not arrive at the eyes and ears at the same time. Losing that flexibility could make speech harder to understand.
A different study found that children with autism perceive moving dots more clearly than children without autism (SN Online: 5/5/15). The brains of people with autism seem to prioritize incoming sensory information over expectations about how things ought to work. Elizabeth Pellicano of University College London and David Burr of the University of Western Australia in Perth described the concept in 2012 in an opinion paper in Trends in Cognitive Sciences. Intensely attuned to information streaming in from the senses, people with autism experience the world as “too real,” Pellicano and Perth wrote.
New data, however, caution against a too-simple explanation. In an experiment presented in New York City in April at the annual meeting of the Cognitive Neuroscience Society, 20 adults with and without autism had to quickly hit a certain key on a keyboard when they saw its associated target on a screen. Their job was made easier because the targets came in a certain sequence. All of the participants improved as they learned which keys to expect. But when the sequence changed to a new one, people with autism faltered. This result suggests that they learned prior expectations just fine, but had trouble updating them as conditions changed, said cognitive neuroscientist Owen Parsons of the University of Cambridge. Distorted calculations — and the altered versions of the world they create — may also play a role in depression and anxiety, some researchers think. While suffering from depression, people may hold on to distorted priors — believing that good things are out of reach, for instance. And people with high anxiety can have trouble making good choices in a volatile environment, neuroscientist Sonia Bishop of the University of California, Berkeley and colleagues reported in 2015 in Nature Neuroscience.
In their experiment, people had to choose a shape, which sometimes came with a shock. People with low anxiety quickly learned to avoid the shock, even when the relationship between shape and shock changed. But people with high anxiety performed worse when those relationships changed, the researchers found. “High-anxious individuals didn’t seem able to adjust their learning to handle how volatile or how stable the environment was,” Bishop says. Scientists can’t yet say what causes this difficulty adjusting to a new environment in anxious people and in people with autism. It could be that once some rule is learned (a sequence of computer keys, or the link between a shape and a shock), these two groups struggle to update that prior with newer information.
This rigidity might actually contribute to anxiety in the first place, Bishop speculates. “When something unexpected happens that is bad, you wouldn’t know how to respond,” and that floundering “is likely to be a huge source of anxiety and stress.”
Recalculating “There’s been a lot of frustration with a failure to make progress” on psychiatric disorders, Bishop says. Fitting mathematical theories to the brain may be a way to move forward. Researchers “are very excited about computational psychiatry in general,” she says.
Computational psychiatrist Quentin Huys of the University of Zurich is one of those people. Math can help clarify mental illnesses in a way that existing approaches can’t, he says. In the March issue of Nature Neuroscience, Huys and colleagues argued that math can demystify psychiatric disorders, and that thinking of the brain as a Bayesian number cruncher might lead to a more rigorous understanding of mental illness. Huys says that a computational approach is essential. “We can’t get away without it.” If people with high anxiety perform differently on a perceptual test, then that test could be used to both diagnose people and monitor how well a treatment works, for instance.
Scientists hope that a deeper description of mental illnesses may lead to clearer ways to identify a disorder, chart how well treatments work and even improve therapies. Bishop raises the possibility of developing apps to help people with high anxiety evaluate situations — outsourcing the decision making for people who have trouble. Frith points out that cognitive behavioral therapy could help depressed people recalculate their experiences by putting less weight on negative experiences and perhaps breaking out of cycles of despondence.
Beyond these potential interventions, simply explaining to people how their brains are working might ease distress, Adams says. “If you can give people an explanation that makes sense of some of the experiences they’ve had, that can be a profoundly helpful thing,” he says. “It destigmatizes the experience.”
Genetically engineered crops don’t appear to harm humans or the environment, according to a new report released May 17 by the National Academies of Sciences, Engineering and Medicine.
An extensive analysis of two decades’ worth of evidence dug up no substantial proof that genetically engineered foods were any less safe to eat than those that are conventionally bred. The study’s authors also found no conclusive causal link between the engineered crops and environmental problems. The authors note, though, that it’s not always easy to make definitive conclusions; measuring long-term environmental changes is complicated.
The news comes in the midst of political tumult in the United States over laws to label foods made with GE ingredients. But when it comes to food safety and the environment, the authors conclude, how a plant is made isn’t as important as what is actually created.
“It is the product, not the process, that should be regulated,” the authors write.
