A protein that can switch shapes and accumulate inside brain cells helps fruit flies form and retrieve memories, a new study finds.

Such shape-shifting is the hallmark move of prions — proteins that can alternate between two forms and aggregate under certain conditions. In fruit flies’ brain cells, clumps of the prionlike protein called Orb2 stores long-lasting memories, report scientists from the Stowers Institute for Medical Research in Kansas City, Mo. Figuring out how the brain forms and calls up memories may ultimately help scientists devise ways to restore that process in people with diseases such as Alzheimer’s.
The new finding, described online November 3 in Current Biology, is “absolutely superb,” says neuroscientist Eric Kandel of Columbia University. “It fills in a lot of missing pieces.”

People possess a version of the Orb2 protein called CPEB, a commonality that suggests memory might work in a similar way in people, Kandel says. It’s not yet known whether people rely on the prion to store long-term memories. “We can’t be sure, but it’s very suggestive,” Kandel says.

When neuroscientist Kausik Si and colleagues used a genetic trick to inactivate Orb2 protein, male flies were worse at remembering rejection. These lovesick males continued to woo a nonreceptive female long past when they should have learned that courtship was futile. In different tests, these flies also had trouble remembering that a certain odor was tied to food.
Si and colleagues found a different protein, JJJ2, that helped Orb2 switch shapes, a change that then allows Orb2 to aggregate. When the researchers boosted levels of JJJ2 protein, a situation that led to more Orb2 accumulation, flies had sharper memories. Usually, flies need about six hours of training to learn that an unreceptive female really doesn’t want to mate. But after a boost of JJJ2, flies learned that courtship was futile in only two hours. What’s more, this memory lasted for days, researchers found.
Kandel, whose work has turned up evidence for CPEB holding memories in sea slugs and mice, says that the new study makes the concept that prions can stabilize memories “quite definitive now.”

JJJ2 didn’t lead to supersmart flies that could learn everything quickly, though. The boost only came for memories that would have been formed anyway, Si says. The change “lowered the threshold for memory formation, but it has not created a situation where now all information that comes in is turned into long-term memory,” he says. “It can only [affect] memory when the conditions are right to produce a memory.”

The Orb2 results come from just long-term memory. “There could be other biochemical processes for other types of memory,” such as immune cells’ memories of former threats, Si says. Still, it’s possible that protein accumulation is one of the fundamental ways memory works.

In empty space, quantum particles flit in and out of existence, electromagnetic fields permeate the vacuum, and space itself trembles with gravitational waves. What may seem like nothingness paradoxically teems with activity.

In Void: The Strange Physics of Nothing, physicist and philosopher James Owen Weatherall explores how physicists’ beliefs about nothingness have changed over several revolutionary periods. The void, Weatherall argues, is physics distilled to its bare essence. If physicists can’t agree on the properties of empty space, they won’t be able to explain the physics of planets or particles either.
Scientists have argued over nothingness since the early days of physics. Vacant space was unthinkable to Aristotle, and Descartes so abhorred the idea of a vacuum that he posited that an invisible “plenum” suffused the gaps between objects. But Isaac Newton upended this view, arguing that space was just a barren container into which matter is placed.

Since then, physicists have continued to flip-flop on this issue. The discovery in the mid-1800s that light is an electromagnetic wave led scientists to conclude that a vibrating medium, an “ether,” filled space. Just as sound waves vibrate the air, physicists thought there must be some medium for light waves to ripple. Albert Einstein tore down that idea with his special theory of relativity. Since the speed of light was the same for all observers, no matter their relative speeds, he reasoned, light could not be traveling through some absolute, stationary medium. But he later predicted, as part of his general theory of relativity, that space itself can ripple with gravitational waves (SN: 3/5/16, p. 6) — suggesting that the void is not quite empty.

Under the modern view of quantum physics, various fields pervade all of space, and particles are simply excitations, or waves, in these fields. Even in a vacuum, experiments show, fluctuating fields produce a background of transient particles and antiparticles. Does a space pulsating with gravitational waves and bubbling with particles really qualify as empty? It depends on the scientific definition of “nothing,” Weatherall argues, which may not conform to intuition.

Weatherall serves readers a fairly typical buffet of physics theories, dishing up Newtonian mechanics, relativity, quantum mechanics and a small helping of string theory. But he does this through a lens that highlights connections between those theories in a novel way. Weatherall contends, for instance, that differing notions of nothingness between theories of general relativity and quantum mechanics could help explain why scientists are still struggling to unite the two ideas into one theory of quantum gravity.

Exploring the physics of nothing demands quite a bit of wading through the physics of something, and it’s not always clear how the threads Weatherall is following will lead back to the void. When he finally makes these connections, though, they often reveal insights that are missed in the typical focus on things of substance.

SAN DIEGO — A small number of people maintain razor-sharp memories into their 90s, despite having brains chock-full of the plaques and tangles linked to Alzheimer’s disease. Researchers suspect that these people’s brains are somehow impervious to the usual devastation thought to be caused by those plaques and tangles.

Researchers studied the brains of people 90 years old or older who had excellent memories, performing as well as people in their 50s and 60s on some tests. Postmortem brain tissue from eight such people revealed a range of Alzheimer’s features. Two participants had remarkably clean brains with few signs of amyloid-beta plaques and tangles of tau protein. Four participants had middling levels.
Surprisingly, the other two samples were packed with plaques and tangles, enough to qualify those people for an Alzheimer’s diagnosis based on their brains. “These people, for all practical purposes, should be demented,” study coauthor Changiz Geula of Northwestern University’s medical school said November 15 in a news briefing at the annual meeting of the Society for Neuroscience.

Further tests revealed that even in the midst of these Alzheimer’s hallmarks, nerve cells survived in people with strong memories. Those people had more healthy-looking nerve cells than people with dementia and similar plaque and tangle levels. The researchers don’t know how these mentally sharp people avoid the ravages thought to be caused by plaques and tangles. “What’s surprising is this segment of people does exist,” Geula says. “We have to find out why.”

The new record-holder for fastest flying animal isn’t a bat out of hell. It’s a bat from Brazil, a new study claims. Brazilian free-tailed bats (Tadarida brasiliensis) can reach ground speeds of 160 kilometers per hour.

It’s unclear why they need that kind of speed to zoom through the night sky, but Brazilian bats appear to flap their wings in a similar fashion to ultrafast birds, an international group of researchers report November 9 in Royal Society Open Science. A sleek body, narrow wings and a wingspan longer than most other bats’ doesn’t hurt either.

Radio transmitters attached to the backs of seven bats allowed the team, led by evolutionary biologist Gary McCracken of the University of Tennessee, Knoxville, to track the flight path and speed of the bats after they emerged from a cave in southwestern Texas. All seven reached almost 100 km/hr when flying horizontally; one bat hit about 160 km/hr.

Until now, common swifts held the record of fastest fliers, soaring at up to 112 km/hr, often with help from wind and gravity. The Brazilian bats, however, reached their higher speeds with no assist. Since bat flight is rarely studied, there may be even faster bats out there, the researchers speculate.

When Christian Agrillo runs number-related experiments in his lab, he wishes his undergraduate subjects good luck. For certain tests, that’s about all he says. Giving instructions to the people would be unfair to the fish.

Agrillo, of the University of Padua in Italy, is finishing up several years of pitting humans against fish in trials of their abilities to compare quantities. He can’t, of course, tell his angelfish or his guppies to choose, say, the larger array of dots. So in recent tests he made the bemused students use trial and error too.
“At the end, they start laughing when they find they are compared with fish,” he says. Yet the fish versus humans face-offs are eye-opening comparisons in his search for the deep evolutionary basis of what has blossomed into human mathematics. If it turns out that fish and people share some idiosyncrasies of their number sense (like spidey sense, except focused on quantities rather than danger), those elements might in theory date from a common ancestor more than 400 million years old. Comparisons of animals’ mental powers are “the paleontology of cognition,” Agrillo says.

No one seriously argues that animals other than people have some kind of symbolic numeral system, but nonhuman animals — a lot of them — can manage almost-math without numbers.

“There’s been an explosion of studies,” Agrillo says. Reports of a quantity-related ability come from chickens, horses, dogs, honeybees, spiders, salamanders, guppies, chimps, macaques, bears, lions, carrion crows and many more. And nonverbal number sensing, studies now suggest, allows much fancier operations than just pointing to the computer screen that shows more dots.

News stories on this diversity often nod to the idea that such a broad sweep of numberlike savvy across the animal tree of life could mean that animals all inherited rudiments of quantification smarts from a shared ancestor. Some scientists think that idea is too simple. Instead of inheriting the same mental machinery, animals could have just happened upon similar solutions when confronting the same challenge. (Birds and bats both fly, but their wings arose independently.)

Chasing down those deep origins means figuring out how animals, including humans too young or too rushed, manage quantitative feats without counting. It’s not easy. Putting together what should be a rich and remarkable story of the evolution of nonverbal number sense is just beginning.
Who’s (sort of) counting?
Symbolic numbers do marvels for humankind, but for millions of years, other animals without full powers to count have managed life-and-death decisions about magnitude (which fruit pile to grab, which fish school to join, whether there are so many wolves that it’s time to run).
Counting dog treats
For a sense of the issues, consider the old and the new in dog science. Familiar as dogs are, they’re still mostly wet-nosed conundrums when it comes to their number sense.

When food is at stake, dogs can tell more from less, according to a string of laboratory studies over more than a decade. And dogs may be able to spot cheating when people count out treats. Dog owners may not be amazed at such food smarts, but the interesting question is whether dogs solve the problem by paying attention to the actual number of goodies they see, or some other qualities.

An experiment in England in 2002, for instance, let 11 pet dogs settle down in front of a barrier that researchers then moved so the dogs could get a peek at a row of bowls. One bowl held a Pedigree Chum Trek treat. The barrier went up again, and researchers lowered a second treat into a bowl behind the screen, or sometimes just pretended to. When the barrier dropped again, the dogs overall stared a bit longer if only one treat was visible than if 1 + 1 had indeed equaled 2. Five of the dogs, in an extra test, also stared longer on average after a researcher covertly sneaked an extra treat into a bowl and then lowered the barrier on the unexpected 1 + 1 = 3.

Dogs could in theory recognize funny business by paying attention to the number of treats — or the treats’ “numerosity,” as researchers often call a quantity recognized nonverbally. But, depending on the design of a test, dogs might also get the right answers by judging the total surface area of treats instead of their numerosity. A multitude of other clues — density of objects in a cluster, a cluster’s total perimeter or darkness and so on — would also work. Researchers lump those giveaways under the term “continuous” qualities, because they change in a smooth continuum of increments instead of in the discrete 1, 2, 3.

The continuous qualities present a real staring-at-the-ceiling, heavy-sigh challenge for anyone inventing a numerosity test. By definition, nonverbal tests don’t use symbols such as numbers, so an experimenter has to show something, and those somethings inevitably have qualities that intensify or dwindle as the numerosity does.
To at least see whether dogs evaluate total area to choose more food, Krista Macpherson of the University of Western Ontario in Canada devised a task for her rough collie Sedona. The dog had already served as an experimental subject in Macpherson’s earlier test of whether real dogs would try to seek help for their owners in danger, as TV’s trusty Lassie did. Sedona hadn’t tried to seek help for Macpherson (no dog in the test aided its owner), but she had proved amenable to doing lab work, especially for bits of hot dog or cheese.

Sedona was put to work to select whichever of two magnet boards had a greater number of geometric shapes fastened to it. Macpherson varied the dimensions of black triangles, squares and rectangles so that their total surface area wasn’t a reliable clue to the right answer.

The idea came from an experiment involving monkeys that reacted to a computer touch screen. But “I’m all cardboard and tape,“ Macpherson says. Sedona was perfectly happy to look at two magnet boards fastened to cardboard boxes on the ground and then indicate her choice by knocking over a box.

Sedona in the end triumphed at picking the box with more geometric thingies regardless of area, though the project took considerable effort from both woman and beast. The dog worked through more than 700 trials, starting as simply as 0 versus 1 and eventually scoring better than chance scrutinizing bigger magnitudes, such as 6 versus 9, Macpherson and William A. Roberts reported in Learning and Motivation in 2013. (Eight versus nine finally stumped the collie, but more on patterns in accuracy later.) In a 2016 paper in Behavioural Processes, another lab hailed the Sedona research as the “only evidence of dogs’ ability to use numerical information.”

More is better
Dogs might have number sense, but when, or how much, they use it is another matter, notes Clive Wynne of Arizona State University in Tempe, a co­author of that 2016 paper. To see what dogs do in more natural situations, he and Maria Elena Miletto Petrazzini of the University of Padua designed a test offering pets at a doggie daycare a choice of two plates of cut-up treat strips. A mix of breeds considered such options as a few big treat strips versus a smaller total amount of treats cut up into numerous small pieces. The dogs, without Sedona’s arduous training, went for the greater total amount of food, regardless of the number of pieces. Of course they did; it’s food — more is better. Without controls, food tests may not be measuring numerosity at all.

It’s not just edibility that affects whether an animal pays attention to numerosity. Experience with similarity or differences in objects can matter. Rosa Rugani, also at Padua, has pioneered studying number sense in recently hatched chicks, which can learn experimental procedures fast if she gets them motivated. “One of the more fascinating challenges of my job is to come up with ‘games’ the chicks like to play,” she says.
Newly hatched chicks can develop a strong social attachment to objects, as if little plastic balls or ragged crosses of colored bars were pals to huddle near in a flock. Taking advantage of this tendency, Rugani let day-old chicks imprint on either two or three objects. Then she watched them choose between two little flocks of novel pals to toddle over to. If the potential buddy-objects in a flock looked identical to each other, the chicks in the test typically just moved near the larger cluster or largest object. But if the buddies in each group had individual quirks, mixing colors, shapes and sizes, the chicks paid attention to numerosity. Those imprinted on three pals were a bit more likely to club with three different kinds of pals; those imprinted on the pairs more often clubbed with the twos.

Some animals can deal with what people would call numerical order, or ordinality. Rats have learned to choose a particular tunnel entrance, such as the fourth or 10th from the end, even when researchers fiddled with distances between entrances. Five-day-old chicks rewarded for pecking at an item in a sequence, the fourth hole or the third jar, still showed a preference for position when researchers lengthened the distances between options or even moved the whole array.

Rhesus monkeys react if researchers violate rules of addition and subtraction, as dogs seemed to do in the Chums experiment. Chicks can track additions and subtractions too, well enough to pick the card hiding the bigger result. The chicks can also go one better. Rugani and colleagues have shown that chicks have some sense of ratios, for example choosing between mixes of red and green dots to match a ratio they learned from such mixes as 18 greens mingling with 9 reds.

A sense of numerosity itself, regardless of volume or surface area, may not be limited to fancy vertebrate brains. One recently published test takes advantage of overkill among golden orb-web spiders (Nephila clavipes). When they have a crazy run of luck catching insects faster than they can eat them, the spiders wrap each catch in silk and fasten it with a single strand to dangle from the center of the web. Turning this hoarding tendency into a test, Rafael Rodríguez of the University of Wisconsin–Milwaukee tossed bits of mealworms of different sizes into the web as spiders created a dangling treasure trove. Then shooing the spider off the web, he snipped the strands and watched how long the spiders searched for their stolen meals. Losing a greater volume of food inspired more strumming of the web and searching about. But losing four items instead of just one or two increased the search time even more, Rodríguez and his colleagues reported in 2015 in Animal Cognition. It’s not just volume of food in a hoard, they argue. Numerosity has its own effects.

At a glance
Nonhuman animals don’t have human language for counting, so researchers studying behavior talk about an “approximate number system” that allows for good-enough estimates of quantities with no real counting. One of the features of this still mysterious system is its declining accuracy in comparing bigger numbers that are very close together, the trend that made Sedona the collie’s struggles as noteworthy as her successes.

As the ratios of the two quantities Sedona had to compare drew closer to 1, she was more prone to make mistakes. Her scores worsened as she moved from 0.11 (comparing 1 to 9), 0.2 (1 to 5) and so on. She never conquered the fiendish 8 versus 9. That same trend, described by what’s called Weber’s law, shows up in humans’ nonverbal approximate number system as well as in those of other animals.
When Agrillo tested guppies against humans, both fell behind in accuracy for such difficult comparisons as 6 versus 8. But for small quantities, both fish and people performed well, he and colleagues reported in 2012. People and fish could tell 3 dots from 4 about as reliably as 1 dot from 4. Researchers have long recognized this instant human ease of dealing with very small quantities, calling it subitizing: suddenly just seeing that there are three dots or ducks or daffodils without having to count them. Agrillo suspects the underlying mechanism will prove different from the approximate number systems, though he describes this as a minority view.

The similarity between guppies and people in subitizing skill doesn’t prove it’s a shared inheritance from that ancient common ancestor several hundred million years ago, Agrillo says. Yet the similarity does raise the possibility.
Struggling to separate some pure response to numerosity from all the confounding surface areas and other continuous qualities may not even be the most important question, says Lisa Cantrell, now at the University of California, Davis. Human babies, as an example of noncounting animals, might start figuring out the world by relying on these other confounders and grow into their numerical abilities, she and Linda Smith of Indiana University, Bloomington, suggested in 2013. The hypothesized approximate number system might be part of some more general way of perceiving the world, which can draw on multiple clues to get a clearer sense of quantity. Cantrell and Smith called their version of the idea the “signal clarity hypothesis.”

Into their heads
Studying behavior alone isn’t enough to trace the inheritance of any part of number savvy, says Andreas Nieder of the University of Tübingen in Germany. “At the behavioral level, it may look as if number estimation follows the same laws, but the underlying neural code could actually look quite different.”

He’s not going as far afield as fish yet, but Nieder and colleagues have looked at how monkey and bird brains handle quantity. The researchers described neurons (nerve cells) in the brains of carrion crows (Corvus corone corone) that function much like those in rhesus macaques.

Research in monkeys over the last 15 years has identified what Nieder calls “number neurons.” They could have multiple functions, but each responds to a specific number of whatevers, be it six crows or six crowbars. Some number neurons respond to sight, some to sound, and amazingly, some to either.
The neurons could be responding to increasing total surface area or density or darkness. But researchers have varied one aspect at a time, and used multiple imaging and pharmacological techniques, to argue that as far as strenuous efforts can tell, these neurons detect the actual numerosity.

Individual neurons in parts of a monkey brain have their own preferred number and respond most strongly to it and less so to neighboring numbers. The neurons for three get less excited for two and four, while others light up at four. In 2015, Nieder and colleagues started untangling how monkey neurons handle zero, suggesting the beginnings of an ability to treat “nothing there” as an abstract numerosity of zero.

These neurons lie in notable places: the six-layered neocortex of the parietal and frontal lobes of the brain. That’s territory that primates boast about, a feature of mammalian brain structure credited with allowing human mental capacities to reach such heights. Nonmammalian vertebrates, including birds, don’t have a multilayered neocortex. Yet Nieder and colleagues have, for the first time, detected individual neurons in the bird brain that fire in response to numerosities much as primate number neurons do.

Story continues after graph

Neurons for numbers
Recordings from four nerve cells in monkeys suggest each cell responds most to a particular number of dots (lines with circles) and the same number of musical tones (squares).
The bird versions of number neurons lie in a relatively newfangled area of the avian brain called the nidopallium caudolaterale, or NCL. It didn’t exist as such, nor did the primate’s precious neocortex, in the reptile-ish ancestors that mammals and birds last shared some 300 million years ago. Both the bird NCL and the primate number neuron zones arose from the same tissue, the pallium. In mammals, that ancient pallium morphed into layers of neocortex tissue, in birds the transformation went a different way.

For the number sense tingling through specialized neurons in birds and primates alike, similarity does not strictly mean shared inheritance, Nieder wrote in the June Nature Reviews Neuroscience. The systems of number neurons probably specialized independently.

Finding some brain structures to compare across deep time is a promising step in fathoming the evolution of animal number sense, but it’s just a beginning. There are many questions about how the neurons work, not to mention what’s going on in all those other brains that contemplate quantity. For now, looking across the tree of life at the crazy abundance of number smarts, which may or may not be related but are certainly numerous, the clearest thing to say may be just: Wow.

An oddball superconductor is the first of its kind — and if scientists are lucky, its discovery may lead to others.

At a frigid temperature 5 ten-thousandths of a degree above absolute zero, bismuth becomes a superconductor — a material that conducts electricity without resistance — physicists from the Tata Institute of Fundamental Research in Mumbai, India, report online December 1 in Science.

Bismuth, a semimetallic element, conducts electricity less efficiently than an ordinary metal. It is unlike most other known superconductors in that it has very few mobile electrons. Consequently, the prevailing theory of superconductivity doesn’t apply.
The result is “quite important,” says theoretical physicist Marvin Cohen of the University of California, Berkeley. New ideas — either a different theory or a tweak to the standard one — are needed to explain bismuth’s superconductivity. “It might lead us to a better theory of superconductivity with more details,” Cohen says.

An improved theoretical understanding might lead scientists to other superconductors, potentially ones that work at more practical temperatures, says Srinivasan Ramakrishnan, a coauthor of the paper. “It opens a new path for discovering new superconducting materials.”

Physicists’ ultimate goal is to find a superconductor that operates at room temperature. Such a material could be used to replace standard metals in wires and electronics, providing massive energy savings and technological leaps, from advanced supercomputers to magnetically levitating trains.

To confirm that bismuth was superconducting, Ramakrishnan and collaborators chilled ultrapure crystals of bismuth, while shielding the crystals from magnetic fields. Below 0.00053 kelvins (about –273° Celsius), the researchers observed a hallmark of superconductivity known as the Meissner effect, in which the superconductor expunges magnetic fields from within itself.

In the standard theory of superconductivity, electrons partner up in a fashion that removes resistance to their flow, thanks to the electrons’ interactions with ions in the material. But the theory, known as the Bardeen-Cooper-Schrieffer, or BCS, theory, works only for materials with many free-floating electrons. A typical superconductor has about one mobile electron for each atom in the material, while in bismuth each electron is shared by 100,000 atoms.
Bismuth has previously been made to superconduct when subjected to high pressure or when formed into nanoparticles, or when its atoms are disordered, rather than neatly arranged in a crystal. But under those conditions, bismuth behaves differently, so the BCS theory still applies. The new result is the first sign of superconducting bismuth in its normal form.

Another class of superconductors, known as high-temperature superconductors, likewise remains enigmatic (SN: 8/8/15, p. 12). Scientists have yet to reach a consensus on how they work. Though these superconductors must be cooled, they operate at relatively high temperatures, above the boiling point of liquid nitrogen (77 kelvins, or –196° Celsius).

Bismuth’s unusual behavior provides another handle with which to investigate the still-mysterious phenomenon of superconductivity. In addition to its low electron density and unexpected superconductivity, bismuth has several anomalous properties, including unusual optical and magnetic behavior. “A good global picture is missing” for explaining the abnormal element, says theoretical physicist Ganapathy Baskaran of the Institute of Mathematical Sciences in Chennai, India. “I think it’s only a tip of an iceberg.”

A child mummy buried in a church crypt in Lithuania could hold the oldest genetic evidence of smallpox.

Traces of the disease-causing variola virus linger in the mummy, which dates to about 1654, evolutionary geneticist Ana Duggan and colleagues report December 8 in Current Biology. Previously, a team of researchers had reported variola DNA in a roughly 300-year-old Siberian mummy.

Some Egyptian mummies, dating back more than 3,000 years, have pockmarks that scientists have interpreted as signs of smallpox, indicating the disease may have tormented humans for millennia. “The definitive feature of smallpox is a pustular rash,” says Duggan of McMaster University in Hamilton, Canada. “But it isn’t easy to say whether a rash comes from smallpox or chicken pox or measles.”
Duggan’s team analyzed skin from the mummy, believed to be a boy who died between ages 2 and 4. They found DNA from an ancient strain of variola, and compared it with dozens of strains from the 20th century. The ancient and modern strains weren’t all that different, the researchers found. They shared a common ancestor that dates to around the late 16th century, not long before the boy died.

“It’s a little bit curious,” Duggan says. More diversity might be expected of a virus that had been kicking around since ancient Egyptian times. The find could suggest that “the timeline of smallpox existing in humans isn’t that deep at all.”

In fact, historical mortality records suggest that around the late 16th century, smallpox seemed to go “from something that occasionally caused infection to more of an epidemic disease,” Duggan says.

But researchers can’t say for sure when smallpox started affecting humans on a large-scale, she cautions. Whether or not those ancient Egyptian mummies had smallpox is still an open question, she says. “We haven’t closed it.”

Self-driving cars promise to transform roadways. There’d be fewer traffic accidents and jams, say proponents, and greater mobility for people who can’t operate a vehicle. The cars could fundamentally change the way we think about getting around.

The technology is already rolling onto American streets: Uber has introduced self-driving cabs in Pittsburgh and is experimenting with self-driving trucks for long-haul commercial deliveries. Google’s prototype vehicles are also roaming the roads. (In all these cases, though, human supervisors are along for the ride.) Automakers like Subaru, Toyota and Tesla are also including features such as automatic braking and guided steering on new cars.
“I don’t think the ‘self-driving car train’ can be stopped,” says Sebastian Thrun, who established and previously led Google’s self-driving car project.

But don’t sell your minivan just yet. Thrun estimates 15 years at least before self-driving cars outnumber conventional cars; others say longer. Technical and scientific experts have weighed in on what big roadblocks remain, and how research can overcome them.
To a computer, a highway on a clear day looks completely different than it does in fog or at dusk. Self-driving cars have to detect road features in all conditions, regardless of weather or lighting. “I’ve seen promising results for rain, but snow is a hard one,” says John Leonard, a roboticist at MIT.
Sensors need to be reliable, compact and reasonably priced — and paired with detailed maps so a vehicle can make sense of what it sees.
Leonard is working with Toyota to help cars respond safely in variable environments, while others are using data from cars’ onboard cameras to create up-to-date maps. “Modern algorithms run on data,” he says. “It’s their fuel.”
Self-driving cars struggle to interpret unusual situations, like a traffic officer waving vehicles through a red light. Simple rule-based programming won’t always work because it’s impossible to code for every scenario in advance, says Missy Cummings, who directs a Duke University robotics lab.
Body language and other contextual clues help people navigate these situations, but it’s challenging for a computer to tell if, for example, a kid is about to dart into the road. The car “has to be able to abstract; that’s what artificial intelligence is all about,” Cummings says.

In a new approach, her team is investigating whether displays on the car can instead alert pedestrians to what the car is going to do. But results suggest walkers ignore the newfangled displays in favor of more old-fashioned cues — say, eyeballing the speed of the car.
Even with fully autonomous vehicles on the horizon, most self-driving cars will be semiautonomous for at least the foreseeable future. But figuring out who has what responsibilities at what time can be tricky. How does the car notify a passenger who has been reading or taking a nap that it’s time to take over a task, and how does the car confirm that the passenger is ready to act?
“In a sense, you are still concentrating on some of the driving, but you are not really driving,” says Chris Janssen, a cognitive scientist at Utrecht University in the Netherlands.

His lab is studying how people direct their attention in these scenarios. One effort uses EEG machines to look at how people’s brains respond to an alert sound when the people are driving versus riding as a passive passenger (as they would in a self-driving car). Janssen is also interested in the best time to deliver instructions and how explicit the instructions should be.

In exploring the ethical questions of self-driving cars, Iyad Rahwan, an MIT cognitive scientist, has confirmed that people are selfish: “People buying these cars, they want cars that prioritize the passenger,” says Rahwan — but they want other people’s cars to protect pedestrians instead (SN Online: 6/23/16).
In an online exercise called the Moral Machine, players choose whom to save in different scenarios. Does it matter if the pedestrian is an elderly woman? What if she is jaywalking? Society will need to decide what rules and regulations should govern self-driving cars. For the technology to catch on, decisions will have to incorporate moral judgments while still enticing consumers to embrace automation.
In 2015, hackers brought a Jeep to a halt on a St. Louis highway by wirelessly accessing its braking and steering via the onboard entertainment system. The demonstration proved that even conventional vehicles have vulnerabilities that, if exploited, could lead to accidents.
Self-driving cars, which would get updates and maps through the cloud, would be at even greater risk. “The more computing permeates into everyday objects, the harder it is going to be to keep track of the vulnerabilities,” says Sean Smith, a computer scientist at Dartmouth College.

And while terrorists might want to crash cars, Smith can imagine other nefarious acts: For instance, hackers could disable someone’s car and hold it for ransom until receiving a digital payment.

In a better world, it would be the big news of the year just to report that Arctic sea ice shrank to 4.14 million square kilometers this summer, well below the 1981–2010 average of 6.22 million square kilometers (SN Online: 9/19/16). But in this world of changing climate, extreme summer ice loss has become almost expected. More novel in 2016 were glimpses of the complex biological consequences of melting at the poles and the opening of Arctic passageways, talked about for at least a decade and now well under way.

With top-of-the-world trade and tourist shortcuts opening, less ice means more travel. Europe-to-Asia shipping routes will typically shorten by about 10 days by midcentury, a report in Geophysical Research Letters predicted. Hopes for Northwest Passage routes obsessed (and killed) explorers in previous centuries, but in 2016, the thousand-passenger cruise ship Crystal Serenity offered the first megascale tourist trip from Alaska to New York with fine dining, casino gambling and an escort icebreaker vessel.
Biologists are delving into consequences for organisms other than human tourists — or the much-discussed polar bear. “There’s been a marked shift in the research community,” says climate change ecologist Eric Post of the University of California, Davis. There’s new interest in considering more than just species that dwell on sea ice, with researchers looking for the less direct effects of declining ice.
In the February Global Change Biology, eight scientists issued a call for observations of what could be early signs of faunal exchange: the mingling of Atlantic and Pacific species. One possible indicator is the sighting of gray whales off the coast of Namibia and also off Israel, even though that species went extinct in the Atlantic two centuries ago. These whales feed by snouting around in soft ocean bottoms, adding another predator to the system but also creating new habitat opportunities for some creatures (SN: 1/23/16, p. 14).

Since the call was published, biodiversity scientist Seabird McKeon of Colby College in Waterville, Maine, has heard new reports, such as a sighting of an ancient murrelet off the coast of Maine. It’s not the first wrong-coast report for the bird, which typically resides in the northern Pacific, but repeat sightings could be important, too. “What I think we’re seeing is not just new species coming across, but also perhaps an increased chance of survival and reproduction if more come over,” McKeon says. He is hoping to get new data from the online Encyclopedia of Life’s upcoming Fresh Data system, which connects scientists to people reporting nature observations.
For terrestrial northerners, melting ice often means loss of mobility. Peary caribou on the 36,000 or more islands of Canada’s northern archipelago occasionally use ice bridges to travel to new territories and mix genes with other populations. Yet ice losses since 1979 have

made it some 15 percent harder

to find traveling paths, researchers reported in September inBiology Letters

(

SN: 10/29/16, p. 8

).

Even some plants such as dwarf birch probably travel by ice, scientists also reported in September in Biology Letters. Reconstructing long-ago sea ice extent and plant colonization dates suggests that seeds hitchhiked on slowly creeping frozen conveyors around northern Europe to colonize new territory at the end of the Ice Age. Losing ice roads could lead to tattered, disconnected populations as recolonization becomes less likely. Yet, there are pluses and minuses, says Post, who is helping to develop a package of scientific articles for Biology Letters on the biological effects of sea ice loss. Reseeding populations after a wipeout could be more difficult with tattered ice, but for the highly specialized and vulnerable plants very far north, the loss of sea ice could slow the arrival of invasive species that threaten the natives.

The minimum summer sea ice extent since 1979 has declined by about 87,000 square kilometers per year, equivalent to an area more than three times the size of New Jersey disappearing annually, as Post has put it. The September 2016 sea ice minimum didn’t break a record, as some had expected it might. It tied for second worst, behind the 2012 minimum, and roughly equaled the 2007 minimum. 2016 did set a new record low for winter Arctic ice extent (SN Online: 3/28/16).
Sea ice changes reverberate through the ecosystem. Ice melting cues the springtime phytoplankton blooms that feed copepods and other tiny marine grazers. The grazers feed their predators and, in turn, the predators of those predators. In years when spring warming brings an early ice retreat, the phyto-plankton bloom is not a huge, rich burst. It favors smaller grazing zooplankton that don’t fuel as much of a boom in their predators, marine ecologist Martin Renner of Homer, Alaska, and colleagues reported in a paper for the Biology Letters special collection.

Tracing the effects of shrinking ice through these grazers to fish to seabirds revealed a tangled web of ups and downs and shifting foraging grounds. In the end, Renner and colleagues predict “a very different eastern Bering Sea ecosystem and fishery than we know today.” And that may be far from the only sea change in the far north.

Future moon colonies could be totally tubular.

Slight variations in the moon’s gravitational tug have hinted that kilometers-wide caverns lurk beneath the lunar surface. Like the lava tubes of Hawaii and Iceland, these structures probably formed when underground rivers of molten rock ran dry, leaving behind a cylindrical channel. On Earth, such structures max out at around 30 meters across, but the gravitational data suggest that the moon’s tubes are vastly wider.

Assessing the sturdiness of lava tubes under lunar gravity, planetary geophysicist Dave Blair of Purdue University in West Lafayette, Ind., and colleagues estimate that the caves could remain structurally sound up to 5 kilometers across. That’s wide enough to fit the Golden Gate Bridge, Brooklyn Bridge and London Bridge end to end.

Such colossal caves will be prime real estate for lunar pioneers, the researchers report in the Jan. 15 Icarus. Lava tubes could offer protection from the extreme temperatures, harsh radiation and meteorite impacts on the surface.