Art of the day: this spring I had the pleasure of illustrating the album cover for singer-songwriter Tae Phoenix's sophomore album Let the Light In. I’ve known Tae since we were both in utero (literally!), so this was a blast. She wanted an “ever-so-slightly-sinister” coloring book vibe.
This is the digital release version of the album cover - the physical version will be uncolored, so your CD sleeve is your own coloring book page.
Tae is performing at SXSW this week - if you’re not in attendance, you can check out some tracks at http://taephoenix.bandcamp.com/. It’s a crazy leap forward for an already immoderately talented lady.
I particularly defy you to listen to the single “Let the Light In” without having it take up permanent residence in your head.
I’m experimenting with audio for some of my posts. If you’d like to listen to me reading this one aloud, click the play button below:
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Update, 1/12/14, 9:05pm: A bunch of scientists have pointed out on Twitter that this study suffers from a weak statistical analysis. So, interpret the following with that in mind.
Coffee fiends like me love to use scientific research to justify our habit. So, here goes. A new study finds that people who consume caffeine shortly after learning something show memory gains 24 hours later.
Scientists have long known that our memories are unstable in the minutes or hours after they’re first created. During this period, called ‘consolidation’, the memory moves into long-term storage and into a fairly stable molecular state. (Caveat: Stable memories become unstable again whenever you recall them, as I wrote about a few weeks ago.)
In the new study, published today in Nature Neuroscience, researchers from the University of California, Irvine, wanted to see whether caffeine affects the memory consolidation process. They recruited young adults who don’t usually drink much coffee — less than 500 milligrams of caffeine a week, or about five cups of coffee — and who hadn’t had any before the experiment. The volunteers were shown lots of pictures of objects, such as a seahorse, a basket, and a saxophone, and then asked whether each picture depicted an indoor or outdoor item. Soon after looking at the pictures, the volunteers took a pill containing either 200 milligrams of caffeine (which is equivalent to about two cups of coffee) or a placebo.
The volunteers returned to the lab the next day; by then the caffeine had washed out of their systems. They were shown another series of pictures, but their task this time was to determine whether each picture was “old,” meaning they’d seen it the previous day; “similar,” meaning they’d seen a similar picture the previous day, or “new,” meaning it had not been in the older set. The similar pictures were tricky. For instance, whereas one of the “old” pictures was a wicker basket with two handles, one of the “similar” pictures was a wicker basket with one handle and a blue blanket peeking out from under its lid.
All of the volunteers were pretty good at correctly labeling the old and new pictures, regardless of whether they had taken the caffeine pill. But their responses to the similar pictures were strikingly different. Volunteers who had taken the caffeine were more likely to correctly label similar pictures as similar, whereas those who had taken the placebo labeled the similar pictures as old. In other words, the caffeine group was better at spotting subtle visual differences, which means they were better at remembering the details of the original pictures.
This caffeine edge was about the same when researchers repeated the whole experiment with a higher dose of the drug — 300 milligrams, or about three cups of coffee — but the advantage disappeared when they dropped the dose to 100 milligrams, or about one cup of coffee.
For memory researchers, the most intriguing part of the study relates not to the dose, but the timing. In one experiment, instead of giving the volunteers caffeine during memory consolidation, the researchers gave it to them 24 hours after consolidation, and just one hour before the memory test. This time, the caffeine group’s responses were no more accurate than those of the placebo group.
Caffeine is a drug, and like all drugs, it carries risks. It can dehydrate you, or make you feel jittery. It can be dangerous for people with a heart condition or pregnant women. And its beneficial effects on cognition are only just beginning to be understood. Nobody knows, for example, how caffeine would improve memory. (One idea is that caffeine indirectly boosts levels of the chemical messenger norepinephrine, which is known to aid memory consolidation.)
It’s also unclear whether the caffeine-induced memory gain applies to people who drink a ton of coffee, like me. But I’ll assume that it does, for now, since I have some reading to do today.
Possible relationships here to socio/psychopaths, who don't seem to form fear memories at all.
A hurricane, a car accident, a roadside bomb, a rape — extreme stress is more common than you might think, with an estimated 50 to 60 percent of Americans experiencing it at some point in their lives. About 8 percent of that group will be diagnosed with post-traumatic stress disorder, or PTSD. They will have flashbacks and nightmares. They will feel amped up, with nerves on a permanent state of high alert. They won’t be able to forget.
One of the only effective treatments for PTSD is ‘exposure therapy,’ in which people are repeatedly exposed to their fear — such as a painful memory — in a safe context. This treatment works partly because of how our brain encodes memories. Whenever we actively recall a memory, it transforms into a pliable molecular state and becomes vulnerable to modification.
About half of people who get exposure therapy for PTSD get better. But that still leaves a lot of people who don’t. A mouse study published last week in Cell throws the spotlight on a drug that acts in concert with exposure therapy to help extinguish fear memories. The drug works by changing the epigenome, the chemical markers that attach to DNA and can turn genes on and off.
“It’s remarkable,” says Li-Huei Tsai, a neuroscientist at the Massachusetts Institute of Technology who led the work. “If we inject a single dose of this drug it actually is sufficient to reactivate neuroplasticity.”
The drug works by changing the way DNA is expressed in the brain.
DNA wraps around proteins called histones. Image via Wikipedia
In order to fit into the nucleus of each cell, DNA wraps tightly around spherical proteins called histones. (You can see how in this animation.) Histones are littered with chemical groups, such as methyl and acetyl, that influence how nearby genes get turned on and off.
For many years, Tsai has been studying enzymes called histone deacetylases, or HDACs, which switch off genes by removing acetyl groups from histones. In 2012, she showed that one such enzyme, dubbed HDAC2, is overactive in a mouse model of Alzheimer’s disease and shuts down genes related to learning. In that study she also showed that blocking HDAC2 led to dramatic gains in the animals’ memory.
“HDAC2 is a master regulator of the expression of neuroplasticity genes,” Tsai says. “And HDAC inhibitors seem to be very beneficial for memory formation.”
In the new study, Tsai’s team investigated whether this enzyme is also involved in the way that fear memories cement themselves into brain circuits.
Mice don’t get PTSD, but they can acquire fear memories. Using so-called Pavlovian fear conditioning, researchers train the animals to fear a particular cue, such as a sound or smell, by pairing it with a mild shock to the foot. After a few trials, the animal freezes at the cue alone.
There’s also a mouse version of exposure therapy. After a mouse learns to fear, say, a certain tone, researchers can extinguish that fear by repeatedly playing the tone without a shock. Gradually the animal learns to associate the tone with the safer context.
But in mice (and, importantly, in some people with severe PTSD), this extinction therapy only works for recently acquired fear memories. If a fear memory is old, then no amount of retraining will erase the animal’s fear. “One of the major challenges in developing treatments for PTSD is that traumatic memories can persist for a lifetime,” notes Matt Lattal, a neuroscientist at Oregon Health and Science University who was not involved in the new study. “It is therefore critical that laboratory models of PTSD include this long interval between traumatic experience and testing.”
Tsai and her colleagues trained mice to fear a tone and then gave them extinction therapy either a day later or 30 days later. When extinction training happened a day later, the HDAC2 enzyme was inactivated in brain cells, the study found. With HDAC2 quiet, acetyl groups stayed latched on to histones and various memory genes stayed on. Presumably, this window of plasticity allowed the mice to un-learn the fear memory. In contrast, when extinction training happened 30 days later, the HDAC2 enzyme was active. It removed those acetyl groups, effectively shutting off neuroplasticity genes.
But here’s the exciting part. The animals were able to un-learn the fear memory 30 days after it was formed when the researchers paired extinction therapy with a drug that inhibits HDAC2, dubbed “CI-994.” It only took one dose, and the researchers saw no side effects, Tsai says. “We did a lot of control experiments to show that this mechanism doesn’t wipe out other memories. It really is very specific to the training condition.”
HDAC inhibitors are becoming a hot class of drugs. In 2012, Yossef Itzhak and his colleagues at the University of Miami reported that giving a different HDAC inhibitor to mice before they acquire the fear memory accelerates the extinction of the memory weeks later. “Hypothetically speaking, HDAC inhibitors may be useful prophylactics against the persistence of fear memory,” says Itzhak, who was not involved in the new study.
Researchers are investigating HDAC inhibitors for all sorts of other conditions, too, including heart disease, HIV, and cancer. Because HDAC enzymes are expressed all over the body, though, some experts are worried about their translation into the clinic.
“HDAC inhibitors have a wide spectrum of biological effects, and only when they will be targeted for the treatment of a specific malady [will] their therapeutic value be of great importance,” Itzhak says. ”The goal is to identify specific HDAC inhibitors which target specific brain circuits and genes.”
Some seriously fascinating (and intuitively nice) ideas in here.
If you’ve ever clenched up at the sound of nails on a chalkboard, or felt a pleasant chill when listening to an opera soprano, then you have an intuitive sense of the way our brains sometimes mix information from our senses. For the latest issue of Nautilus magazine I wrote a story about a woman whose brain mixes more than most, allowing her to feel many types of sounds on her skin.
Over the past decade or so, neuroscientists have revamped their view of how the brain processes sensory information. According to the traditional model, the cortex, or outer layers of the brain, processes only one sense at a time. For example, the primary visual cortex at the back of the head was thought to process only input from the eyes, while the auditory cortex above the ears dealt with information from the ears and the somatosensory cortex near the top of the head took in signals from the skin. But a growing number of studies have found that these cortical areas actually integrate information from many senses at once.
One of the most fascinating examples of this line of work, just published in Psychological Science, took advantage of a technology called transcranial direct current stimulation, or tDCS. This tool essentially gives researchers a safe, non-invasive way to activate specific parts of the human brain. Pretty wild, right? Here’s how it works. Researchers place two electrodes in various positions on a volunteer’s scalp. A small electric current passes between the electrodes, stimulating the neurons underneath.
In the new study (cleverly named “Feeling Better”) neuroscientist Jeffrey Yau of Johns Hopkins University used tDCS to stimulate the brain as volunteers performed two different tasks related to touch perception. One task is similar to reading Braille: blindfolded volunteers placed their fingers over gratings of bars of varied widths and spacing. The closer the bars, the more difficult it is for someone to determine whether there is one bar or two. The smallest distance at which the volunteer can correctly make this call is called the “spacial acuity.”
The second task measures the frequency of vibrations, similar to the different kinds of rumblings you might feel while waiting on a subway platform. On a given trial, volunteers use their index fingers to feel vibrations produced by a metal probe. They feel two vibrations back to back and then judge which they perceive to be stronger.
Yau ushered participants through each of these tasks before and after stimulating their brains. He found that activating volunteers’ primary visual cortex improved their tactile acuity, whereas stimulating their primary auditory cortex improved their ability to discriminate between different tactile frequencies.
What does this mean?
These findings make sense, Yau says, if you reframe the traditional view of how the cortex is organized. As I mentioned, the primary visual cortex has typically been thought of as the region that processes input from the eyes. But what if instead it was a region that processed information about shape, no matter what organ that information came from? Most of the time, shape information comes from the eyes, but sometimes—such as in this experiment—it can come from touch. Similarly, the primary auditory cortex might not be tailored for interpreting sounds, per se, but rather frequency information of any kind, including but not limited to sounds.
Yau speculates that we should be thinking differently about the other senses, too. The somatosensory cortex might process skin input, sure, but also other information related to keeping track of our body in physical space.
Yau’s study is one of many to reveal so-called multi-sensory processing in the brain. (Check out my Nautilus piece to learn about similar findings from other labs.)
“Within the last six or seven years, so much evidence has emerged that shows that early sensory cortex is not modality specific,” Yau says. Nevertheless, because subfields have built up around particular senses, Yau says it will probably take awhile before traditional theory of uni-sensory processing is dethroned. “That’s the idea that is always pushed in the textbooks. I think it’s hard to fight that dogma.”
Dad pulls a scroll of paper from one of the dozens of crumpling boxes stacked in a chilly warehouse near Santa Cruz, Calif. He gently unrolls it, and a familiar reddish ink pattern appears on the delicate grid.
“Ah,” he says. “This is Ozma.”
His fingertip traces the inky magenta line, and he squints at the faded, penciled-in numbers inscribed near the line’s peaks and valleys. “Is that your handwriting?” I ask. It doesn’t look anything like his. “Nope,” he answers. “It must be the telescope operator’s.”
The scroll my father, Frank Drake, is holding is more than a half-century old. It’s part of the data he collected during an experiment known as Project Ozma. Named after a character in L. Frank Baum’s Oz series, the project was the first scientific search for extraterrestrial intelligent life. From April to July, 1960, astronomers in Green Bank, West Virginia monitored two nearby, sun-like stars for artificial radio signals—signs that an interstellar intelligence inhabited Earth’s starry skies, that humans were not adrift in an incessantly quiet cosmic ocean.
The entire endeavor cost $2,000.
Frank Drake retrieves a scroll with data on it from Project Ozma. (Nadia Drake)
Dad was in charge; at just 29 years old, he had been planning and building the necessary equipment for the last year and half. He’d determined that the Green Bank telescope should be able to detect radio transmissions coming from up to 10 light-years away, if they were at least as strong as Earth’s. So he selected two nearby stars, Tau Ceti and Epsilon Eridani, to aim the telescope at. He built antennas and receivers and amplifiers, and picked a band of radio frequencies to monitor. He came up with a plan to follow if a signal were detected.
“For all we knew at the time, almost every star had strong radio signals coming from it,” he says. “We might look at only a few stars and succeed.”
Finally, before dawn on a chilly West Virginia morning, Dad climbed up the observatory’s 85-foot telescope, fiddled with a finicky signal amplifier, and kicked off an experiment that would ignite decades of scientific discourse about extraterrestrial civilizations. Over the next four months, dozens of scrolls like the one we were staring at would come rolling out of the pen-and-ink data recorder, each bearing a bright red record of radio static from the universe.
Of course, in the end, Tau Ceti and Epsilon Eridani showed no signs of hosting intelligent life. “That was a disappointment,” Dad says. “But as time went on, we began to realize that’s the way the universe is, and it’s not our fault.”
The search is far from over. Increasingly, we’re finding that the ingredients necessary for life on Earth are abundant in the cosmos. Water, organic molecules, and even amino acids—so basic to life as we know it—have been found in space.
And the Milky Way, our home galaxy, is stuffed with planets. Even Project Ozma’s target stars have them. “Planets are plentiful,” astrophysicist Neil DeGrasse Tyson confidently stated last night in the first episode of Cosmos: A Spacetime Odyssey, which shows again tonight on the National Geographic Channel. “They outnumber the stars.”
It’s kind of crazy to think that when Dad was collecting the Ozma data, we knew nothing about the abundance of exoplanets—in fact, it would be another three decades before the first exoplanets were reported. Pulsars were still waiting in the wings, and the moon bore no human footprints. It was a different era in astronomy, and though Project Ozma garnered a ton of media attention, thinking about life outside the solar system was still on the fringes of traditional science. But momentum was gathering.
A newspaper story that ran shortly after Project Ozma. (Photograph by Nadia Drake)
The next year, in 1961, dad would organize a conference at Green Bank devoted to thinking about intelligent life in the universe. It was the day before that meeting that the Drake Equation, which estimates the number of detectable intelligent civilizations in the Milky Way galaxy, would be born.
But that’s a story for another time.
We’d been rummaging through piles of my father’s papers for about an hour before the first signs of Ozma casually surfaced. Before that, we’d found a map he’d made of the galactic center. Another box held data he’d used to determine the temperature on the surface of Venus—an experiment that brought him into contact with a Ph.D. student at the University of Chicago named Carl Sagan. Another box held the results of an experiment he and Sagan would conduct at the Arecibo Observatory in the late 1970s, where they surveyed nearby galaxies for intensely bright radio transmissions. And another box has memos from the Voyager record project.
In short, these sagging boxes are filled with the evidence of a life spent exploring the cosmos. It’s this adventurous ideal that led Dad to name the first SETI search after Princess Ozma. “Oz is a land, a strange land, populated by strange and exotic creatures. Which described the sort of place I as about to search for,” he says to me, later. “If we find life out there, it’s going to be much more unearth-like than Oz.”
Nadia and Frank Drake. (Photograph courtesy Nadia Drake)
And it’s these threads of thought that led me to the name of this blog: No Place Like Home. There are infinite worlds out there, and none of them will be exactly like ours. For millennia, humans have stared at the stars and mapped the movements of heavenly bodies, seeking to learn the mathematical language and physical laws that tell the stories of the spheres. In the last half-century, we’ve managed to launch our robotic creations from Earth’s watery shores and land them on other worlds. Maybe someday, we’ll be going along for the ride as well.
For now, though, we have the science of astronomy and the spaceships of our imagination to show us what else is out there. I’m so excited to be joining National Geographic as a space blogger for Phenomena—just as Cosmos kicks off—and am thrilled to be bringing you tales from beyond our home planet.
When two hours have gone by, it’s time to go home. We carry our folding chairs and lanterns from the warehouse and step into the sunlight. Dad pauses. “After looking at all that stuff,” he says, “For a moment I didn’t know where I was. It feels weird being in California.”
Fifteen months ago, Virginia Hughes, Brian Switek, Ed Yong, and I joined National Geographic to form Phenomena. I’m delighted that our circle is now expanding. Starting today, science writer Nadia Drake will be writing “No Place Like Home.” I’ve followed Nadia’s work for the past couple years, but I’ve never had the chance to talk to her. To celebrate her debut, I asked her some questions about her past and future.
Your father is Frank Drake, of the famed Drake Equation. What was it like growing up with a dad spending so much time thinking about life in the universe?
Grand cosmic questions loomed large in our home, in a good way. The walls were filled with astronomy related artwork, the shelves stuffed books about the stars; we have a rendering of the Pioneer plaque by the door, and a stained glass window depicting the Arecibo message. There’s a chunk of the meteorite that created Meteor Crater in Arizona sitting on the mantle. My parents used to host observing nights for my elementary school classes – in the backyard — and my sister and I would go with my dad’s college classes to look through the big telescopes at the Lick Observatory.
I learned a lot of astronomy by diffusion. Following dad to lectures or observatories, and tagging along to meetings overseas meant meeting a lot of very thoughtful scientists.
Dad is also hilarious, and exceedingly humble. We rarely knew when he was going to be on TV and often learned about it the next day from classmates and friends. But more than that, I learned by example that it’s OK to be interested in, and fascinated by, a variety of questions. It’s OK to cast a wide intellectual net. Our house wasn’t just filled by astronomy – my dad’s orchids and his wine-making and other projects were just as visible.
What was the path you took to becoming a science writer?
I took the long way. Started out planning on a professional dance career, then made a left turn and switched to academics when it was time for college. Later, that road would turn back on itself and I would end up dancing professionally after all, which was a pleasant surprise and one of the most fulfilling (and hardest) jobs I’ve had.
Along the way, I seriously considered law school, but ended up ditching those plans and working in a clinical genetics lab at Johns Hopkins Medical School, looking for abnormalities in fetal chromosomes. After that, I went to graduate school at Cornell University, where I worked in an epigenetics lab and studied a gene that’s imprinted in neonatal mouse brain — in other words, copies of the gene are either turned on or off, depending on whether they were inherited from the father or the mother.
It was only after I finished my PhD that I finally returned home to Santa Cruz and enrolled in the Science Communication program at UCSC. That was one of the best decisions I’ve made. Since then, the road has been much straighter and the trip much faster, and I’m grateful for the opportunities I’ve had in the (nearly) three years since I’ve been at UCSC.
Before coming to Phenomena, where have you been writing, and what have you been writing about?
My first reporting job was as the astronomy reporter at Science News, based in Washington, D.C. When I moved back to California, I started writing for WIRED, where I report on the life and materials sciences – from giant spiders through marine mammals to materials that change color when they stretch. I’m also working on astronomy features for the news section of the Proceedings of the National Academy of Sciences. While at UCSC, I interned at Nature and wrote about everything from human ancestors to rogue planets, and also spent two quarters interning at Bay Area newspapers, which I loved.
I’m really looking forward to getting back on the astronomy news beat at Phenomena!
What can we expect from the blog?
A thoughtful exploration of the science probing everything that isn’t on planet Earth. I’m aiming for a mix of stories – many about recently published research, but also some excursions into astro history, perhaps some profiles of scientists, some obsession-driven posts. And lots of great photos. Maybe I’ll even open up the Frank Drake archives from time to time. As I get going, I’d be interested in hearing feedback from readers. Which stories or topics are the most satisfying?
Blogging is an excuse for writers to put their obsessions on public display. What obsesses you?
Above all, words. Using language to express ideas that are slippery, to describe something intangible or relay a visceral experience, in a way that leaps off pages or screens – it’s like assembling a jigsaw puzzle. Words are powerful and meant to be used properly.
My other obsessions tend to be fairly transient in duration – I’ll plunge into a subject or idea for a short but utterly immersive period, then slip quietly out and move on to the next. That said, some obsessions do recur. In astronomy? Iapetus, a cranky, bizarre moon of Saturn. Type 1a supernovas – what in the world is going on with those? Ancient observatories, those sites where scientists and philosophers convened to observe the skies. And of course, exoplanets. Also exomoons. For some reason, I really, really love the idea of exomoons.
In life? Ballet. Champagne. I love a good glass of bubbly more than just about anything.
(What are your obsessions, Carl?) [Ed. note: These days, oxygen, for some reason.]
You’ve written about some strange science—what’s the weirdest thing you’ve written about so far?
The non-profit Public Laboratory for Open Technology and Science (Public Lab) previously won a Knight News Challenge in 2011 and received $500,000 to fund a tool kit and online community for citizen-based, grassroots data gathering and research. The second Knight News Challenge the group won, a $350,000 Knight award focused on health data, will allow the group to build and deploy inexpensive technologies for monitoring.
Connections between the hacker culture of the 1970s and emerging DIY science continue with the funding of the Homebrew Sensing Project. Born of Public Lab, this project aims to create low-cost sensor technologies for environmental research and monitoring. Following its namesake’s (the homebrew computer club) lead, this project’s participant composition complicates distinctions between expert and hobbyist or amateur.
The three individuals leading up the project are Shannon Dosemagen, Jeffrey Warren, and Mathew Lippincott. I was able to chat with Dosemagen, also a co-Founder of Public Lab, via email. Situating the Homebrew Sensing Project within the Public Lab’s effort tells us a lot about the motivations behind the project. “Public lab,” Dosemagen writes, “isn’t just a nonprofit that creates tools, we’re interested in creating a community.” Connecting with community organizations, NGOs, and research institutions they have created an extensive network that helps connect with a community and connect communities.
Connecting communities and providing a space for them to interact, Public Lab provides what Dosemagen describes as “a space where people with different expertise can interact.” This is a particularly important interaction among different kinds of expertise, including specialized technical as well as local knowledge, and reflects the efforts of Public Lab, Dosemagen tells us, to “recognize that not only researchers linked to academic institutions bring value and expertise to projects such as this, but that everyone can bring something to the table through the experience and knowledge sets that they have.”
Engagement among experts is demonstrated through the “barn raising” activities, events where members of the community come together to create something (be it tool or tutorials), Public Lab undertakes. Winning a another Knight Challenge means that the group can continue such efforts with the Homebrew Sensing Project. This project aims to address growing concerns about exposure to various human-made hazards and the associated risks, including health risks. To do this, the group wants to create inexpensive tools that can be used with mobile devices, allowing community members to take readings and analyze the information without the high costs associated with traditional lab testing. The group will undertake these efforts by refining their hardware and software platforms and developing new ones. As well, Dosemagen writes that a “portion of this grant will go towards supporting an outreach role and community partners,” which means that further community building and crossing of boundaries between communities will be part of this important initiative. If you’re interested in learning more about Public Lab or following this project you can find more information about the project in their news release.
Public Lab’s Homebrew Sensing Project extends their work on a DIY spectrometry project. The initial project, Dosemagen noted, began a few years ago and publicly “launched in 2012 with a Kickstarter” and the results have been impressive. To date, she tells us, Public Lab has ”over 2,000 accounts on SpectralWorkbench.org, over 14,000 spectral samples uploaded, [and] 750 members in the spectrometry Google Group.” In addition to all of this work, the group has “shipped 3,500 spectrometers worldwide that range between a price point of $10 and $70,” with the price point being a particularly notable feature in how accessible that is when compared with traditional spectrometers that typically begin at several thousand dollars.
IMAGINE a world where all people are able to understand, value, and participate in science. This is the vision that inspires the Citizen Science Association (CSA), an emerging organization that will support organizers advancing scientific research that involves the public. It isn’t so hard to do. There are many prominent ornithological programs that engage bird watchers in research. These are not the only ones. There have been many scientific contributions of amateur astronomers. These are not the only ones. Right now you could look at almost any scientific discipline, and if you look deeply enough and carefully enough you’re going to see some aspects of citizen science happening.
“The CSA is offering free inaugural membership for 2014 to grow, unite, and guide this global community of practice focused on public participation in citizen science. The CSA recognizes all forms of citizen science and focuses on building the community of practice involving those who organize volunteers. Whether organizers are scientists, educators, data managers, technology specialists, evaluators, or enthusiastic volunteers, the CSA welcomes those who want to benefit form a network based on the diverse practices of citizen science.”
The work of building the association is just beginning to take shape. While four committees have begun to coordinate planning, the Association is soliciting the involvement and leadership of future members. Membership requires no financial contribution at this point, and people receive complementary membership by completing a short survey. According to the CSA, this survey will help the Association understand the diverse needs, interests, and expertise of the citizen science community, gauge the energy, initiative, and commitment to CSA activities, and inspire potential funders.
Documenting the characteristics of the incoming membership is crucial because Citizen Science is a remarkably diverse field in terms of disciplines, sectors, and communities engaged. Panelists at the AAAS meeting included an astronomer, a neuroscientist, an ornithologist, an unusual combination for a single panel. It sounded so much like a ‘walked-into-a-bar’ joke that these practitioners jested they should crowdsource for the best punchline. Even though the research topics differed, the methods used and the challenges faced are similar. The panel also included professionals involved in computer science, informatics, human-computer interaction, and education. These are some of the fields enabling innovations in how citizen science is put into practice.
The CSA will foster exchange, collaboration, and professional development across the compelling diversity in order to support parallel practices in various fields. To this end, the Association will establish an open-access, peer-reviewed journal dedicated to advances in the theory and practice of citizen science. The Association will sponsor international conferences that disseminate findings and innovations and act as networking events. By building a digital community of practice, and compiling tools and resources to further best practices in the field, the CSA hopes to serve as an umbrella organization, drawing members from diverse communities including Scistarter, The Citizen Science Alliance, and the European Citizen Science Association (ECSA).
Early support for the association is generously provided by National Geographic, the Cornell Lab of Ornithology, the Data Observation Network for Earth (DataONE), The Woodrow Wilson International Center for Scholars, the Schoodic Institute, and the National Ecological Observatory Network (NEON).
These organizations have common hopes for a world full of people engaged in citizen science. You may say these organizations are dreamers. If you are organizing citizen science activities, you are not the only one. With over 1,300 members already, we hope someday you’ll join us!
Image credit: Kelly Hills
This post is co-authored by Anne Bowser, a graduate Research Assistant in the Commons Lab, a PhD student at the University of Maryland’s College of Library and Information Science, and member of the Steering Committee of the Citizen Science Association.
This is part one of a three part post. Parts two and three have now been posted.
The academic paper is old - older than the steam engine, the pocket watch, the piano, and the light bulb. The first journal, Philosophical Transactions, was published on March 6th, 1665. Now that doesn’t mean that the journal article format is obsolete - many inventions much older are still in wide use today. But after a third of a millennium, it’s only natural that the format needs some serious updating.
When brainstorming changes, it may be useful to think of the limitations of ink and paper. From there, we can consider how new technologies can improve or even transform the journal article. Some of these changes have already been widely adopted, while others have never even been debated. Some are adaptive, using the greater storage capacity of computing to extend the functions of the classic journal article, while others are transformative, creating new functions and features only available in the 21st century.
The ideas below are suggestions, not recommendations - it may be that some aspects of the journal article format are better left alone. But we all benefit from challenging our assumptions about what an article is and ought to be.
The classic journal article format cannot convey the full range of information associated with an experiment.
Until the rise of modern computing, there was simply no way for researchers to share all the data they collected in their experiments. Researchers were forced to summarize: to gloss over the details of their methods and the reasoning behind their decisions and, of course, to provide statistical analyses in the place of raw data. While fields like particle physics and genetics continue to push the limits of memory, most experimenters now have the technical capacity to share all of their data.
Many journals have taken to publishing supplemental materials, although this rarely encompasses the entirety of data collected, or enough methodological detail to allow for independent replication. There are plenty of explanations for this slow adoption, including ethical considerations around human subjects data, the potential to patent methods, or the cost to journals of hosting this extra materials. But these are obstacles to address, not reasons to give up. The potential benefits are enormous: What if every published paper contained enough methodological detail that it could be independently replicated? What if every paper contained enough raw data that it could be included in meta-analysis? How much of meta-scientific work is never undertaken, because it's dependent on getting dozens or hundreds of contact authors to return your emails, and on universities to properly store data and materials?
Providing supplemental material, no matter how extensive, is still an adaptive change. What might a transformative change look like? Elsevier’s Article of the Future project attempts to answer that question with new, experimental formats that include videos, interactive models, and infographics. These designs are just the beginning. What if articles allowed readers to actually interact with the data and perform their own analyses? Virtual environments could be set up, lowering the barrier to independent verification of results. What if authors reported when they made questionable methodological decisions, and allowed readers, where possible, to see the results when a variable was not controlled for, or a sample was not excluded?
The classic journal article format is difficult to organize, index or search.
New technology has already transformed the way we search the scientific literature. Where before researchers were reliant on catalogues and indexes from publishers, and used abstracts to guess at relevance, databases such as PubMed and Google Scholar allow us to find all mentions of a term, tool, or phenomena across vast swathes of articles. While searching databases is itself a skill, its one that allows us to search comprehensively and efficiently, and gives us more opportunities to explore.
Yet old issues of organization and curation remain. Indexes used to speed the slow process of skimming through physical papers. Now they’re needed to help researchers sort through the abundance of articles constantly being published. With tens of millions of journal articles out there, how can we be sure we’re really accessing all the relevant literature? How can we compare and synthesize the thousands of results one might get on a given search?
Special kinds of articles - reviews and meta-analyses - have traditionally helped us synthesize and curate information. As discussed above, new technologies can help make meta-analyses more common by making it easier for researchers to access information about past studies. We can further improve the search experience by creating more detailed metadata. Metadata, in this context, is the information attached to an article which lets us categorize it without having to read the article itself. Currently, fields like title, author, date, and journal are quite common in databases. More complicated fields less often adopted, but you can find metadata on study type, population, level of clinical trial (where applicable), and so forth. What would truly comprehensive metadata look like? Is it possible to store the details of experimental structure or analysis in machine-readable format - and is that even desirable?
What happens when we reconsider not the metadata but the content itself? Most articles are structurally complex, containing literature reviews, methodological information, data, and analysis. Perhaps we might be better served by breaking those articles down into their constituent parts. What if methods, data, analysis were always published separately, creating a network of papers that were linked but discrete? Would that be easier or harder to organize? It may be that what we need here is not a better kind of journal article, but a new way of curating research entirely.
When it comes to opening up your work there is, ironically, a bit of a secret. Here it is: being open - in open science, open source software, or any other open community - can be hard. Sometimes it can be harder than being closed.
In an effort to attract more people to the cause, advocates of openness tend to tout its benefits. Said benefits are bountiful: increased collaboration and dissemination of ideas, transparency leading to more frequent error checking, improved reproducibility, easier meta-analysis, and greater diversity in participation, just to name a few.
But there are downsides, too. One of those is that it can be difficult to do your research openly. (Note here that I mean well and openly. Taking the full contents of your hard drive and dumping it on a server somewhere might be technically open, but it’s not much use to anyone.)
How is it hard to open up your work? And why?
Closed means privacy.
In the privacy of my own home, I seldom brush my hair. Sometimes I spend all day in my pajamas. I leave my dirty dishes on the table and eat ice cream straight out of the tub. But when I have visitors, or when I’m going out, I make sure to clean up.
In the privacy of a closed access project, you might take shortcuts. You might recruit participants from your own 101 class, or process your data without carefully documenting which steps you took. You’d never intentionally do something unethical, but you might get sloppy.
Humans are social animals. We try to be more perfect for each other than we do for ourselves. This makes openness better, but it also makes it harder.
Two heads need more explanation than one.
As I mentioned above, taking all your work and throwing it online without organization or documentation is not very helpful. There’s a difference between access and accessibility. To create a truly open project, you need to be willing to explain your research to those trying to understand it.
There are numerous routes towards sharing your work, and the most open projects take more than one. You can create stellar documentation of your project. You can point people towards background material, finding good explanations of the way your research methodology was developed or the math behind your data analysis or how the code that runs your stimulus presentation works. You can design tutorials or trainings for people who want to run your study. You can encourage people to ask questions about the project, and reply publicly. You can make sure to do all the above for people at all levels - laypeople, students, and participants as well as colleagues.
Even closed science is usually collaborative, so hopefully your project is decently well documented. But making it accessible to everyone is a project in itself.
New ideas and tools need to be learned.
As long as closed is the default, we’ll need to learn new skills and tools in the process of becoming open, such as version control, format conversion and database management.
These skills aren’t unique to working openly. And if you have a good network of friends and colleagues, you can lean on them to supplement your own expertise. But the fact remains that “going open” isn’t as easy as flipping a switch. Unless you’re already well-connected and well-informed, you’ll have a lot to learn.
People can be exhausting.
Making your work open often means dealing with other people - and not always the people you want to deal with. There are the people who mean well, but end up confusing, misleading, or offending you. There are the people who don’t mean well at all. There are the discussions that go off in unproductive directions, the conversations that turn into conflicts, the promises that get forgotten.
Other people are both a joy and a frustration, in many areas of life beyond open science. But the nature of openness assures you’ll get your fair share. This is especially true of open science projects that are explicitly trying to build community.
It can be all too easy to overlook this emotional labor, but it’s work - hard work, at that.
There are no guarantees.
For all the effort you put into opening up your research, you may find no one else is willing to engage with it. There are plenty of open source software projects with no forks or new contributors, open science articles that are seldom downloaded or science wikis that remain mostly empty, open government tools or datasets that no one uses.
Open access may increase impact on the whole, but there are no promises for any particular project. It’s a sobering prospect to someone considering opening up their research.
How can we make open science easier?
We can advocate for open science while acknowledging the barriers to achieving it. And we can do our best to lower those barriers:
Forgive imperfections. We need to create an environment where mistakes are routine and failures are expected - only then will researchers feel comfortable exposing their work to widespread review. That’s a tall order in the cutthroat world of academia, but we can begin with our own roles as teachers, mentors, reviewers, and internet commentators. Be a role model: encourage others to review your work and point out your mistakes.
Share your skills as well as your research. Talk about your experiences opening up your research with colleagues. Host lab meetings, department events, and conference panels to discuss the practical difficulties. If a training, website, or individual helped you understand some skill or concept, recommend widely. Talking about the individual steps will help the journey seem less intimidating - and will give others a map for how to get there.
Recognize the hard work of others with words and, if you can, financial support. Organization, documentation, mentorship, community management. These are areas that often get overlooked when it comes to celebrating scientific achievement - and allocating funding. Yet many open science projects would fail without leadership in these areas. Contribute what you can and support others who take on these roles.
Collaborate. Open source advocates have been creating tools to help share the work involved in opening research - there’s Software Carpentry, the Open Science Framework, Sage Bionetworks, and Research Compendia, just to name a few. But beyond sharing tools, we can share time and resources. Not every researcher will have the skillset, experience, or personality to quickly and easily open up their work. Sharing efforts across labs, departments and even schools can lighten the load. So can open science specialists, if we create a scientific culture where these specialists are trained, utilized and valued.
We can and should demand open scientific practices from our colleagues and our institutions. But we can also provide guidelines, tools, resources and sympathy. Open science is hard. Let’s not make it any harder.
Reproducibility: It's not just good science, it's MANDATORY
The reproducibility@XSEDE workshop is a full-day event scheduled for Monday, July 14, 2014 in Atlanta, Georgia.
The workshop will take place in conjunction with XSEDE14,
the annual conference of the Extreme Science and Engineering Discovery Environment,
and will feature an interactive,
open-ended,
discussion-oriented agenda focused on reproducibility in large-scale computational science.
We hope to help promote a culture of reproducibility within the broad community of stakeholders
connected to computation-enabled research,
and expect our work to lead to recommendations address to this community.
This event will build on the 2009 Yale Data and Code Sharing Roundtable,
which culminated in a declaration
"demanding a resolution to the credibility crisis from the lack of reproducible research in computational science".
To find out more,
please see the workshop website,
or send questions to reproducibility@xsede.org.
Originally posted 2014-03-07 by Greg Wilson in Announcements.
For those looking for quite durable fountain pen ink. I use several of these, and they are awesome.
Using a new ink for the first time is always an exciting experience - that's what Ink Drop is all about. However, not every ink leaves a lasting impression, meaning that it will last permanently on the paper. These inks are all permanent and will outlast any reasonable effort to remove them! Here are the five inks we chose for the March 2014 Ink Drop, themed Lasting Impression:
Noodler's Bad Green Gator is part of the Warden's Series, meaning it is ideal for check-writing and fraud-resistance. It is one of the few highly water-resistant green inks that we're aware of.
Platinum Carbon Black is a pigmented black ink, chosen as a favorite black ink by many artists. It is definitely permanent once it dries on the page.
Rohrer & Klingner Salix and Scabiosa inks go hand-in-hand. Both are modern iron-gall inks and will last a long time on paper! The blue and purple colors, respectively, are muted and quite pleasing to the eye.
In keeping with the kind of week I've been having, I present to you the Eviscerati Coffee Consumption Scale, or ECCS. ECCS is designed to measure critical levels of coffee consumption, which in turn is used to evaluate other environmental conditions which may be influencing said levels of coffee consumption.
ECCS Levels are described below. Check with your employer to determine if your company is adequately prepared to respond to these scenarios:
"Don't scientists all learn how to program these days as part of their education?"
HHAHAHAHAHAHAHAHAHAHAHAHA NO
I was interviewed about Software Carpentry earlier this week,
and the interviewer's second question was,
"Don't scientists all learn how to program these days as part of their education?"
The answer, even today, is "no":
the average scientist might know more about calculus and statistics
than someone who did a degree in marketing or graphic design,
but she probably doesn't know any more about how to build software
and share data on the web.
Brent Gorda and I started Software Carpentry in 1998 to fix that.
Our goal was to teach our colleagues
the equivalent of basic lab skills for scientific computing
so that they could get more done in less time and with less pain.
As the project grew,
I realized that this problem wasn't specific to scientists:
almost everyone who uses the web spends hours or days doing things
that a few simple programs could do for them
faster and more reliably.
Since Software Carpentry became part of the Mozilla Science Lab last summer,
we've been thinking about how we can turn our training into
a starting point for deeper involvement in open, web-enabled science.
Our long-term goal is to change the way science is done;
it turns out that
teaching people the skills they need to make changes themselves
is more compelling than preaching open science at them,
and more likely to inspire them to create things that we would never have thought of.
What we haven't been doing is following through
to show them where to go and what to do next.
Of course,
lots of other groups are trying to do things like this for other audiences.
In particular,
Mozilla's Webmaker team is
a global community dedicated to teaching digital skills.
Their focus is digital literacy:
they explore, tinker, and create to help people learn how to build a web that's open and collaborative.
Like us,
their goal isn't to create the next generation of professional programmers;
instead,
we want to democratize these skills
so that everyone knows enough to make what they need to solve their day-to-day problems,
whatever those may be.
Last year,
Webmaker ran its first training session for the mentors
who actually do this kind of grassroots teaching.
They're scaling up their efforts this year in a big way:
they hope to train 1000 mentors in the coming months,
which is almost ten times as many people as we have in our entire instructor pool.
Their road map includes a list of upcoming events,
all of which are intended to lower barriers to entry
so that everyone can make, create, remix and build on the web.
Superficially,
Webmaker and Software Carpentry teach different skills—Webmaker
focuses on front-end technologies like HTML5 and CSS,
while Software Carpentry's focus is the back-end tools needed to move data around and analyze it—but
under the hood,
what both really teach is
how to think like the web.
While specific tools come and go,
basic ideas like remixing instead of rewriting
and sharing instead of just showing
are here to stay,
and those are what make the difference.
We believe that we need to build capacity in order to strengthen and accelerate open research.
We also believe that open research is just one special case of "open".
Over the next year,
we'll be looking at how we can engage Software Carpentry's learners in larger efforts,
both in science and in society at large.
If you'd like to help us, or Webmaker,
please get in touch.
Parasites can take many forms. Just this week, I’ve written about a giant virus that reproduces inside amoebae (and has survived being frozen 30,000 years in permafrost), along with a wasp that performs brain surgery to zombify hosts for its young. Viruses and wasps are radically different organisms–some would say that viruses don’t even deserve the label of organism. And they make use of their hosts in different ways. The virus sits inside a cell, manipulates its biochemistry to build virus proteins and DNA. The wasp, on the other hand, sips fluids inside a still-living roach, and builds its own proteins and DNA–and then becomes a free-living creature that can climb out of its host and fly away.
So why are they both parasites? The answer lies beyond the details of anatomy and molecules. It’s all about relationships.
Species can have all sorts of influences on each other. They can eat or be eaten, they can pollinate or steal pollen. But there’s one yardstick that scientists can use to measure all the variety in these interactions: the change that one species has on how many offspring the other can have. By that measurement, the differences between giant viruses and brain-surgeon wasps melt away. Each one is a disaster for its partner species. The viruses multiply inside amoebae until they burst. The roach lives until its wasp parasite is ready to depart. In each case, the relationship is good for the parasite (more offspring) and bad for the host (fewer).
When scientists look at life with this definition in mind, they can see a lot of parasites that might not look like parasites. We don’t think of birds as parasites–they’re too beautiful and not in the least bit creepy. But when a cuckoo pushes out the eggs of a reed warbler and puts her own in their place, and when the cuckoo chicks use all sorts of tricks to fool the reed warbler to feed them as if they were its own, we are seeing another parasite at work.
In the journal BMC Evolutionary Biology, a team of scientists in Finland describe another kind of parasite–one that doesn’t steal food or protein synthesis or even parental care. In the words of the scientists, these are “information parasites.”
Top: Great tit. Bottom: Pied flycatcher. Flickr: http://flic.kr/p/7o6KjK http://flic.kr/p/dGnDRc
These information parasites are, once again, birds. Lovely birds, in fact, known as pied flycatchers. And their victims are another species of bird, the great tit (twelve-year-olds at heart are allowed a few moments to get sniggers out of their system).
The pied flycatchers and great tits, both found across much of Europe, have evolved to the point where their existence is quite similar. They eat a lot of the same kinds of food, get killed by the same predators, and even choose the same sites for their nests. This similarity leads to a fair amount of competition, sometimes quite violent. If a bird from one species flies into a crevice to check out a potential nest spot, only to find the other species there, the two birds will fight–sometimes to the death.
The two species aren’t identical, though, and there a couple differences that are particularly intriguing.The great tits build their nests earlier in the year, and the pied flycatchers have a habit of paying visits to great tit nests before building their own.
In recent years, the Finnish researchers have found a likely reason for these visits. The pied flycatchers are gathering intel. They inspect the nests of great tits to help them decide where they will make their own nests. One piece of information they’re interested in is the number of eggs are in a great tit’s nest. If a nest is loaded with eggs, it’s probably a good place for a pied flycatcher to make its own nearby.
The great tit suffers for letting the pied flycatcher get this information. Now a rival bird sets up house on the same territory and starts to compete for the same food. The researchers have found that great tits that attract these neighbors end up with fewer nestlings as a result. The pied flycatchers, on the other hand, have more success in reproducing because they build their nests on good real estate. One species benefits, and one suffers. But the benefit doesn’t come from cockroach innards or cell proteins. The pied flycatcher is stealing information.
Once parasites evolve a strategy for taking advantage of a host, the host generally evolves defenses. Immune systems recognize pathogens and destroy them. The hosts of some wasps will fly away or fight off their attacker. If pied flycatchers really were information parasites, then great tits might evolve defenses to safeguard their information.
When great tits are laying eggs, they search for sheep hair and other materials to keep the eggs covered. It’s not clear why they bother. You could imagine that the covering is a blanket to keep the eggs warm. But the birds don’t bother to keep the eggs covered once they’re all laid and the embryos start to develop. So it’s possible that they’re doing something else with the hair.
One thing that the hair does is hide the eggs. The Finnish scientists wondered if the great tits use hair to hide information from flycatchers. To find out, they ran an experiment.
They put a decoy of a pied flycatcher five meters from great tit nests and played a recording of a pied flycatcher singing for five minutes. The next day, they collected the hair in the nests. The scientists then ran the same experiment, but with decoys of cedar waxwings–birds that live alongside great tits but don’t compete with them.
The great tits responded to pied flycatchers by adding over 40% more hair on top of their eggs than they would otherwise. The scientists concluded that the birds hide the eggs when pied flycatchers show up so that the pied flycatchers won’t see just how well the great tits are doing. Seeing what looks like a meager nest, the pied flycatchers will be more likely to move on.
When hosts evolve defenses against parasites, parasites sometimes evolve counter-defenses. When flu viruses infect a cell, for example, the cell can respond by making an anti-viral protein called interferon. The interferon guides the cell to chop up the invading virus genes. But flu viruses have proteins that block interferon.
Do information parasites have their own counter-defenses? The scientists don’t offer any solid scientific evidence in their new report, but they do mention that they’ve seen something odd. They’ve seen pied flycatchers sneak into great nests and pull hair from the eggs. That may seem like a pointless exercise, since pied flycatchers don’t use hair on their own nests. It’s possible that they’re just trying to steal some reliable information.
When I first started writing my book on the triumph of parasites, I burrowed into the science and was stunned at how many ways there were to be a parasite. Eventually, the bottom just fell out. This is the first time that I’ve become aware of the concept of “information parasites,” but I suspect it won’t be the last.
[Update: Correction--reed warblers are hosts of cuckoos, not cowbirds]
Fifteen months ago, Virginia Hughes, Brian Switek, Ed Yong, and I joined National Geographic to form Phenomena. I’m delighted that our circle is now expanding. Starting today, science writer Nadia Drake will be writing “No Place Like Home.” I’ve followed Nadia’s work for the past couple years, but I’ve never had the chance to talk to her. To celebrate her debut, I asked her some questions about her past and future.
