The Web of Science ranking of the world’s most highly-cited scientists was released this morning, telling us who makes up the top 1 percent of the world’s scientists. These are the authors of influential papers that other scientists point to when making their arguments.
EDITOR’S NOTE! — Web of Science shared last year’s data! We apologize. List below is now corrected, changes to copy in bold. We’re so sorry.
Twenty-three of the citation laureates are Duke scholars or had a Duke affiliation when the landmark works were created over the last decade.
A couple of these Duke people disappeared from this year’s list, but we’re still proud of them.
Dan Scolnic of Physics returns as our lone entry in Space Science, which just makes Duke sound cooler all around, don’t you think?
This is a big deal for the named faculty and an impressive line on their CVs. But the selection process weeds out “hyper-authorship, excessive self-citation and anomalous citation patterns,” so don’t even think about gaming it.
Fifty-nine nations are represented by the 6,636 individual researchers on this year’s list. About half of the citation champions are in specific fields and half in ‘cross-field’ — where interdisciplinary Duke typically dominates. The U.S. is still the most-cited nation with 36 percent of the world’s share, but shrinking slightly. Mainland China continues to rise, claiming second place with 20 percent of the cohort, up 2.5 percent from just last year. Then, in order, the UK, Germany and Australia round out the top five.
In fact, five Duke NUS faculty made this year’s list: Antonio Bertoletti, Derek Hausenloy and Jenny Guek-Hong Low for cross-field; Carolyn S. P. Lam for clinical medicine, and the world famous “Bat Man,” Lin-Fa Wang, for microbiology.
From tiny flies, Duke researchers are finding new clues to how the brain sets up its circuitry.
In her time at Duke, Khanh Vien figures she’s dissected close to 10,000 fly brains. For her PhD she spent up to eight hours each day peering at baby flies under the microscope, teasing out tiny brains a fraction the size of a poppy seed.
“I find it very meditative,” she said.
Vien acknowledges that, to most people, fruit flies are little more than a kitchen nuisance; something to swat away. But to researchers like her, they hold clues to how animal brains — including our own — are built.
While the human brain has some 86 billion neurons, a baby fruit fly’s brain has a mere 3016 — making it millions of times simpler. Those neurons talk to each other via long wire-like extensions, called axons, that relay electrical and chemical signals from one cell to the next.
Vien and other researchers in Professor Pelin Volkan’s lab at Duke are interested in how that wiring gets established during the fly’s development.
By analyzing a subset of neurons responsible for the fly’s sense of smell, the researchers have identified a protein that helps ensure that new neurons extend their axons to the correct spots in the olfactory area of the young fly’s brain and not elsewhere.
Because the same protein is found across the animal kingdom, including humans, the researchers say the work could ultimately shed light on what goes awry within the brains of people living with schizophrenia and other mental illnesses.
Their findings are published in the journal iScience.
Khanh Vien earned her PhD in developmental and stem cell biology in Professor Pelin Volkan’s lab at Duke.
Note: Each year, we partner with Dr. Amy Sheck’s students at the North Carolina School of Science and Math to profile some unsung heroes of the Duke research community. This is the second of eight posts.
Meet a star in the realm of academic medicine – Dr. Kyle Todd Mitchell!
A man who wears many hats – a neurologist with a passion for clinical care, an adventurous researcher, and an Assistant Professor of Neurology at Duke – Mitchell finds satisfaction in the variety of work, which keeps him “driven and up to date in all the different areas.”
Dr. Mitchell holds a deep brain stimulation device.
Dr. Mitchell’s educational journey is marked by excellence, including a fellowship at the University of California San Francisco School of Medicine, a Neurology Residency at Washington University School of Medicine, and an M.D. from the Medical College of Georgia. Beyond his professional accolades, he leads an active life, enjoying running, hiking, and family travels for rejuvenation.
Dr. Mitchell’s fascination with neurology ignited during his exposure to the field in medical school and residency. It was a transformative moment when he witnessed a patient struggling with symptoms experience a sudden and remarkable improvement through deep brain stimulation. This therapy involves the implantation of a small electrode in the brain, offering targeted stimulation to control symptoms and bringing relief to individuals grappling with the challenges of Parkinson’s Disease.
“You don’t see that often in medicine, almost like a light switch, things get better and that really hooked me,” he said. The mystery and complexity of the brain further captivated him. “Everything comes in as a bit of a mystery, I liked the challenge of how the brain is so complex that you can never master it.”
Dr. Mitchell’s research is on improving deep brain stimulation to alleviate the symptoms of Parkinson’s disease, the second most prevalent neurodegenerative disorder, which entails a progressive cognitive decline with no cure. Current medications exhibit fluctuations, leading to tremors and stiffness as they wear off. Deep brain stimulation (DBS), FDA-approved for over 20 years, provides a promising alternative.
Dr. Mitchell’s work involves creating adaptive algorithms that allow the device to activate when needed and deactivate so it is almost “like a thermostat.” He envisions a future where biomarkers recorded from stimulators could predict specific neural patterns associated with Parkinson’s symptoms, triggering the device accordingly. Dr. Mitchell is optimistic, stating that the “technology is very investigational but very promising.”
A key aspect of Dr. Mitchell’s work is its interdisciplinary nature, involving engineers, neurosurgeons, and fellow neurologists. Each member of the team brings a unique expertise to the table, contributing to the collaborative effort required for success. Dr. Mitchell emphasizes, “None of us can do this on our own.”
Acknowledging the challenges they face, especially when dealing with human subjects, Dr. Mitchell underscores the importance of ensuring research has a high potential for success. However, the most rewarding aspect, according to him, is being able to improve the quality of life for patients and their families affected by debilitating diseases.
Dr. Mitchell has a mindset of constant improvement, emphasizing the improvement of current technologies and pushing the boundaries of innovation.
“It’s never just one clinical trial — we are always thinking how we can do this better,” he says.
The pursuit of excellence is not without its challenges, particularly when attempting to improve on already effective technologies. Dr. Mitchell juggles his hats of being an educator, caregiver, and researcher daily. So let us tip our own hats and be inspired by Dr. Mitchell’s unwavering dedication to positively impact the lives of those affected by neurological disorders.
Guest post by Amy Lei, North Carolina School of Science and Math, Class of 2025.
It’s that most wonderful time of the year: The official list of Clarivate’s Most Highly Cited Scientists came out this morning. Scientists all over the world came racing down the stairs in their PJs to see if Clarivate had left a treat under the tree for them.
L-R: Odgers, Scolnic, Dong, Hernandez, Harrington, Smith, Ostrom and Lopes.
Good news – there are 30 Duke names on the list!
Being highly cited is a point of pride for researchers. To make the cut, a paper has to be ranked in the top 1 percent for its field for the last decade. Clarivate’s “Institute for Scientific Information” crunches all the numbers.
Mostly, the names on this year’s list of Duke authors are the usual titans. Oddly, some returning names have changed categories since last year — but that’s okay, they’re still important.
And there are three fresh faces: Cardiologist Renato Delascio Lopes, MD Ph.D., who studies atrial fibrillation; David R. Smith Ph.D. of physics and electrical engineering, who’s a leading light in the field of metamaterials; and Dan Scolnic Ph.D. of physics, who’s measuring the expansion of the universe and trying to figure out the dark energy that apparently drives it.
Five of the Duke names on the list this year are co-authors in the Terrie Moffit and Avshalom Caspi lab, a hugely influential group of psychologists and social scientists. Honnalee Harrington, Renate Houts, Caspi, Moffitt, and UC Irvine professor and Duke adjunct Candice Odgers are studying human development from cradle to grave using two cohorts of life-long study participants in New Zealand and England.
Two other longitudinal scientists, Jane Costello and William Copeland of the Great Smoky Mountains Study, are also on the list.
There are 6,938 highly cited scientists this year, from 69 countries and regions. Several appear in more than one division. The United States still dominates with 38 percent of the honorees, but Chinese scientists are on the rise at 16 percent.
The most highly cited Duke authors are:
Biology and Biochemistry
Charles A. Gersbach
Clinical Medicine
Christopher Bull Granger
Adrian F. Hernandez
Renato D. Lopes
Cross-Field
Stefano Curtarolo
Xinnian Dong
HonaLee Harrington
Renate Houts
Tony Jun Huang
Ru-Rong Ji
Robert Lefkowitz
Jason Locasale
David B. Mitzi
Christopher B. Newgard
Michael J. Pencina
Bryce B. Reeve
Pratiksha I. Thakore
Mark R. Wiesner
Microbiology
Barton F. Haynes
Neuroscience and Behavior
Quinn T. Ostrom
Pharmacology and Toxicology
Evan D. Kharasch
Physics
David R. Smith
Plant and Animal Science
Sheng Yang He
Psychiatry and Psychology
Avshalom Caspi
E. Jane Costello
Terrie E. Moffitt
Space Science
Dan Scolnic
Duke Affiliated:
Cross Field
Po-Chun Hsu – University of Chicago, Adjunct Assistant Professor in Mechanical Engineering and Materials Science at Pratt School of Engineering
Candice Odgers, UC Irvine, Adjunct at Duke
Environment and Ecology
Robert B. Jackson, Stanford University, Adjunct Professor of Earth and Ocean Science at Nicholas School of the Environment
William E. Copeland, University of Vermont, adjunct in psychiatry and behavioral sciences, School of Medicine.
It’s a miracle that people aren’t constantly getting into car accidents.
Whizzing by at 65 miles per hour in a car, the brain rapidly decodes millions of photons worth of information from the eyes, and then must use that information to instantly figure out where it is and where it needs to go. Is that a pedestrian approaching the sidewalk or a mailbox? Do I need to take this offramp or the next one? What color is the traffic light up ahead?
Was it a stop sign? I didn’t notice. (US Marine Corps, via Wikimedia Commons.)
Most motorists, miraculously, get to work or school without a scratch.
After nearly a decade worth of research, Duke scientists have figured out how the brain juggles all of this so effortlessly and tirelessly in a surprisingly inefficient way: by making quick, low-level models of the world to help form a clear view of the road ahead. The new findings expand the understanding of how the brain sees the world, and might one day help clinicians better understand what goes awry in people with psychiatric issues defined by perceptual problems, like schizophrenia.
Most neuroscientists think our brain cells figure out what we’re looking at by quickly comparing what’s in front of us to past experience and prior knowledge. Like a biological detective, they might determine you are looking at a house by using past experiences of neighborhoods you have been in and houses you have lived in. Enthusiasts of this Bayesian theory have long reasoned that these quick, probability-based analyses are what help people see a stable world despite sensory and motor noise from eye movement and constant environmental uncertainties, like a glare from the sun or a backdrop of a moving crowd.
A recent paper in the online journal eNeuro however, suggests neuroscientists have overlooked a simpler explanation: that brain cells are also rapidly decoding a constant stream of information from the eyes using simple pattern recognition, like determining you’re looking at a house from the visual evidence of windows, a tall rectangular opening, and a manicured lawn.
Marc Sommer
“That discriminative model has some advantages because it’s really quick, logical, and flexible,” said Marc Sommer, Ph.D., a professor of biomedical engineering at Duke and senior author of the new study. “You can learn the boundaries between decisions, and you can apply all sorts of statistical pattern-matching at a very low level. You don’t have to create a model of the world, which is a big task for a brain.”
Sommer initially hoped to confirm the general consensus in neuroscience—that the brain builds on a working model of the world instead of recognizing patterns from the ground up. But after putting the Bayesian theory to the test with Duke neurobiology alumna Divya Subramanian, Ph.D., now a postdoctoral researcher at the National Institutes for Health, he’s hoping to extend their newfound results to other processes in the brain.
To ferret out which theory would hold up, Sommer and Subramanian recruited 45 adults for an eye test. Participants looked at a computer screen and were quizzed about where a shape on the screen moved to, or if it moved at all. Throughout the test, Subramanian subtly made movements trickier and less obvious to tease out how the brain compensates when there is increasing uncertainty, from changing the contrast of the shape to the shape itself.
After scoring the eye exams, Sommer and Subramanian were surprised to find that the brain didn’t solely rely on a Bayesian approach.
People scored worse when the visual noise was dialed up, but only when they were asked where the target moved to. Test scores were mostly unaffected with noisier scenes when people were asked if a shape moved on the screen, suggesting that—to the team’s surprise—people don’t always use prior experiences when they are more uncertain about what they are seeing, like our biological detective would.
The team spent the next several years parsing through results and replicating their findings “three times to believe it,” Subramanian said, but it always led them to the same conclusion: for some forms of perception, brain cells stick to low-level patterns to draw conclusions about the world around them.
“You can collect data forever and ever. And at some point, you just realize you have enough,” Sommer said.
Sommer now plans to disrupt the dogma for other sensory systems, like spoken language, to see if beloved theories hold up to the scrutiny of testing.
The hope is that by understanding how the brain solves other perceptual problems, Sommer and others can better understand psychiatric and motor disorders, like Parkinson’s disease, schizophrenia, or obsessive-compulsive disorder, and develop more effective treatments as a result.
“There are some sub-circuits of the brain that are probably pretty well-understood to be involved with these disorders. That’s a biological description,” Sommer said. “And there’s also neurotransmitter deficits, like lacking dopamine in Parkinson’s. That’s a chemical explanation. But there are very few big-picture, explanations of why people have certain psychiatric or motor disorders.”
CITATION: “Bayesian and Discriminative Models for Active Visual Perception Across Saccades,” Divya Subramanian, John Pearson, Marc A. Sommer. eNeuro, July 14, 2023. DOI: 10.1523/ENEURO.0403-22.2023
Warning: the following article discusses rape and sexual assault. If you or someone you know has been sexually assaulted, help is available.
Image: DreamStudio AI, with prompt “Woman, screaming, sitting on the witness stand in a U.S. court of law, in the style of Edvard Munch’s ‘The Scream’”
“You never screamed for help?”
“Why didn’t you fight back?”
These are questions that lawyers asked E. Jean Carroll in her rape case against former president Donald J. Trump this spring. These kinds of questions reflect a myth about rape: that it’s only rape if the victim puts up a fight.
A recent review of the research, “Neuroscience Evidence Counters a Rape Myth,” aims to set the record straight. It serves as a call to action for those in the scientific and legal professions. Ebani Dhawan completed this work at the University College London with Professor Patrick Haggard. She is now my classmate at Duke University, where she is pursuing an MA in Bioethics & Science Policy.
Ebani Dhawan
Commonly accepted beliefs and myths about rape are a persistent problem in defining and prosecuting sexual assault. The intentions of all actors are examined in the courtroom. If a victim freezes or does not attempt to resist during a sexual assault, perpetrators may claim there was passive acquiescence; that consent was assumed from an absence of resistance.
From the moment a victim reports an assault, the legal process poses “why” questions about the survivor’s behavior. This is problematic because it upholds the idea that survivors can (and should) choose to scream or fight back during an assault.
This new paper presents neuroscientific evidence which counters that misconception. Many survivors of sexual assault report ‘freezing’ during an assault. The researchers argue that this is an involuntary response to a threat which can prevent a victim from actively resisting, and that it occurs throughout biology.
Animal studies have demonstrated that severe, urgent threats, like assault or physical restraint, can trigger a freeze response involving fixed posture (tonic immobility) or loss of muscle tone (collapsed immobility). Self-reports of these states in humans shed light on an important insight into immobility. Namely, that we are unable to make voluntary actions during this freezing response.
An example of this is the “lockup” state displayed by pilots during an aviation emergency. After a plane crash, it’s hard to imagine anyone asking a pilot if they froze because they really wanted to crash the plane.
Yet, quite frequently victims of sexual assault are asked to explain the freeze response, something which is further made difficult by the impaired memory and loss of sense of agency which often accompanies trauma.
The legal process around sexual assault should be updated to reflect this neuroscientific evidence.
THIS MYTH HAS REAL CONSEQUENCES.
The vast majority of sexual assault cases do not result in a conviction. It is estimated that out of every 1,000 sexual assaults in the U.S., only 310 are reported to the police and only 28 lead to felony conviction. That is a conviction rate of less than 3%.
In England and Wales, just 3% of rapes recorded in the previous year resulted in charges. According to RAINN, one of the leading anti-sexual assault organizations, many victims don’t report because they believe the justice system would not do anything to help — a belief that these conviction rates support.
E. Jean Carroll named this in her trial. She said, “Women don’t come forward. One of the reasons they don’t come forward is because they’re always asked, why didn’t you scream? You better have a good excuse if you didn’t scream.”
This research serves as a much-needed call-to-action. By revisiting processes steeped in myth, justice can be better served.
I asked Ebani what she thinks must be done. Here are her recommendations:
The neuroscience community should pursue greater mechanistic understanding of threat processing and involuntary action processes and the interaction between them.
Activists and legal scholars should advocate for processes reflective of the science behind involuntary responses like freezing, and the inability of victims to explain that behavior.
Neuroscientists should contribute to Police officers’ education regarding involuntary responses to rape and sexual assault.
“I’m telling you: He raped me whether I screamed or not.” – E. Jean Carroll
We didn’t know we needed another way to rank the importance of Duke’s scientists, but the folks at research.com have gone ahead and developed one anyway. And in its second year of data, several Duke people come out in the top ten nationally and globally. So, okay, maybe we did need a new ranking system!
Duke Psychology and Neuroscience swept the U.S. medals in psychology: Terrie E. Moffitt Ph.D., first, Michael Tomasello, Ph.D. second, and Avshalom Caspi, Ph.D. third. Duke University’s psychology is overall ninth in the world, according to this ranking.
Moffitt, the Nannerl O. Keohane University Distinguished Professor of P&N, and Caspi, the Edward M. Arnett Distinguished Professor of P&N,are frequent co-authors on a lifelong psychology and health study of 1,000 people born in Dunedin, New Zealand. Moffitt ranks fourth in the world in psychology, with 207,903 citations of her 582 works. Caspi’s 159,598 citations of 507 papers were good enough for 10th in the world.
Developmental psychologist Tomasello, the James F. Bonk Distinguished Professor of P&N, has focused his work on cognitive development, social cognition and language acquisition. He has 147,951 citations on an even 800 works, placing him second in the U.S. and ninth in the world.
Nobel laureate Robert Lefkowitz M.D., the chancellor’s distinguished professor of medicine, is ranked second in the nation and third in the world for Biology and Biochemistry with 198,000 citations of his 881 papers. The rankings reflect the importance of Lefkowitz’s discovery and characterization of the 7-transmembrane g-coupled protein receptor (GPCR), a fundamental signaling port on the surface of cells that is targeted by a third to a half of all prescription drugs.
Koenig
Psychiatry and Behavioral Sciences professor and Co-Director of Duke’s Center for Spirituality, Theology and Health, Harold G. Koenig M.D., was ranked seventh in the nation and 10th in the world for Social Sciences and Humanities for his work on spirituality and health. His 703 publications have earned 66,404 citations.
Many other Duke scholars finished in the top 100 worldwide in their respective fields, some even making a mark in multiple fields. Check it out.
Methodology: Research.com’s ranking of the best scholars by discipline relies on data consolidated from various sources including OpenAlex and CrossRef. The bibliometric data for estimating the citation-based metrics were collected on Dec. 21, 2022. Position in the ranking is based on a researcher’s D-index (Discipline H-index), which includes exclusively papers and citation metrics for an examined discipline.
And just to prevent some letters to the editor, we acknowledge that the H-index has its critics, including its inventor. We don’t make the rankings folks, we just share them.
The literature is clear: there is a dark side to engaging with social media, with linkages to depressive symptoms, a sense of social isolation, and dampened self-esteem recently revealed in the global discourse as alarming potential harms.
Underlying the pitfalls of social media usage is social comparison—the process of evaluating oneself relative to another person—to the extent that those who engage in more social comparison are at a significantly higher risk of negative health outcomes linked to their social media consumption.
Today, 72 percent of Americans use some type of social media, with most engaging daily with at least one platform.(1) Particularly for adolescents and young adults, interactions on social media are an integral part of building and maintaining social networks.(2-5) While the potential risks to psychosocial well-being posed by chronic engagement with these platforms have increasingly come to light within the past several years, mitigating these adverse downstream effects poses a novel and ongoing challenge to researchers and healthcare professionals alike.
The intervention aimed to supplant college students’ habitual social comparison … with social savoring: experiencing joyful emotions about someone else’s experiences.
A team of researchers led by Nancy Zucker, PhD, professor in Psychiatry & Behavioral Sciences and director of graduate studies in psychology and neuroscience at Duke University, recently investigated this issue and found promising results for a brief online intervention targeted at altering young adults’ manner of engagement with social media. The intervention aimed to supplant college students’ habitual social comparison when active on social media with social savoring: experiencing joyful emotions about someone else’s experiences.
Image from Andrade et al
Zucker’s team followed a final cohort of 55 college students (78 percent female, 42 percent White, with an average age of 19.29) over a two-week period, first taking baseline measures of their mental well-being, connectedness, and social media usage before the students returned to daily social media usage. On day 8, a randomized group of students received the experimental intervention: an instructional video on the skill of social savoring. These students were then told to implement this new skill when active on social media throughout days 8 to 14, before being evaluated with the rest of the cohort at the two-week mark.
For those taught how and why to socially savor their daily social media intake, shifting focus from social comparison to social savoring measurably increased their performance self-esteem—their positive evaluation—as compared with the control group, who received no instructional video. Consciously practicing social savoring even seemed to enable students to toggle their self-esteem levels up or down: those in the intervention group reported significantly higher levels of self-esteem on days during which they engaged in more social savoring.
Encouragingly, the students who received the educational intervention on social media engagement also opted to practice more social savoring over time, suggesting they found this mode of digesting their daily social media feeds to be enduringly preferable to that of social comparison. The team’s initial findings suggest a promising future for targeted educational interventions as an effective way to improve facets of young adults’ mental health without changing the quantity or quality of their media consumption.
Of course, the radical alternative—forgoing social media platforms altogether in the name of improved well-being—looms in the distance as an appealing yet often unrealistic option for many; therefore, thoughtfully designed, evidence-based interventions such as this research team’s program seem to offer a more realistic path forward.
Black-capped chickadees have an incredible ability to remember where they’ve cached food in their environments. They are also small, fast, and able to fly.
So how exactly can a neuroscientist interested in their memories conduct studies on their brains? Dmitriy Aronov, Ph.D., a neuroscientist at the Zuckerman Mind Brain Behavior Institute at Columbia University, visited Duke recently to talk about chickadee memory and the practicalities of studying wild birds in a lab.
Black-capped chickadees, like many other bird species, often store food in hiding places like tree crevices. This behavior is called caching, and the ability to hide food in dozens of places and then relocate it later represents an impressive feat of memory. “The bird doesn’t get to experience this event happening over and over again,” Aronov says. It must instantly form a memory while caching the food, a process that relies on episodic memory. Episodic memory involves recalling specific experiences from the past, and black-capped chickadees are “champions of episodic memory.”
They have to remember not just the location of cached food but also other features of each hiding place, and they often have only moments to memorize all that information before moving on. According to Aronov, individual birds are known to cache up to 5,000 food items per day! But how do they do it?
Chickadees, like humans, rely on the brain’s hippocampus to form episodic memories, and the hippocampus is considerably bigger in food-caching birds than in birds of similar size that aren’t known to cache food. Aronov and his team wanted to investigate how neural activity represents the formation and retrieval of episodic memories in black-capped chickadees.
Step one: find a creative way to study food-caching in a laboratory setting. Marissa Applegate, a graduate student in Aronov’s lab, helped design a caching arena “optimized for chickadee ergonomics,” Aronov says. The arenas included crevices covered by opaque flaps that the chickadees could open with their toes or beaks and cache food in. The chickadees didn’t need any special training to cache food in the arena, Aronov says. They naturally explore crevices and cache surplus food inside.
Once a flap closed over a piece of cached food (sunflower seeds), the bird could no longer see inside—but the floor of each crevice was transparent, and a camera aimed at the arena from below allowed scientists to see exactly where birds were caching seeds. Meanwhile, a microdrive attached to the birds’ tiny heads and connected to a cable enabled live monitoring of their brain activity, down to the scale of individual neurons.
An artistic rendering of one of the cache sites in an arena. “Arenas in my lab have between 64 and 128 of these sites,” Aronov says. Drawing by Julia Kuhl.
Through a series of experiments, Aronov and his team discovered that “the act of caching has a profound effect on hippocampal activity,” with some neurons becoming more active during caching and others being suppressed. About 35% percent of neurons that are active during caching are consistently either enhanced or suppressed during caching—regardless of which site a bird is visiting. But the remaining 65% of variance is site-specific: “every cache is represented by a unique pattern of this excess activity in the hippocampus,” a pattern that holds true even when two sites are just five centimeters apart—close enough for a bird to reach from one to another.
Chickadees could hide food in any of the sites for retrieval at a future time. The delay period between the caching phase (when chickadees could store surplus food in the cache sites) and the retrieval phase (when chickadees were placed back in the arena and allowed to retrieve food they had cached earlier) ranged from a few minutes to an hour. When a bird returned to a cache to retrieve food, the same barcode-like pattern of neural activity reappeared in its brain. That pattern “represents a particular experience in a bird’s life” that is then “reactivated” at a later time.
Aronov said that in addition to caching and retrieving food, birds often “check” caching sites, both before and after storing food in them. Of course, as soon as a bird opens one of the flaps, it can see whether or not there’s food inside. Therefore, measuring a bird’s brain activity after it has lifted a flap makes it impossible to tell whether any changes in brain activity when it checks a site are due to memory or just vision. So the researchers looked specifically at neural activity when the bird first touched a flap—before it had time to open it and see what was inside. That brain activity, as it turns out, starts changing hundreds of milliseconds before the bird can actually see the food, a finding that provides strong evidence for memory.
What about when the chickadees checked empty caches? Were they making a memory error, or were they intentionally checking an empty site—even knowing it was empty—for their own mysterious reasons? On a trial-by-trial basis, it’s impossible to know, but “statistically, we have to invoke memory in order to explain their behavior,” he said.
A single moment of caching, Aronov says, is enough to create a new, lasting, and site-specific pattern. The implications of that are amazing. Chickadees can store thousands of moments across thousands of locations and then retrieve those memories at will whenever they need extra food.
It’s still unclear how the retrieval process works. From Aronov’s study, we know that chickadees can reactivate site-specific brain activity patterns when they see one of their caches (even when they haven’t yet seen what’s inside). But let’s say a chickadee has stored a seed in the bark of a particular tree. Does it need to see that tree in order to remember its cache site there? Or can it be going about its business on the other side of the forest, suddenly decide that it’s hungry for a seed, and then visualize the location of its nearest cache without actually being there? Scientists aren’t sure.
If you’re a doe-eyed first-year at Duke who wants to eventually become a doctor, chances are you are currently, or will soon, take part in a pre-med rite of passage: finding a lab to research in.
Most pre-meds find themselves researching in the fields of biology, chemistry, or neuroscience, with many hoping to make research a part of their future careers as clinicians. Undergraduate student and San Diego native Eden Deng (T’23) also found herself plodding a similar path in a neuroimaging lab her freshman year.
Eden Deng T’23
At the time, she was a prospective neuroscience major on the pre-med track. But as she soon realized, neuroimaging is done through fMRI. And to analyze fMRI data, you need to be able to conduct data analysis.
This initial research experience at Duke in the Martucci Lab, which looks at chronic pain and the role of the central nervous system, sparked a realization for Deng. “Ninety percent of my time was spent thinking about computational and statistical problems,” she explained to me. Analysis was new to her, and as she found herself struggling with it, she thought to herself, “why don’t I spend more time getting better at that academically?”
Deng at the Martucci Lab
This desire to get better at research led Deng to pursue a major in Statistics with a secondary in Computer Science, while still on the pre-med track. Many people might instantly think about how hard it must be to fit in so much challenging coursework that has virtually no overlap. And as Deng confirmed, her academic path not been without challenges.
For one, she’s never really liked math, so she was wary of getting into computation. Additionally, considering that most Statistics and Computer Science students want to pursue jobs in the technology industry, it’s been hard for her to connect with like-minded people who are equally familiar with computers and the human body.
“I never felt like I excelled in my classes,” Deng said. “And that was never my intention.” Deng had to quickly get used to facing what she didn’t know head-on. But as she kept her head down, put in the work, and trusted that eventually she would figure things out, the merits of her unconventional academic path started to become more apparent.
Research at the intersection of data and health
Last summer, Deng landed a summer research experience at Mount Sinai, where she looked at patient-level cancer data. Utilizing her knowledge in both biology and data analytics, she worked on a computational screener that scientists and biologists could use to measure gene expression in diseased versus normal cells. This will ultimately aid efforts in narrowing down the best genes to target in drug development. Deng will be back at Mount Sinai full-time after graduation, to continue her research before applying to medical school.
Deng presenting on her research at Mount Sinai
But in her own words, Deng’s most favorite research experience has been her senior thesis through Duke’s Department of Biostatistics and Bioinformatics. Last year, she reached out to Dr. Xiaofei Wang, who is part of a team conducting a randomized controlled trial to compare the merits of two different lung tumor treatments.
Generally, when faced with lung disease, the conservative approach is to remove the whole lobe. But that can pose challenges to the quality of life of people who are older, with more comorbidities. Recently, there has been a push to focus on removing smaller sections of lung tissue instead. Deng’s thesis looks at patient surgical data over the past 15 years, showing that patient survival rates have improved as more of these segmentectomies – or smaller sections of tissue removal – have become more frequent in select groups of patients.
“I really enjoy working on it every week,” Deng says about her thesis, “which is not something I can usually say about most of the work I do!” According to Deng, a lot of research – hers included – is derived from researchers mulling over what they think would be interesting to look at in a silo, without considering what problems might be most useful for society at large. What’s valuable for Deng about her thesis work is that she’s gotten to work closely with not just statisticians but thoracic surgeons. “Originally my thesis was going to go in a different direction,” she said, but upon consulting with surgeons who directly impacted the data she was using – and would be directly impacted by her results – she changed her research question.
The merits of an interdisciplinary academic path
Deng’s unique path makes her the perfect person to ask: is pursuing seemingly disparate interests, like being a Statistics and Computer Science double-major on the pre-med, track worth it? And judging by Deng’s insights, the answer is a resounding yes.
At Duke, she says, “I’ve been challenged by many things that I wouldn’t have expected to be able to do myself” – like dealing with the catch-up work of switching majors and pursuing independent research. But over time she’s learned that even if something seems daunting in the moment, if you apply yourself, most, if not all things, can be accomplished. And she’s grateful for the confidence that she’s acquired through pursuing her unique path.
Moreover, as Deng reflects on where she sees herself – and the field of healthcare – a few years from now, she muses that for the first time in the history of healthcare, a third-party player is joining the mix – technology.
While her initial motivation to pursue statistics and computer science was to aid her in research, “I’ve now seen how its beneficial for my long-term goals of going to med school and becoming a physician.” As healthcare evolves and the introduction of algorithms, AI and other technological advancements widens the gap between traditional and contemporary medicine, Deng hopes to deconstruct it all and make healthcare technology more accessible to patients and providers.
“At the end of the day, it’s data that doctors are communicating to patients,” Deng says. So she’s grateful to have gained experience interpreting and modeling data at Duke through her academic coursework.
And as the Statistics major particularly has taught her, complexity is not always a good thing – sometimes, the simpler you can make something, the better. “Some research doesn’t always do this,” she says – she’s encountered her fair share of research that feels performative, prioritizing complexity to appear more intellectual. But by continually asking herself whether her research is explainable and applicable, she hopes to let those two questions be the North Stars that guide her future research endeavors.
At the end of the day, it’s data that doctors are communicating to patients.
Eden Deng
When asked what advice she has for first-years, Deng said that it’s important “to not let your inexperience or perceived lack of knowledge prevent you from diving into what interests you.” Even as a first-year undergrad, know that you can contribute to academia and the world of research.
And for those who might be interested in pursuing an academic path like Deng, there’s some good news. After Deng talked to the Statistics department about the lack of pre-health representation that existed, the Statistics department now has a pre-health listserv that you can join for updates and opportunities pertaining specifically to pre-med Stats majors. And Deng emphasizes that the Stats-CS-pre-med group at Duke is growing. She’s noticed quite a few underclassmen in the Statistics and Computer Science departments who vocalize an interest in medical school.
So if you also want to hone your ability to communicate research that you care about – whether you’re pre-med or not – feel free to jump right into the world of data analysis. As Deng concludes, “everyone has something to say that’s important.”
Guest post by Amy Lei, North Carolina School of Science and Math, Class of 2025.
