The prestigious APS Fellowship Program signifies recognition by one’s professional peers. Each year, no more than one half of one percent of the APS membership is recognized with this distinct honor. Bassett’s election and groundbreaking work in biological physics and network science will be recognized through presentation of a certificate at the APS March Meeting.
Bassett is a pioneer in the field of network neuroscience, an emerging subfield which incorporates elements of mathematics, physics, biology and systems engineering to better understand how the overall shape of connections between individual neurons influences cognitive traits. They lead the Complex Systems lab which tackles problems at the intersection of science, engineering, and medicine using systems-level approaches, exploring fields such as curiosity, dynamic networks in neuroscience, and psychiatric disease.
Bassett recently collaborated with Penn artist-in-residence Rebecca Kamen and other scholars on an interdisciplinary art exhibit on the creative process in art and science at the Katzen Art Center at American University. They have also published research modeling different types of curiosity and exploring gender-based citation bias in neuroscience publishing.
“I’m thrilled and humbled to receive this honor from the American Physical Society,” says Bassett. “I am indebted to the many fantastic mentees, colleagues, and mentors that have made my time in science such an exciting adventure. Thank you.”
Jennifer E. Phillips-Cremins (upper left) and members of her lab.
Each year, the National Institutes of Health (NIH) recognizes exceptionally creative scientists through its High-Risk, High-Reward Research Program. The four awards granted by this program are designed to support researchers whose “out of the box” and “trailblazing” ideas have the potential for broad impact.
Jennifer E. Phillips-Cremins, Associate Professor and Dean’s Faculty Fellow in Penn Engineering’s Department of Bioengineering and the Perelman School of Medicine’s Department of Genetics, is one such researcher. As a recipient of an NIH Director’s Pioneer Award, she will receive $3.5 million over five years to support her work on the role that the physical folding of chromatin plays in the encoding of neural circuit and synapse properties contributing to long-term memory.
Phillips-Cremins’ award is one of 106 grants made through the High-Risk, High-Reward program this year, though she is only one of 10 to receive the Pioneer Award, which is the program’s largest funding opportunity.
“The science put forward by this cohort is exceptionally novel and creative and is sure to push at the boundaries of what is known,” said NIH Director Francis S. Collins.
Phillips-Cremins’ research is in the general field of epigenetics, the molecular and structural modifications that allow the genome — an identical copy of which is found in each cell — to express genes differently at different times and in different parts of the body. Within this field, her lab focuses on higher-order folding patterns of the DNA sequence, which bring distant sets of genes and regulatory elements into close proximity with one another as they are compressed inside the cell’s nucleus.
Previous work from the Cremins lab has investigated severe genome misfolding patterns common across a class of genetic neurological disorders, including fragile X syndrome, Huntington’s disease, ALS and Friedreich’s ataxia.
With the support of the Pioneer Award, she and the members of her lab will extend that research to a more fundamental question of neuroscience: how memory is encoded over decades, despite the rapid turnover of the relevant proteins and RNA sequences within the brain’s synapses.
“Our long-term goals are to understand how, when and why pathologic genome misfolding leads to synaptic dysfunction by way of disrupted gene expression,” said Phillips-Cremins, “as well as to engineer the genome’s structure-function relationship to reverse pathologic synaptic defects in debilitating neurological diseases.”
A collaborative study finds that deeper regions of the brain encode visual information more slowly, enabling the brain to identify fast-moving objects and images more accurately and persistently.
by Erica K. Brockmeier
Busy pedestrian crossing at Hong Kong
New research from the University of Pennsylvania, the Scuola Internazionale Superiore de Studi Avanzati (SISSA), and KU Leuven details the time scales of visual information processing across different regions of the brain. Using state-of-the-art experimental and analytical techniques, the researchers found that deeper regions of the brain encode visual information slowly and persistently, which provides a mechanism for explaining how the brain accurately identifies fast-moving objects and images. The findings were published in Nature Communications.
Understanding how the brain works is a major research challenge, with many theories and models developed to explain how complex information is processed and represented. One area of particular interest is vision, a major component of neural activity. In humans, for example, there is evidence that around half of the neurons in the cortex are related to vision.
Researchers are eager to understand how the visual cortex can process and retain information about objects in motion in a way that allows people to take in dynamic scenes while still retaining information about and recognizing the objects around them.
“One of the biggest challenges of all the sensory systems is to maintain a consistent representation of our surroundings, despite the constant changes taking place around us. The same holds true for the visual system,” says Davide Zoccolan, director of SISSA’s Visual Neuroscience Laboratory. “Just look around us: objects, animals, people, all on the move. We ourselves are moving. This triggers rapid fluctuations in the signals acquired by the retina, and until now it was unclear whether the same type of variations apply to the deeper layers of the visual cortex, where information is integrated and processed. If this was the case, we would live in tremendous confusion.”
Experiments using static stimuli, such as photographs, have found that information from the sensory periphery are processed in the visual cortex according to a finely tuned hierarchy. Deeper regions of the brain then translate this information about visual scenes into more complex shapes, objects, and concepts. But how this process works in more dynamic, real-world settings is not well understood.
To shed light on this, the researchers analyzed neural activity patterns in multiple visual cortical areas in rodents while they were being shown dynamic visual stimuli. “We used three distinct datasets: one from SISSA, one from a group in KU Leuven led by Hans Op de Beeck and one from the Allen Institute for Brain Science in Seattle,” says Zoccolan. “The visual stimuli used in each were of different types. In SISSA, we created dedicated video clips showing objects moving at different speeds. The other datasets were acquired using various kinds of clips, including from films.”
Next, the researchers analyzed the signals registered in different areas of the visual cortex through a combination of sophisticated algorithms and models developed by Penn’s Eugenio Pasini and Vijay Balasubramanian. To do this, the researchers developed a theoretical framework to help connect the images in the movies to the activity of specific neurons in order to determine how neural signals evolve over different time scales.
“The art in this science was figuring out an analysis method to show that the processing of visual images is getting slower as you go deeper and deeper in the brain,” says Balasubramanian. “Different levels of the brain process information over different time scales; some things could be more stable, some quicker. It’s very hard to tell if the time scales across the brain are changing, so our contribution was to devise a method for doing this.”
Vijay Balasubramanian is the Cathy and Marc Lasry Professor in the Department of Physics and Astronomy in the School of Arts & Sciences and a member of the Penn Bioengineering Graduate Group at the University of Pennsylvania.
The Lindback Awards, announced annually, are the most prestigious teaching awards that full-time faculty members at the University can receive.
Meaney is the Solomon R. Pollack Professor in Bioengineering and Senior Associate Dean of Penn Engineering and his research areas span from traumatic brain injury to brain network theory. He received his M.S. and Ph.D. in Bioengineering and Biomedical Engineering from Penn Engineering.
Speaker: Emery N. Brown, MD, PhD
Edward Hood Taplin Professor of Medical Engineering and of Computational Neuroscience, MIT
Warren M. Zapol Professor of Anaesthesia, Harvard Medical School
Massachusetts General Hospital
Date: Thursday, April 1, 2021
Time: 3:00-4:00 PM EDT
Zoom – check email for link or contact ksas@seas.upenn.edu
Title: “Deciphering the Dynamics of the Unconscious Brain Under General Anesthesia”
Abstract:
General anesthesia is a drug induced state that is critical for safely and humanely allowing a patient to undergo surgery or an invasive diagnostic procedure. During the last 10 years the study of the neuroscience of anesthetic drugs has been an active area of research. In this lecture we show how anesthetics create altered states of arousal by creating oscillation that impede how the various parts of the brain communicate. These oscillations, which are readily visible on the electroencephalogram (EEG), change systematically with anesthetic dose, anesthetic class and patient age. We will show how the EEG oscillations can be used to monitor the brain states of patients receiving general anesthesia, manage anesthetic delivery and learn about fundamental brain physiology.
EMERY BROWN BIO:
Emery N. Brown is the Edward Hood Taplin Professor of Medical Engineering and Professor of Computational Neuroscience at Massachusetts Institute of Technology. He is the Warren M. Zapol Professor of Anaesthesia at Harvard Medical School and Massachusetts General Hospital (MGH), and an anesthesiologist at MGH.
Dr. Brown received his BA (magna cum laude) in Applied Mathematics from Harvard College, his MA and PhD in statistics from Harvard University, and his MD (magna cum laude) from Harvard Medical School. He completed his internship in internal medicine at the Brigham and Women’s Hospital and his residency in anesthesiology at MGH. He joined the staff at MGH, the faculty at Harvard Medical School in 1992 and the faculty at MIT in 2005.
Dr. Brown is an anesthesiologist-statistician recognized for developing signal processing algorithms for neuroscience data analysis and for defining the neurophysiological mechanisms of general anesthesia.
Dr. Brown was a member of the NIH BRAIN Initiative Working Group. He is a fellow of the IEEE, the AAAS, the American Academy of Arts and Sciences and the National Academy of Inventors. Dr. Brown is a member of the National Academy of Medicine, the National Academy of Sciences and the National Academy of Engineering. He received an NIH Director’s Pioneer Award, the National Institute of Statistical Sciences Sacks Award, the American Society of Anesthesiologists Excellence in Research Award, the Dickson Prize in Science, the Swartz Prize for Theoretical and Computational Neuroscience and a Doctor of Science (honoris causa) from the University of Southern California.
Danielle Bassett, J. Peter Skirkanich Professor in the departments of Bioengineering and Electrical and Systems Engineering, investigates how the shape of networks impact the phenomena that arises from them. Much of that research is focused on networks of neurons, and how the different ways they are wired together in different people can influence their mental traits, such as memory or executive function.
Bassett is also interested in networks of people, however, as the shapes of those networks can have a major impact on a society’s traits. Last year, she and her colleagues published a study that investigated the network of citations neuroscience researchers produced in the course of their work, demonstrating a systemic gender bias that left women underrepresented in the literature.
Recently, Bassett spoke with WIRED’s Grace Huckins about the big-picture changes that must take place within academia for it to become truly equitable.
When a group of researchers at NYU Abu Dhabi published a paper in Nature Communications last fall suggesting that young women scientists should seek out men as mentors, the backlash was swift and vociferous. Countless scientists, many of them women, registered their indignation on Twitter—some even penning open letters and their ownpreprints in response. The original paper had found that female junior scientists who authored papers with male senior scientists saw their papers cited at higher rates. But a number of critics contested the assertion that this result established a link between male mentors and career performance. Scientists routinely coauthor articles with people who are not their mentors, they argued, and citation rates are just one metric of achievement. In response to these criticisms, the authors eventually retracted their paper. (They declined to comment to WIRED.)
But the paper had already stirred up a broader discussion about gender and mentorship in academia. For Danielle Bassett, a professor of bioengineering at the University of Pennsylvania, the methodological concerns that prompted the paper’s retraction were far from its worst sin. She herself has researched citation practices and found that, in neuroscience, papers with male senior authors are cited at a disproportionately high rate—primarily because other male scientists preferentially cite them. To suggest that young women should therefore try to author papers with men is, she believes, a grave error. “That was a problem in assigning blame,” she says. “The onus is on us to create a scientific culture that lets students choose a mentor that’s right for them.”
Living Electrode Panels (image courtesy of the Cullen Lab)
Connecting the human brain to electrical devices is a long-standing goal of neuroscientists, bioengineers, and clinicians, with applications ranging from deep brain stimulation (DBS) to treat Parkinson’s disease to more futuristic endeavors such as Elon Musk’s NeuraLink initiative to record and translate brain activity. However, these approaches currently rely on using implantable metallic electrodes that inherently provoke a lasting immune response due to their non-biological nature, generally complicating the reliability and stability of these interfaces over time. To address these challenges, D. Kacy Cullen, Associate Professor in Neurosurgery and Bioengineering, and Dayo Adewole, a doctoral candidate in Bioengineering, worked with a multi-disciplinary team of collaborators to develop the first “living electrodes” as an implantable, biological bridge between the brain and external devices. In a recent article published in Science Advances, the team demonstrated the fabrication of hair-like microtissue comprised of living neuronal networks and bundled tracts of axons — the signal sending fibers of the nervous system — protected within soft hydrogel cylinders. They showed that these axon-based living electrodes could be fully controlled and monitored with light — thus eliminating the need for electrical contact — and are capable of surviving and forming synapses with the brain as demonstrated in an adult rat model. While further advancements are necessary prior to clinical use, the current findings provide the foundation for a new class of “living electrodes” as a biological intermediary between humans and devices capable of leveraging natural mechanisms to potentially provide a stable interface for clinical applications.
While artificial intelligence is becoming a bigger part of nearly every industry and increasingly present in everyday life, even the most impressive AI is no match for a toddler, chimpanzee, or even a honeybee when it comes to learning, creativity, abstract thinking or connecting cause and effect in ways they haven’t been explicitly programmed to recognize.
This discrepancy gets at one of the field’s fundamental questions: what does it mean to say an artificial system is “intelligent” in the first place?
Konrad Kording, Timothy Verstynen, Joshua T. Vogelstein, and Leyla Isik (clockwise from top left)
Seventy years ago, Alan Turing famously proposed such a benchmark; a machine could be considered to have artificial intelligence if it could successfully fool a person into thinking it was a human as well. Now, many artificial systems could pass a “Turing Test” in certain limited domains, but none come close to imitating the holistic sense of intelligence we recognize in animals and people.
Understanding how AI might someday be more like this kind of biological intelligence — and developing new versions of the Turing Test with those principles in mind — is the goal of a new collaboration between researchers at the University of Pennsylvania, Carnegie Mellon University and Johns Hopkins University.
The project, called “From Biological Intelligence to Human Intelligence to Artificial General Intelligence,” is led by Konrad Kording, a Penn Integrates Knowledge Professor with appointments in the Departments of Bioengineering and Computer and Information Science in Penn Engineering and the Department of Neuroscience at Penn’s Perelman School of Medicine. Kording will collaborate with Timothy Verstynen of Carnegie Mellon University, as well Joshua T. Vogelstein and Leyla Isik, both of Johns Hopkins University, on the project.
The Perelman School of Medicine has announced the winners of the 2020 Penn Medicine Awards of Excellence. The Office of the Dean says:
“These awardees exemplify our profession’s highest values of scholarship, teaching, innovation, commitment to service, leadership, professionalism and dedication to patient care. They epitomize the preeminence and impact we all strive to achieve. The awardees range from those at the beginning of their highly promising careers to those whose distinguished work has spanned decades.
Each recipient was chosen by a committee of distinguished faculty from the Perelman School of Medicine or the University of Pennsylvania. The contributions of these clinicians and scientists exemplify the outstanding quality of patient care, mentoring, research, and teaching of our world-class faculty.”
Two faculty members affiliated with Penn Bioengineering are among this year’s recipients.
Yale Cohen, PhD, Professor of Otorhinolaryngology with secondary appointments in Neuroscience and Bioengineering, is the recipient of the Jane M. Glick Graduate Student Teaching Award. Cohen is an alumnus of the Penn Bioengineering doctoral program and is currently the department’s Graduate Chair.
“Dr. Cohen’s commitment to educating and training the next generation of scientists exemplifies the type of scientist and educator that Jane Glick represented. His students value his highly engaging and supportive approach to teaching, praising his enthusiasm, energy, honesty, and compassion.”
Douglas H. Smith, MD, Robert A. Groff Endowed Professor of Research and Teaching in Neurosurgery and member of the Penn Bioengineering Graduate Group, is the recipient of this year’s William Osler Patient Oriented Research Award:
“Dr. Smith is the foremost authority on diffuse axonal injury (DAI) as the unifying hypothesis behind the short- and long-term consequences of concussion. After realizing early in his career that concussion, or mild traumatic brain injury (TBI), was a much more serious event than broadly appreciated, Dr. Smith and his team have used computer biomechanical modeling, in vitro and in vivo testing in parallel with seminal human studies to elucidate mechanisms of concussion.”
When the COVID-19 pandemic began taking hold in the United States, one of the first “superspreader” events was an academic conference. Such conferences have long been a primary way for researchers to share new findings and launch collaborations, but with thousands of people from around the world, indoors and in close proximity, it quickly became clear that the traditional format for these events would need to radically change.
Konrad Kording
Konrad Kording, a Penn Integrates Knowledge Professor with appointments in the departments of Bioengineering and Computer and Information Science in Penn Engineering and the Department of Neuroscience at Penn’s Perelman School of Medicine, was ahead of the curve on this shift. With the issues of prohibitive costs and environmental impact of travel in mind, Kording had already started brainstorming ways of reinventing the traditional conference format when the pandemic made it a necessity.
The resulting event, Neuromatch, involved algorithmically analyzing participants’ work in order to connect researchers who might not otherwise meet. Building on the success of that “unconference,” Kording and his colleagues launched the Neuromatch Academy, a free-ranging online summer school organized around the same principles.
Ashley Juavinett writing for The Simons Collaboration on the Global Brain, recently dug into how Neuromatch was able to pull together 1,750 students from 70 countries in a matter of months:
Kording already had experience quickly pulling together online events. Early in the pandemic, together with Dan Goodman, Titipat Achakulvisut and Brad Wyble, he developed an online ‘unconference,’ which featured both lectures and a virtual networking component designed to mimic the in-person interactions that make conferences so valuable. (For more, see “Designing a Virtual Neuroscience Conference.”) Soon after, they decided to spin that success into a full-fledged summer school offering live lectures with top computational neuroscientists, guided coding exercises to teach mathematical approaches to neural modeling and analysis, and community support from mentors and teaching assistants (TAs).
The result was a summer school with well-designed content, a diverse student body, including participants from U.S.-sanctioned Iran, and a determined group of organizers who managed to pull off the most inclusive computational neuroscience school yet. NMA now has its eye on a future with even broader representation across countries, languages and skill levels. This year has been incredibly difficult for many, but NMA has provided an important precedent for how to collaborate across, and even dismantle, all sorts of barriers.
