Tag: physics

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Understanding Optimal Resource Allocation in the Brain

by Erica K. Brockmeier

A processed image representative of the types of images used in this study. Natural landscapes were transformed into binary images, ones made of black and white pixels, that were decomposed into different textures defined by specific statistics. (Image: Eugenio Piasini)

The human brain uses more energy than any other organ in the body, requiring as much as 20% of the body’s total energy. While this may sound like a lot, the amount of energy would be even higher if the brain were not equipped with an efficient way to represent only the most essential information within the vast, constant stream of stimuli taken in by the five senses. The hypothesis for how this works, known as efficient coding, was first proposed in the 1960s by vision scientist Horace Barlow.

Now, new research from the Scuola Internazionale Superiore di Studi Avanzati (SISSA) and the University of Pennsylvania provides evidence of efficient visual information coding in the rodent brain, adding support to this theory and its role in sensory perception. Published in eLife, these results also pave the way for experiments that can help understand how the brain works and can aid in developing novel artificial intelligence (AI) systems based on similar principles.

According to information theory—the study of how information is quantified, stored, and communicated—an efficient sensory system should only allocate resources to how it represents, or encodes, the features of the environment that are the most informative. For visual information, this means encoding only the most useful features that our eyes detect while surveying the world around us.

Vijay Balasubramanian, a computational neuroscientist at Penn, has been working on this topic for the past decade. “We analyzed thousands of images of natural landscapes by transforming them into binary images, made up of black and white pixels, and decomposing them into different textures defined by specific statistics,” he says. “We noticed that different kinds of textures have different variability in nature, and human subjects are better at recognizing those which vary the most. It is as if our brains assign resources where they are most necessary.”

Read the full story in Penn Today.

Vijay Balasubramanian is the Cathy and Marc Lasry Professor in the Department of Physics and Astronomy in the School of Arts & Sciences at the University of Pennsylvania. He is a member of the Penn Bioengineering Graduate Group.

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A New Model for How the Brain Perceives Unique Odors

by Erica K. Brockmeier

Cathy and Marc Lasry Professor Vijay Balasubramanian at Penn’s BioPond.

A study published in PLOS Computational Biology describes a new model for how the olfactory system discerns unique odors. Researchers from the University of Pennsylvania found that a simplified, statistics-based model can explain how individual odors can be perceived as more or less similar from others depending on the context. This model provides a starting point for generating new hypotheses and conducting experiments that can help researchers better understand the olfactory system, a complex, crucial part of the brain.

The sense of smell, while crucial for things like taste and hazard avoidance, is not as well studied as other senses. Study co-author Vijay Balasubramanian, a theoretical physicist with an interest in how living systems process information, says that olfaction is a prime example of a complex information-processing system found in nature, as there are far more types of volatile molecules—on the scale of tens or hundreds of thousands—than there are receptor types in the nose to detect them, on the scale of tens to hundreds depending on the species.

“Every molecule can bind to many receptors, and every receptor can bind to many molecules, so you get this combinatorial mishmash, with the nose encoding smells in a way that involves many receptor types to collectively tell you what a smell is,” says Balasubramanian. “And because there are many fewer receptor types than molecular species, you basically have to compress a very high dimensional olfactory space into a much lower dimensional space of neural responses.”

Read the full story in Penn Today.

Vijay Balasubramanian is the Cathy and Marc Lasry Professor in the Department of Physics & Astronomy in the School of Arts & Sciences at the University of Pennsylvania and a member of the Penn Bioengineering Graduate Group.

This research was supported by the Simons Foundation Mathematical Modeling of Living Systems (Grant 400425) and the Swartz Foundation.

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Dani Bassett Elected an American Physical Society Fellow

Dani Bassett, Ph.D.

Dani S. Bassett,  J. Peter Skirkanich Professor in the departments of Bioengineering and Electrical and Systems Engineering, has been elected a 2021 Fellow of the American Physical Society (APS) “for significant contributions to the network modeling of the human brain, including dynamical changes caused by evolution, learning, aging, and disease.”

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.”

Read more stories about Bassett’s research here.

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Atomically-thin, Twisted Graphene Has Unique Properties

by Erica K. Brockmeier

New collaborative research describes how electrons move through two different configurations of bilayer graphene, the atomically-thin form of carbon. These results provide insights that researchers could use to design more powerful and secure quantum computing platforms in the future.

New research published in Physical Review Letters describes how electrons move through two different configurations of bilayer graphene, the atomically-thin form of carbon. This study, the result of a collaboration between Brookhaven National Laboratory, the University of Pennsylvania, the University of New Hampshire, Stony Brook University, and Columbia University, provides insights that researchers could use to design more powerful and secure quantum computing platforms in the future.

“Today’s computer chips are based on our knowledge of how electrons move in semiconductors, specifically silicon,” says first and co-corresponding author Zhongwei Dai, a postdoc at Brookhaven. “But the physical properties of silicon are reaching a physical limit in terms of how small transistors can be made and how many can fit on a chip. If we can understand how electrons move at the small scale of a few nanometers in the reduced dimensions of 2-D materials, we may be able to unlock another way to utilize electrons for quantum information science.”

When a material is designed at these small scales, to the size of a few nanometers, it confines the electrons to a space with dimensions that are the same as its own wavelength, causing the material’s overall electronic and optical properties to change in a process called quantum confinement. In this study, the researchers used graphene to study these confinement effects in both electrons and photons, or particles of light.

The work relied upon two advances developed independently at Penn and Brookhaven. Researchers at Penn, including Zhaoli Gao, a former postdoc in the lab of Charlie Johnson who is now at The Chinese University of Hong Kong, used a unique gradient-alloy growth substrate to grow graphene with three different domain structures: single layer, Bernal stacked bilayer, and twisted bilayer. The graphene material was then transferred onto a special substrate developed at Brookhaven that allowed the researchers to probe both electronic and optical resonances of the system.

“This is a very nice piece of collaborative work,” says Johnson. “It brings together exceptional capabilities from Brookhaven and Penn that allow us to make important measurements and discoveries that none of us could do on our own.”

Read the full story in Penn Today.

Charlie Johnson is the Rebecca W. Bushnell Professor of Physics and Astronomy in the Department of Physics and Astronomy in the School of Arts & Sciences at the University of Pennsylvania and a member of the Penn Bioengineering Graduate Group.

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Reimagining Scientific Discovery Through the Lens of an Artist

by Erica K. Brockmeier

Rebecca Kamen, Penn artist-in-residence and visiting scholar, has a new exhibition titled “Reveal: The Art of Reimagining Scientific Discovery” at American University Museum at the Katzen Arts Center that explores curiosity and the creative process across art and science. (Image: Greg Staley)

Rebecca Kamen, Penn artist-in-residence and visiting scholar, has long been interested in science and the natural world. As a Philadelphia native and an artist with a 40-plus-year career, her intersectional work sheds light on the process of scientific discovery and its connections to art, with previous exhibitions that celebrate Apollo 11’s “spirit of exploration and discovery” to new representations of the periodic table of elements.

Now, in her latest exhibition, Kamen has created a series of pieces that highlight how the creative processes in art and science are interconnected. In “Reveal: The Art of Reimagining Scientific Discovery,” Kamen chronicles her own artistic process while providing a space for self-reflection that enables viewers to see the relationship between science, art, and their own creativity.

The exhibit, on display at the Katzen Art Center at American University, was inspired by the work of Penn professor Dani Bassett and American University professor Perry Zurn, the exhibit’s faculty sponsor. The culmination of three years of work, “Reveal” features collaborations with a wide range of scientists, including philosophers at American University, microscopists at the National Institutes of Health studying SARS-CoV-2 , and researchers in Penn’s Complex Systems Lab and the Addiction, Health, and Adolescence (AHA!) Lab.

Continue reading at Penn Today.

Dani S. Bassett is the J. Peter Skirkanich Professor in the departments of Bioengineering and Electrical and Systems Engineering in the School of Engineering and Applied Science at the University of Pennsylvania. She also has appointments in the Department of Physics and Astronomy in Penn’s School of Arts & Sciences and the departments of Neurology and Psychiatry in the Perelman School of Medicine at Penn.

Rebecca Kamen is a visiting scholar and artist-in-residence in the Department of Physics & Astronomy in Penn’s School of Arts & Sciences.

David Lydon-Staley is an assistant professor in the Annenberg School for Communication at Penn and was formerly a postdoc in the Bassett lab.

Dale Zhou is a Ph.D. candidate in Penn’s Neuroscience Graduate Group.

“Reveal: The Art of Reimagining Scientific Discovery,” presented by the Alper Initiative for Washington Art and curated by Sarah Tanguy, is on display at the American University Museum in Washington, D.C., until Dec. 12.

The exhbition catalog, which includes an essay on “Radicle Curiosity” by Perry Zurn and Dani S. Bassett, can be viewed online.

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Decoding How the Brain Accurately Depicts Ever-changing Visual Landscapes

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.”

Read the full story in Penn Today.

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.

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New Grant Aims to Broaden Participation in Cutting-Edge Materials Research

University of Puerto Rico’s Edgardo Sánchez (left) and Penn graduate Zhiwei Liao working in the lab of Daeyeon Lee. Via the Advancing Device Innovation through Inclusive Research and Education program, researchers from Penn and the University of Puerto Rico will continue their materials science collaboration while supporting STEM career pathways for underrepresented groups. (Image credit: Felice Macera).

The National Science Foundation (NSF) has awarded grants to eight research teams to support partnerships that will increase diversity in cutting-edge materials research, education, and career development. One of those teams is Penn’s Laboratory for Research on the Structure of Matter (LRSM) and the University of Puerto Rico (UPR), whose long-running collaboration has now received an additional six years of support.

With the goal of supporting partnerships between minority-serving educational institutions and leading materials science research centers, NSF’s Partnership for Research & Education in Materials (PREM) program funds innovative research programs and provides institutional support to increase recruitment, retention, and graduation by underrepresented groups as well as providing underserved communities access to materials research and education.

‘Research at the frontier’

With this PREM award, known as the Advancing Device Innovation through Inclusive Research and Education (ADIIR) program, researchers from Penn and UPR’s Humacao and Cayey campuses will conduct research on the properties of novel carbon-based materials with unique properties, and will study the effects of surface modification in new classes of sensors, detectors, and purification devices.

Thanks to this collaboration of more than 20 years, both institutions have made significant scientific and educational progress aided by biannual symposia and regular pre-pandemic travel between both institutions before the pandemic, resulting in a rich portfolio of publications, conference presentations, patents, students trained, and outreach programs.

“Together we have been publishing good papers that have impact, and we’ve really cultivated a culture of collaboration and friendship between our institutions,” says Penn’s Arjun Yodh, former director of the LRSM. “Our goal is to carry out research at the frontier and, in the process, nurture promising students from Puerto Rico and Penn.”

Ivan Dmochowski, a chemistry professor at Penn who has been involved with PREM for several years, says that this program has helped his group connect with experts in Puerto Rico whose skills complement his group’s interests in protein engineering. Dmochowski has also hosted UPR faculty members and students in his lab and also travelled to Puerto Rico before the pandemic to participate in research symposia, seminars, and outreach events.

“I’ve had students who have benefitted from being a co-author on a paper or having a chance to mentor students, and the faculty we’ve interacted with are exceptional,” Dmochowski says. “There’s a lot of benefit for both me and my students, and I’ve enjoyed our interactions both personally and scientifically.”

Penn’s Daeyeon Lee, a chemical and biomolecular engineering professor who has been involved with PREM for several years, regularly hosts students and faculty from UPR while working on nanocarbon-based composite films for sensor applications. The success of this collaboration relies on unique materials made by researchers at UPR combined with a method for processing them into composite structures developed in Lee’s lab.

“What I really admire about people at PREM, both faculty and students, is their passion,” says Lee. “I think that’s had a really positive impact on my students and postdocs who got to interact with them because they got to see the passion that the students brought.”

Read the full story in Penn Today.

Daeyeon Lee is a professor and the Evan C Thompson Term Chair for Excellence in Teaching in the Department of Chemical and Biomolecular Engineering and a member of the Bioengineering Graduate Group in Penn’s School of Engineering and Applied Science.

Arjun Yodh is the James M. Skinner Professor of Science in the Department of Physics & Astronomy in Penn’s School of Arts & Sciences and a member of the Bioengineering Graduate Group in Penn’s School of Engineering and Applied Science.

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“’Electronic Nose’ Accurately Sniffs Out Hard-to-Detect Cancers”

A.T. Charlie Johnson, Ph.D.

A.T. Charlie Johnson, Rebecca W. Bushnell Professor of Physics and Astronomy at the Penn School of Arts & Sciences, and member of the Penn Bioengineering Graduate Group has been working with a team of researchers on a new “electronic nose” that could help track the spread of COVID-19 based on the disease’s unique odor profile. Now, similar research shows that vapors emanating from blood samples can be tested to distinguish between benign and cancerous pancreatic and ovarian cells. Johnson presented the results at the annual American Society of Clinical Oncology meeting on June 4 (Abstract # 5544):

“It’s an early study but the results are very promising,” Johnson said. “The data shows we can identify these tumors at both advanced and the earliest stages, which is exciting. If developed appropriately for the clinical setting, this could potentially be a test that’s done on a standard blood draw that may be part of your annual physical.”

Read the full story in Penn Medicine News.

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Bioengineering Contributes to “New COVID-19 Testing Technology at Penn”

César de la Fuente, Ph.D., a Presidential Assistant Professor in Psychiatry, Microbiology, and Bioengineering, is leading a team to develop an electrode that can be easily printed at low cost to provide COVID-19 test results from your smart phone.

A recent Penn Medicine blog post surveys the efforts across Penn and the Perelman School of Medicine to develop novel says to detect SARS-CoV-2 and features several Department of Bioengineering faculty and Graduate Group members, including César de la Fuente, Presidential Assistant Professor in Psychiatry, Microbiology, and Bioengineering; Arupa Ganguly, Professor in Genetics; A.T. Charlie Johnson, Rebecca W. Bushnell Professor in Physics and Astronomy; Lyle Ungar, Professor in Computer and Information Science; and Ping Wang, Associate Professor in Pathology and Laboratory Medicine.

Read “We’ll Need More than Vaccines to Vanquish the Virus: New COVID-19 Testing Technology at Penn” by Melissa Moody in Penn Medicine News.

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An ‘Electronic Nose’ to Sniff Out COVID-19

by Erica K. Brockmeier

Postdoc Scott Zhang at work in the Johnson lab. (Photo: Eric Sucar, University Communications)

Even as COVID-19 vaccines are being rolled out across the country, the numerous challenges posed by the pandemic won’t all be solved immediately. Because herd immunity will take some time to reach and the vaccine has not yet been approved for some groups, such as children under 16 years of age, the coming months will see a continued need for tools to rapidly track the disease using real-time community monitoring.

A team of Penn researchers is working on a new “electronic nose” that could help track the spread of COVID-19. Led by physicist Charlie Johnson, the project, which was recently awarded a $2 million grant from the NIH, aims to develop rapid and scalable handheld devices that could spot people with COVID-19 based on the disease’s unique odor profile.

Dogs and devices that can detect diseases

Long before “coronavirus” entered into the vernacular, Johnson was collaborating with Cynthia Otto, director of the Penn Vet Working Dog Center, and Monell Chemical Senses Center’s George Preti to diagnose diseases using odor. Diseases are known to alter a number of physical processes, including body odors, and the goal of the collaboration was to develop new ways to detect the volatile organic compounds (VOCs) that were unique to ovarian cancer.

The next step is to scale down the current device, and the researchers are aiming to develop a prototype for testing on patients within the next year.

Since 2012, the researchers have been developing new ways to diagnose early-stage ovarian cancer. Otto trained dogs to recognize blood plasma samples from patients with ovarian cancer using their acute sense of smell. Preti, who passed away last March, was looking for the specific VOCs that gave ovarian cancer a unique odor. Johnson developed a sensor array, an electronic version of the dog’s nose, made of carbon nanotubes interwoven with single-stranded DNA. This device binds to VOCs and can determine samples that came from patients with ovarian cancer.

Last spring, as the pandemic’s threat became increasingly apparent, Johnson and Otto shifted their efforts to see if they could train their disease-detecting devices and dogs to spot patients with COVID-19.

Continue reading at Penn Today.

N.B.: A.T. Charlie Johnson, Rebecca W. Bushnell Professor of Physics and Astronomy at the Penn School of Arts & Sciences, and Lyle Ungar, Professor in Computer and Information Science at Penn Engineering and Psychology at the School of Arts & Sciences, are both members of the Penn Bioengineering Graduate Group.