Defining Neural “Representation”

by Marilyn Perkins

Neuroscientists frequently say that neural activity ‘represents’ certain phenomena, PIK Professor Konrad Kording and postdoc Ben Baker led a study that took a philosophical approach to tease out what the term means.

Monitors Show EEG Reading and Graphical Brain Model. In the Background Laboratory Man Wearing Brainwave Scanning Headset Sits in a Chair with Closed Eyes. In the Modern Brain Study Research Laboratory
Neuroscientists use the word “represent” to encompass multifaceted relationships between brain activity, behavior, and the environment.

One of neuroscience’s greatest challenges is to bridge the gaps between the external environment, the brain’s internal electrical activity, and the abstract workings of behavior and cognition. Many neuroscientists rely on the word “representation” to connect these phenomena: A burst of neural activity in the visual cortex may represent the face of a friend or neurons in the brain’s memory centers may represent a childhood memory.

But with the many complex relationships between mind, brain, and environment, it’s not always clear what neuroscientists mean when they say neural activity “represents” something. Lack of clarity around this concept can lead to miscommunication, flawed conclusions, and unnecessary disagreements.

To tackle this issue, an interdisciplinary paper takes a philosophical approach to delineating the many aspects of the word “representation” in neuroscience. The work, published in Trends in Cognitive Sciences, comes from the lab of Konrad Kording, a Penn Integrates Knowledge University Professor and senior author on the study whose research lies at the intersection of neuroscience and machine learning.

“The term ‘representation’ is probably one of the most common words in all of neuroscience,” says Kording, who has appointments in the Perelman School of Medicine and School of Engineering and Applied Science. “But it might mean something very different from one professor to another.”

Read the full story in Penn Today.

Konrad Kording is a Penn Integrates Knowledge University Professor with joint appointments in the Department of Neuroscience the Perelman School of Medicine and in the Department of Bioengineering in the School of Engineering and Applied Science.

Ben Baker is a postdoctoral researcher in the Kording lab and a Provost Postdoctoral Fellow. Baker received his Ph.D. in philosophy from Penn.

Also coauthor on the paper is Benjamin Lansdell, a data scientist in the Department of Developmental Neurobiology at St. Jude Children’s Hospital and former postdoctoral researcher in the Kording lab.

Funding for this study came from the National Institutes of Health (awards 1-R01-EB028162-01 and R01EY021579) and the University of Pennsylvania Office of the Vice Provost for Research.

Konrad Kording’s CENTER is Part of a New NIH Education Initiative on Scientific Rigor

by Melissa Pappas

Konrad Kording (Photo by Eric Sucar)

In 2005, John Ioannidis published a bombshell paper titled “Why Most Published Research Findings Are False.” In it, Ioannidis argued that a lack of scientific rigor in biomedical research — such as poor study design, small sample sizes and improper assessment of the significance of data— meant that a large percentage of experiments would not return the same results if they were conducted again.

Since then, researchers’ awareness of this “replication crisis” has grown, especially in fields that directly impact the health and wellbeing of people, where lapses in rigor can have life-or-death consequences. Despite this attention and motivation, however, little progress has been made in addressing the roots of the problem. Formal training in rigorous research practices remains rare; while mentors advise their students on how to properly construct and conduct experiments to produce the most reliable evidence, few educational resources exist to support them.

To address this discrepancy, the National Institute of Neurological Disorders and Stroke (NINDS), part of the National Institutes of Health (NIH), has launched the Initiative to Improve Education in the Principles of Rigorous Research.

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 in Penn’s Perelman School of Medicine, has been awarded one of the initiative’s first five grants.

“The replication crisis is real,” says Kording. “I’ve tried to replicate the research of others and failed. I’ve reanalyzed my own data and found major mistakes that needed to be corrected. I was never properly taught how to do rigorous science, and I want to improve that for the next generation.”

Read the full story in Penn Engineering Today.

Konrad Kording on the Future of Brain-Computer Interfaces

Konrad Kording (Photo by Eric Sucar)

Though the technology for brain-computer interfaces (or BCI’s) has existed for decades, recent strides have been made to create BCI devices which are safer, smaller, and more effective. Konrad Kording, Nathan Francis Mossell University Professor in Bioengineering, Neuroscience, and Computer and Information Science, helps to elucidate the potential future of this technology in a recent feature in Wired. In the article, he discusses the “invasive” aspects of previous BCI technology, in contrast to recent innovations, such as a new device by Synchron, which do not require surgery and are consequently much less risky:

“The device, called a Stentrode, has a mesh-like design and is about the length of a AAA battery. It is implanted endovascularly, meaning it’s placed into a blood vessel in the brain, in the region known as the motor cortex, which controls movement. Insertion involves cutting into the jugular vein in the neck, snaking a catheter in, and feeding the device through it all the way up into the brain, where, when the catheter is removed, it opens up like a flower and nestles itself into the blood vessel’s wall. Most neurosurgeons are already up to speed on the basic approach required to put it in, which reduces a high-risk surgery to a procedure that could send the patient home the very same day. ‘And that is the big innovation,” Kording says.

Read “The Age of Brain-Computer Interfaces Is on the Horizon” in Wired.

Konrad Kording Appointed Co-Director the CIFAR Learning in Machines & Brains Program

Konrad Kording, PhD (Photo by Eric Sucar)

Konrad Kording, Nathan Francis Mossell University Professor in Bioengineering, Neuroscience, and Computer and Information Sciences, was appointed the Co-Director of the CIFAR Program in Learning in Machines & Brains. The appointment will start April 1, 2022.

CIFAR is a global research organization that convenes extraordinary minds to address the most important questions facing science and humanity. CIFAR was founded in 1982 and now includes over 400 interdisciplinary fellows and scholars, representing over 130 institutions and 22 countries. CIFAR supports research at all levels of development in areas ranging from Artificial Intelligence and child and brain development, to astrophysics and quantum computing. The program in Learning in Machines & Brains brings together international scientists to examine “how artificial neural networks could be inspired by the human brain, and developing the powerful technique of deep learning.” Scientists, industry experts, and policymakers in the program are working to understand the computational and mathematical principles behind learning, whether in brains or in machines, in order to understand human intelligence and improve the engineering of machine learning. As Co-Director, Kording will oversee the collective intellectual development of the LMB program which includes over 30 Fellows, Advisors, and Global Scholars. The program is also co-directed by Yoshua Benigo, the Canada CIFAR AI Chair and Professor in Computer Science and Operations Research at Université de Montréal.

Kording, a Penn Integrates Knowledge (PIK) Professor, was previously named an associate fellow of CIFAR in 2017. Kording’s groundbreaking interdisciplinary research uses data science to advance a broad range of topics that include understanding brain function, improving personalized medicine, collaborating with clinicians to diagnose diseases based on mobile phone data and even understanding the careers of professors. Across many areas of biomedical research, his group analyzes large datasets to test new models and thus get closer to an understanding of complex problems in bioengineering, neuroscience and beyond.

Visit Kording’s lab website and CIFAR profile page to learn more about his work in neuroscience, data science, and deep learning.

Investing in Penn’s Data Science Ecosystem

by Erica K. Brockmeier

As part of a major University-wide investment in science, engineering, and medicine, the Innovation in Data Engineering and Science Initiative aims to help Penn become a leader in developing data-driven approaches that can transform scientific discovery, engineering research, and technological innovation.

From smartphones and fitness trackers to social media posts and COVID-19 cases, the past few years have seen an explosion in the amount and types of data that are generated daily. To help make sense of these large, complex datasets, the field of data science has grown, providing methodologies, tools, and perspectives across a wide range of academic disciplines.

But the challenges that lie ahead for data scientists and engineers, from developing algorithms that don’t exacerbate biases to ensuring privacy protections, are equally complex and, in some instances, require entirely new ways of thinking.

As part of its $750 million investment in science, engineering, and medicine, the University has committed to supporting the future needs of this field. To this end, the Innovation in Data Engineering and Science (IDEAS) initiative will help Penn become a leader in developing data-driven approaches that can transform scientific discovery, engineering research, and technological innovation.

“The IDEAS initiative is game-changing for our University,” says President Amy Gutmann. “This new investment allows us to boost our interdisciplinary efforts across campus, recruit phenomenal additional team members, and generate an even more sound foundation for discovery, experimentation, and design. This initiative is a clear statement that Penn is committed to taking data science head-on.”

Building on a foundation of existing expertise

Led by the School of Engineering and Applied Science, the IDEAS initiative builds upon the steadily gathering momentum of its data-centric research. The Warren Center for Network and Data Sciences has been a major catalyst for this type of work, generating foundational research on ethical algorithms and data privacy, as well as collaborations that have drawn in faculty from the Wharton School, Law School, Perelman School of Medicine, and beyond. In addition, Wharton’s Department of Statistics and Data Science is an active partner in research and teaching initiatives that apply statistical modeling across a wide variety of fields.

“One of the unique things about data science and data engineering is that it’s a very horizontal technology, one that is going to be impacting every department on campus,” says George Pappas, Electrical and Systems Engineering Department chair. “When you have a horizontal technology in a competitive area, we have to figure out specific areas where Penn can become a worldwide leader.”

To do this, IDEAS aims to recruit new faculty across three research areas: artificial intelligence (AI) to transform scientific discovery, trustworthy AI for autonomous systems, and understanding connections between the human brain and AI.

Penn already has a strong foundation in using AI for scientific discovery thanks in part to investments in basic research facilities such as the Singh Center for Nanotechnology and the Laboratory for Research on the Structure of Matter. Additionally, there are centers focused on connecting researchers from different fields to address complex scientific questions, including the Center for Soft and Living Matter, Center for Engineering Mechanobiology, and Penn Institute for Computational Science.

Developing “trustworthy” algorithms, ones that work reliably outside of situations in which they are trained, is another key component of the IDEAS initiative. Ongoing research at the Penn Research in Embedded Computing and Integrated Systems Engineering (PRECISE) Center, the General Robotics, Automation, Sensing & Perception (GRASP) Lab, and DARPA-funded projects on the safety of AI-based aircraft control provide a starting point for furthering Penn’s research portfolio on safe, explainable, and trustworthy autonomous systems.

In the area of neuroscience and how the human brain is similar to AI and machine learning approaches, research from PIK Professor Konrad Kording and Dani Bassett’s Complex Systems lab exemplifies the types of cross-disciplinary efforts that are essential for addressing complex questions. By recruiting additional faculty in this area, IDEAS will help Penn make strides in bio-inspired computing and in future life-changing discoveries that could address cognitive disorders and nervous system diseases.

Read the full story in Penn Today.

Konrad Kording Receives Named University Professorship

Konrad Kording (Photo by Eric Sucar)

President Amy Gutmann has recently announced that two Penn Integrates Knowledge Professors, one of which is Penn Engineering’s own Konrad Kording, have received named University Professorships.  

Kording, who holds joint appointments in the Department of Neuroscience in the Perelman School of Medicine and the Department of Bioengineering in the School of Engineering and Applied Science, will become the Nathan Francis Mossell University Professor. 

When Nathan Francis Mossell graduated in 1882, he became the first African American to earn a medical degree from Penn. He soon became a prominent African American physician, the first to be elected to the Philadelphia County Medical Society. He helped found the Frederick Douglass Memorial Hospital and Training School, which treated Black patients and helped train the next generation of Black doctors and nurses.  

“Dr. Mossell was truly inspiring. He had to fight for everything, yet never reneged on his principles. He pretty much started a hospital and was a major champion for the advancement of equality for African Americans,” Kording said. “In my research, where I study how intelligence works, I am inspired by scholars like him who combine many different insights. He was a wonderful man, and I will be proud to carry his name.” 

Read more in Penn Today.

Penn, Carnegie Mellon and Johns Hopkins to Develop New Turing Tests, Investigate How AI Can Become More Like Biological Intelligence

by Evan Lerner

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.

Read the full story on Penn Engineering Today.

‘The Self-Organized Movement to Create an Inclusive Computational Neuroscience School’

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

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.

Continue reading “The Self-Organized Movement to Create an Inclusive Computational Neuroscience School” at The Simons Collaboration on the Global Brain.

Originally posted on the SEAS blog. Media contact Evan Lerner.

Penn Bioengineering and COVID-19

A message from Penn Bioengineering Professor and Chair Ravi Radhakrishnan:

In response to the unprecedented challenges presented by the global outbreak of the novel coronavirus SARS-CoV-2, Penn Bioengineering’s faculty, students, and staff are finding innovative ways of pivoting their research and academic projects to contribute to the fight against COVID-19. Though these projects are all works in progress, I think it is vitally important to keep those in our broader communities informed of the critical contributions our people are making. Whether adapting current research to focus on COVID-19, investing time, technology, and equipment to help health care infrastructure, or creating new outreach and educational programs for students, I am incredibly proud of the way Penn Bioengineering is making a difference. I invite you to read more about our ongoing projects below.


Novel Chest X-Ray Contrast

David Cormode, Associate Professor of Radiology and Bioengineering

Nanomedicine and Molecular Imaging Lab

Peter Noel, Assistant Professor of Radiology and BE Graduate Group Member

Laboratory for Advanced Computed Tomography Imaging

The Cormode and Noel labs are working to develop dark-field X-ray imaging, which may prove very helpful for COVID patients. It involves fabricating diffusers that incorporate gold nanoparticles to modify the X-ray beam. This method gives excellent images of lung structure. Chest X-ray is being used on the front lines for COVID patients, and this could potentially be an easy to implement modification of existing X-ray systems. The additional data give insight into the health state of the microstructures (alveoli) in the lung. This new contrast mechanics could be an early insight into the disease status of COVID-19 patients. For more on this research, see Cormode and Noel’s chapter in the forthcoming volume Spectral, Photon Counting Computed Tomography: Technology and Applications, edited by Katsuyuki Taguchi, Ira Blevis, and Krzysztof Iniewski (Routledge 2020).


Michael J. Mitchell, Skirkanich Assistant Professor of Innovation in Bioengineering

Mitchell Lab

Mike Mitchell is working with Saar Gill (Penn Medicine) on engineering drug delivery technologies for COVID-19 mRNA vaccination. He is also developing inhalable drug delivery technologies to block COVID-19 internalization into the lungs. These new technologies are adaptations of prior research published Volume 20 of Nano Letters (“Ionizable Lipid Nanoparticle-Mediated mRNA Delivery for Human CAR T Cell Engineering” January 2020) and discussed in Volume 18 of Nature Reviews Drug Discovery (“Delivery Technologies for Cancer Immunotherapy” January 2019).

Respiratory Distress Therapy Modeling

Ravi Radhakrishnan, Professor, and Chair of Bioengineering and Professor of Chemical and Biomolecular Engineering

Radhakrishnan Lab

Computational Models for Targeting Acute Respiratory Distress Syndrome (ARDS). The severe forms of COVID-19 infections resulting in death proceeds by the propagation of the acute respiratory distress syndrome or ARDS. In ARDS, the lungs fill up with fluid preventing oxygenation and effective delivery of therapeutics through the inhalation route. To overcome this major limitation, delivery of antiinflammatory drugs through the vasculature (IV injection) is a better approach; however, the high injected dose required can lead to toxicity. A group of undergraduate and postdoctoral researchers in the Radhakrishnan Lab (Emma Glass, Christina Eng, Samaneh Farokhirad, and Sreeja Kandy) are developing a computational model that can design drug-filled nanoparticles and target them to the inflamed lung regions. The model combines different length-scales, (namely, pharmacodynamic factors at the organ scale, hydrodynamic and transport factors in the tissue scale, and nanoparticle-cell interaction at the subcellular scale), into one integrated framework. This targeted approach can significantly decrease the required dose for combating ARDS. This project is done in collaboration with Clinical Scientist Dr. Jacob Brenner, who is an attending ER Physician in Penn Medicine. This research is adapted from prior findings published in Volume 13, Issue 4 of Nanomedicine: Nanotechnology, Biology and Medicine: “Mechanisms that determine nanocarrier targeting to healthy versus inflamed lung regions” (May 2017).


Sydney Shaffer, Assistant Professor of Bioengineering and Pathology and Laboratory Medicine

Syd Shaffer Lab

Arjun Raj, Professor of Bioengineering

Raj Lab for Systems Biology

David Issadore, Associate Professor of Bioengineering and Electrical and Systems Engineering

Issadore Lab

Arjun Raj, David Issadore, and Sydney Shaffer are working on developing an integrated, rapid point-of-care diagnostic for SARS-CoV-2 using single molecule RNA FISH. The platform currently in development uses sequence specific fluorescent probes that bind to the viral RNA when it is present. The fluorescent probes are detected using a iPhone compatible point-of-care reader device that determines whether the specimen is infected or uninfected. As the entire assay takes less than 10 minutes and can be performed with minimal equipment, we envision that this platform could ultimately be used for screening for active COVID19 at doctors’ offices and testing sites. Support for this project will come from a recently-announced IRM Collaborative Research Grant from the Institute of Regenerative Medicine with matching funding provided by the Departments of Bioengineering and Pathology and Laboratory Medicine in the Perelman School of Medicine (PSOM) (PI’s: Sydney Shaffer, Sara Cherry, Ophir Shalem, Arjun Raj). This research is adapted from findings published in the journal Lab on a Chip: “Multiplexed detection of viral infections using rapid in situ RNA analysis on a chip” (Issue 15, 2015). See also United States Provisional Patent Application Serial No. 14/900,494 (2014): “Methods for rapid ribonucleic acid fluorescence in situ hybridization” (Inventors: Raj A., Shaffer S.M., Issadore D.).


Penn Health-Tech Coronavirus COVID-19 Collaborations

Brian Litt, Professor of Bioengineering, Neurology, and Neurosurgery

Litt Lab

In his role as one of the faculty directors for Penn Health-Tech, Professor Brian Litt is working closely with me to facilitate all the rapid response team initiatives, and in helping to garner support the center and remove obstacles. These projects include ramping up ventilator capacity and fabrication of ventilator parts, the creation of point-of-care ultrasounds and diagnostic testing, evaluating processes of PPE decontamination, and more. Visit the Penn Health-Tech coronavirus website to learn more, get involved with an existing team, or submit a new idea.

BE Labs COVID-19 Efforts

BE Educational Labs Director Sevile Mannickarottu & Staff

BE Educational Labs staff members Dana Abulez (BE ’19, Master’s BE ’20) and Matthew Zwimpfer (MSE ’18, Master’s MSE ’19) take shifts to laser-cut face shields.

The George H. Stephenson Foundation Educational Laboratory & Bio-MakerSpace staff have donated their PPE to Penn Medicine. Two staff members (Dana Abulez, BE ’19, Master’s BE ’20 and Matthew Zwimpfer, MSE ’18, Master’s MSE ’19) took shifts to laser-cut face shields in collaboration with Penn Health-Tech. Dana and Matthew are also working with Dr. Matthew Maltese on his low-cost ventilator project (details below).

Low-Cost Ventilator

Matthew Maltese, Adjunct Professor of Medical Devices and BE Graduate Group Member

Children’s Hospital of Philadelphia Center for Injury Research and Prevention (CIRP)

Dr. Maltese is rapidly developing a low-cost ventilator that could be deployed in Penn Medicine for the expected surge, and any surge in subsequent waves. This design is currently under consideration by the FDA for Emergency Use Authorization (EUA). This example is one of several designs considered by Penn Medicine in dealing with the patient surge.

Face Shields

David F. Meaney, Solomon R. Pollack Professor of Bioengineering and Senior Associate Dean

Molecular Neuroengineering Lab

Led by David Meaney, Kevin Turner, Peter Bruno and Mark Yim, the face shield team at Penn Health-Tech is working on developing thousands of rapidly producible shields to protect and prolong the usage of Personal Protective Equipment (PPE). Learn more about Penn Health-Tech’s initiatives and apply to get involved here.

Update 4/29/20: The Penn Engineering community has sprung into action over the course of the past few weeks in response to COVID-19. Dr. Meaney shared his perspective on those efforts and the ones that will come online as the pandemic continues to unfold. Read the full post on the Penn Engineering blog.


Student Community Building

Yale Cohen, Professor of Otorhinolaryngology, Department of Psychology, BE Graduate Group Member, and BE Graduate Chair

Auditory Research Laboratory

Yale Cohen, and Penn Bioengineering’s Graduate Chair, is working with Penn faculty and peer institutions across the country to identify intellectually engaging and/or community-building activities for Bioengineering students. While those ideas are in progress, he has also worked with BE Department Chair Ravi Radhakrishnan and Undergraduate Chair Andrew Tsourkas to set up a dedicated Penn Bioengineering slack channel open to all Penn Bioengineering Undergrads, Master’s and Doctoral Students, and Postdocs as well as faculty and staff. It has already become an enjoyable place for the Penn BE community to connect and share ideas, articles, and funny memes.

Undergraduate Course: Biotechnology, Immunology, Vaccines and COVID-19 (ENGR 35)

Daniel A. Hammer, Alfred G. and Meta A. Ennis Professor of Bioengineering and Chemical and Biomolecular Engineering

The Hammer Lab

This Summer Session II, Professor Dan Hammer and CBE Senior Lecturer Miriam R. Wattenbarger will teach a brand-new course introducing Penn undergraduates to a basic understanding of biological systems, immunology, viruses, and vaccines. This course will start with the fundamentals of biotechnology, and no prior knowledge of biotechnology is necessary. Some chemistry is needed to understand how biological systems work. The course will cover basic concepts in biotechnology, including DNA, RNA, the Central Dogma, proteins, recombinant DNA technology, polymerase chain reaction, DNA sequencing, the functioning of the immune system, acquired vs. innate immunity, viruses (including HIV, influenza, adenovirus, and coronavirus), gene therapy, CRISPR-Cas9 editing, drug discovery, types of pharmaceuticals (including small molecule inhibitors and monoclonal antibodies), vaccines, clinical trials. Some quantitative principles will be used to quantifying the strength of binding, calculate the dynamics of enzymes, writing and solving simple epidemiological models, methods for making and purifying drugs and vaccines. The course will end with specific case study of coronavirus pandemic, types of drugs proposed and their mechanism of action, and vaccine development.
Update 4/29/20: Read the Penn Engineering blog post on this course published April 27, 2020.

Neuromatch Conference

Konrad Kording, Penn Integrates Knowledge University Professor of Bioengineering, Neuroscience, and Computer and Information Science

Kording Lab

Dr. Kording facilitated Neuromatch 2020, a large virtual neurosciences conferences consisting of over 3,000 registrants. All of the conference talk videos are archived on the conference website and Dr. Kording has blogged about what he learned in the course of running a large  conference entirely online. Based on the success of Neuromatch 1.0, the team are now working on planning Neuromatch 2.0, which will take place in May 2020. Dr. Kording is also working on facilitating the transition of neuroscience communication into the online space, including a weekly social (#neurodrinking) with both US and EU versions.

Neuromatch Academy

Konrad Kording, Penn Integrates Knowledge University Professor of Bioengineering, Neuroscience, and Computer and Information Science

Kording Lab

Dr. Kording is working to launch the Neuromatch Academy, an open, online, 3-week intensive tutorial-based computational neuroscience training event (July 13-31, 2020). Participants from undergraduate to professors as well as industry are welcome. The Neuromatch Academy will introduce traditional and emerging computational neuroscience tools, their complementarity, and what they can tell us about the brain. A main focus is not just on using the techniques, but on understanding how they relate to biological questions. The school will be Python-based making use of Google Colab. The Academy will also include professional development / meta-science, model interpretation, and networking sessions. The goal is to give participants the computational background needed to do research in neuroscience. Interested participants can learn more and apply here.

Journal of Biomedical Engineering Call for Review Articles

Beth Winkelstein, Vice Provost for Education and Eduardo D. Glandt President’s Distinguished Professor of Bioengineering

Spine Pain Research Lab

The American Society of Medical Engineers’ (ASME) Journal of Biomechanical Engineering (JBME), of which Dr. Winkelstein is an Editor, has put out a call for review articles by trainees for a special issue of the journal. The call was made in March 2020 when many labs were ramping down, and trainees began refocusing on review articles and remote work. This call continues the JBME’s long history of supporting junior faculty and trainees and promoting their intellectual contributions during challenging times.
Update 4/29/20: CFP for the special 2021 issue here.

Are you a Penn Bioengineering community member involved in a coronavirus-related project? Let us know! Please reach out to



Brain-machine interfaces: Villainous gadgets or tools for next-gen superheroes?

A Q&A with neuroscientist Konrad Kording on how connections between minds and machines are portrayed in popular culture, and what the future holds for this reality-defying technology.

Science fiction and superhero films portray brain-machine interfaces as malevolent robots that plug into human brains for fuel in The Matrix (top left) or as power-enhancing devices in X-Men (top right). In reality, they can help patients use artificial limbs or directly connect to computers. (Image credits, from top left to bottom right: Warner Brothers, 20th Century Fox, Intelligent Films, AFP Photo/Jean-Pierre Clatot)

For the many superheroes that use high-powered gadgets to save the day, there’s an equal number of villains who use technology nefariously. From robots that plug into human brains for fuel in “The Matrix” to the memory-warping devices seen in “Men in Black,” “Captain Marvel,” and “Total Recall,” technology that can control people’s minds is one of the most terrifying examples of technology gone wrong in science fiction and superhero films.

Now, progress made on brain-machine interfaces, technology that provides a direct communication link between a brain and an external device, is bringing us closer to a world that feels like science fiction. Elon Musk’s company NeuraLink is working on a device to let people control computers with their minds, while Facebook’s “mind-reading initiative” can decode speech from brain activity. Is this progress a glimpse into a dark future, or are there more empowering ways in which brain-machine interfaces could become a force for good?

Penn Today talked with Konrad Kording, a Penn Integrates Knowledge Professor of Neuroscience, Bioengineering, and Computer and Information Science whose group works at the interface of data science and neuroscience to better understand the human brain, to learn more about brain-machine interfaces and where real-world technologies and science fiction intersect.

Q: What are the main challenges in connecting brains to devices?

The key problem is that you need to get a lot of information out of brains. Today’s prosthetic devices are very slow, and if we want to go faster it’s a tradeoff: I can go slower and then I am more precise, or I can go faster and be more noisy. We need to get more data out of brains, and we want to do it electrically, meaning we need to get more electrodes into brains.

So what do you need? You need a way of getting electrodes into the brain without making your brain into a pulp, you want the electrodes to be flexible so they can stay in longer, and then you want the system to be wireless. You don’t want to have a big connector on the top of your head.

It’s primarily a hardware problem. We can get electrodes into brains, but they deteriorate quickly because they are too thick. We can have plugs on people’s heads, but it’s ruling out any real-world usage. All these factors hold us back at the moment.

That’s why the Neuralink announcement was very interesting. They get a rather large number of electrodes into brains using well-engineered approaches that make that possible. What makes the difference is that Neuralink takes the best ideas in all the different domains and puts them together.

Q: Most examples in pop culture of connecting brains to machines have villainous or nefarious ends. Does that match up with how brain-machine interfaces are currently being developed? 

Let’s say you’ve had a stroke, you can’t talk, but there’s a prosthetic device that allows you to talk again. Or if you lost your arm, and you get a new one that’s as good as the original—that’s absolutely a force for good.

It’s not a dark, ugly future thing, it’s a beautiful step forward for medicine. I want to make massive progress in these diseases. I want patients who had a stroke to talk again; I want vets to have prosthetic devices that are as good as the real thing. I think short-term this is what’s going to happen, but we are starting to worry about the dark sides.

Read the full interview at Penn Today.