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.

‘Curious Minds: The Power of Connection’

Twin siblings and scholars Dani S. Bassett of Penn and Perry Zurn of American University collaborated over half a dozen years to write “Curious Minds: The Power of Connection.” (Image: Tony and Tracy Wood Photography)

With appointments in the Departments of Bioengineering and Electrical and Systems Engineering, as well as the Department of Physics and Astronomy in Penn Arts & Science, and the Departments of Neuroscience and Psychiatry in Penn Perelman’s School of Medicine, Dani S. Bassett is no stranger to following the thread of an idea, no matter where it might lead.

Curious Minds book cover

Those wide-ranging fields and disciplines orbit around an appropriate central question: how does the tangle of neurons in our brains wire itself up to learn new things? Bassett, J. Peter Skirkanich Professor and director of the Complex Systems Lab, studies the relationship between the shape of those networks of neurons and the brain’s abilities, especially the way the shape of the network grows and changes with the addition of new knowledge.


To get at the fundamentals of the question of curiosity, Bassett needed to draw on even more disciplines. Fortunately, they didn’t have to look far; Bassett’s identical twin is Perry Zurn, a professor of philosophy at American University, and the two have investigated the many different ways a person can exhibit curiosity.

Bassett and Zurn have now published a new book on the subject. In Curious Minds: The Power of Connection, the twins draw on their previous research, as well as an expansive network of ideas from philosophy, history, education and art.

In an interview with The Guardian, Bassett explains how these threads wove together:

“It wasn’t clear at the beginning of our careers that we would even ever have a chance to write a book together because our areas were so wildly different,” Bassett says – but then, as postgraduates, Zurn was studying the philosophy of curiosity while Bassett was working on the neuroscience of learning. “And so that’s when we started talking. That talking led to seven years of doing research together,” Bassett says. “This book is a culmination of that.”

How exactly do philosophy and neuroscience complement each other? It all starts with the book’s first, and most deceptively simple question: what is curiosity? “Several investigators in science have underscored that perhaps the field isn’t even ready to define curiosity and how it’s different from other cognitive processes,” says Bassett. The ambiguity in the neuroscience literature motivated Bassett to turn to philosophy, “where there are really rich historical definitions and styles and subtypes that we can then put back into neuroscience and ask: ‘Can we see these in the brain?’”

Curious Minds: The Power of Connection is available now. Read Amelia Tait’s review “Are you a busybody, a hunter or a dancer? A new book about curiosity reveals all,” in The Guardian. 

This story originally appeared in Penn Engineering Today.

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.

Brian Litt Receives Landis Award for Outstanding Mentorship

Brian Litt, MD

Brian Litt, MD, Professor in Neurology, Neurosurgery and Bioengineering and Director of the Penn Epilepsy Center, has received a 2022 Landis Award for Outstanding Mentorship from the National Institute of Neurological Disorders and Stroke (NINDS). This award honors Litt’s dedication to superior mentorship and training in neuroscience research. The award includes $100,000 in the form of a supplement to an existing NINDS grant to support his efforts to foster the career advancement of additional trainees.

Read the announcement in Penn Medicine News.

Yale Cohen Appointed Assistant Dean of Research Facilities and Resources at Penn Medicine

Yale E. Cohen, PhD

Yale E. Cohen, Professor of Otorhinolaryngology, with secondary appointments in Neuroscience and Bioengineering, was appointed Assistant Dean of Research Facilities and Resources at the Perelman School of Medicine at the University of Pennsylvania, effective April 1, 2022. Cohen is currently Chair of the Penn Bioengineering Graduate Group, and Director of the Hearing Sciences Center:

“Many of you are already quite familiar with Dr. Cohen, as his leadership roles in research training and education at PSOM and the University are far-reaching and impactful. Dr. Cohen is a Professor of Otorhinolaryngology with secondary appointments in the Department of Neuroscience and Engineering’s Department of Bioengineering. Recognized widely for his deep commitment to our teaching and training community, Dr. Cohen chairs the Bioengineering Graduate Group, and in 2020 received the prestigious Jane M. Glick Graduate Student Teaching Award, which honors clinicians and scientists who exemplify outstanding quality of patient care, mentoring, research, and teaching.”

Read the full announcement in the Penn Medicine archive.

Vijay Balasubramanian Discusses Theoretical Physics in Quanta Magazine

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

In an interview with Quanta Magazine, Vijay Balasubramanian discusses his work as a theoretical physicist, noting his study of the foundations of physics and the fundamentals of space and time. He speaks of the importance of interdisciplinary study and about how literature and the humanities can contextualize scientific exploration in the study of physics, computer science, and neuroscience.

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

Read “Pondering the Bits That Build Space-Time and Brains” in Quanta Magazine.

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.

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.

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.