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.

Penn Engineers at the Forefront of Penn’s ‘Innovation Ecosystem’

By Lauren Salig

Andrei Georgescu, a member of Dan Huh’s bioengineering laboratory, prepares microfluidics for the lab’s work on organ-on-a-chip technology. Their innovative research was one of many Engineering projects featured in a recent video.

The University of Pennsylvania is highlighting its “ecosystem of innovation” in a new video, featuring some of the most cutting-edge work being done on campus and the infrastructure supporting that work. Alongside shots of the Singh Center for Nanotechnology, the Pennovation Center and the coming VentureLab are the familiar faces of Penn Engineers inventing the future.

The video includes the voices of Vijay Kumar, the Nemirovsky Family Dean of the School of Engineering and Applied Science; Dawn Bonnell, Penn’s Vice Provost of Research and the Henry Robinson Towne Professor of Materials Science and Engineering; and Konrad Kording, a Penn Integrates Knowledge Professor of Neurosciences and Bioengineering — each discussing the collaborative environment at the University.

A quick watch of the video reveals glimpses into Penn Engineering labs and projects where much of Penn’s innovation happens: PERCH’s flying robots that swarm together without using GPS, an investigation into 2-D room-temperature platforms for quantum technology, testing mechanical walking algorithms on robotic legs named Cassie, organs-on-a-chip that aid the study of diseases on Earth and in space, President’s Innovation Prize winners’ nanoscale implant company Visiplate aiming to treat blindness, blueprints for nanocrystals that self-assemble into materials with unique properties, Penn Electric Racing’s four-wheel drive competitive racecar, and PERCH lab spin-off Ghost Robotic’s Minitaur robot that senses the ground beneath its metal feet.

See if you can spot these Penn Engineering contributions in the video at Penn Today.

This article was originally posted on the Penn Engineering Medium blog.

Shoddy Science Uncovered in New Research

by Linda Tunesi

shoddy science
Konrad Kording, Ph.D.

Konrad Kording, professor in the Department of Bioengineering, and colleagues have a new technique for identifying fraudulent scientific papers by spotting reused images. Rather than scrap a failed study, for example, a researcher might attempt to pass off images from a different experiment to give the false impression that their own was a success.

Kording, a Penn Integrates Knowledge (PIK) Professor who also has an appointment in the Department of Neuroscience in Penn’s Perelman School of Medicine, and his collaborators developed an algorithm that can compare images across journal articles and detect such replicas, even if the image has been resized, rotated, or cropped.

They describe their technique in a paper recently published on the BioRxiv preprint server.

“Any fraudulent paper damages science,” Kording says. “In biology, many times fraud is detected when someone looks at a few papers and says ‘hey, these images look a little similar.’ We reckoned we could make an algorithm that does the same thing.”

“Science depends on building upon other people’s work,” adds Daniel Acuna, lead author on the paper, and a student in Kording’s lab at Northwestern University at the time the study was conducted. “If you cannot trust other people’s work, the scientific process collapses and, worse, the general public loses trust in us. Some websites were doing this, anonymously, but at a painstakingly slow rate.” Acuna is now an assistant professor in the School of Information Studies at Syracuse University.

While much of Kording’s work focuses on using data science to understand the brain, he is also curious about the process of research itself, or, as he puts it, “the science of science.” One of the Kording lab’s previous projects closely analyzed common methods of neuroscience research, and another turned a mirror on itself, describing how to structure a scientific paper.

Continued at the Penn Engineering Medium blog.

CIFAR Names Kording Associate Fellow

CIFAR
Konrad Kording, Ph.D.

Dr. Konrad Kording, a University of Pennsylvania PIK Professor in Bioengineering and Neuroscience, has been named an associate fellow by the Canadian Institute for Advanced Research (CIFAR), an advanced study institute headquartered in Toronto and partially funded by the government of Canada. Dr. Kording’s fellowship is in the institute’s Learning in Machines & Brains area, which has been one of CIFAR’s 14 interdisciplinary study fields since 2004. He joins 32 other fellows currently supported by the institute for their work in this area.

“The CIFAR program in Learning in Machines & Brains brings together many of the world’s leading deep learning scientists,” Dr. Kording says. “I look forward to collaborate with them to figure out how the brain learns.”

CIFAR was founded in 1982. Over the last 35 years, the institute has supported the work of scientists in 133 countries, including 18 Nobel Prize laureates.

New Faculty: Interview With Konrad Kording

Kording
Konrad Kording, PhD

This week, we present our interview with incoming faculty member Konrad Kording, who starts as a Penn Integrates Knowledge Professor in the Department of Bioengineering and the Department of Neuroscience in the Perelman School of Medicine. Konrad and Andrew Mathis discuss what neuroscience is and isn’t, the “C” word (consciousness), and what it’s like for a native of Germany to live in the United States.

 

PlayPlay

Uncertainty Investigated by Neuroscience

uncertainty

 

Uncertainty is part of life, but the underlying neuroscience of how we make decisions under conditions of uncertainty is only beginning to be understood. In a paper published Monday by Nature Human Behaviour, new Penn Bioengineering faculty member and Penn Integrates Knowledge Professor Konrad Kording, Ph.D., and his coauthor, Iris Vilares, Ph.D., of University College London, offer additional evidence that dopamine lies at the heart of how the brain operates when there is a lack of certainty.

Drs. Kording and Vilares devised a simple computerized test that examined the extent to which test takers relied on previous knowledge vs. what they saw at the present moment. They then administered the test to a cohort of patients with Parkinson’s disease, a condition associated with depleted dopamine levels. The patients were tested both while taking dopaminergic medication and while off it. They found that dopaminergic medication caused the patients to pay greater attention to sensory (i.e., visual) information — an effect that diminished as the patients learned. Ultimately, the study provided evidence that dopamine levels were related to the tendency to rely on new information, also called likelihood uncertainty.

“Scientists believe that understanding uncertainty is key to understanding how the brain computes,” Dr. Kording says. “There are many theories in this space. We provide fairly clean evidence for one of them, which is that dopamine encodes likelihood uncertainty. This information could change the way people think about the manner in which the brain deals with uncertainty.”

Konrad Kording: A Penn Integrates Knowledge Professor Coming to Penn BE

konrad kording
Konrad Kording, PhD

The Department of Bioengineering at the University of Pennsylvania is proud to announce that Konrad Kording, PhD, currently professor of physical medicine and rehabilitation, physiology, and applied mathematics at Northwestern University, will join the BE faculty in the fall.

Dr. Kording, a neuroscientist with advanced degrees in experimental physics and computational neuroscience, is a native of Germany. After earning his PhD in 2001 at the Swiss Federal Institute of Technology in Zurich, he held fellowships at University College, London, and MIT before arriving at Northwestern in 2006.

Kording’s groundbreaking interdisciplinary research uses data science to understand brain function, improve personalized medicine, collaborate with clinicians to diagnose diseases based on mobile phone data, and even understand 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.

Dr. Kording’s appointment will be shared between the BE Department and the Department of Neuroscience in the Perelman School of Medicine.