On the Verge of Neuro-Motion

On the Verge of Neuro-Motion

On the Verge of Neuro-Motion 618 371 IEEE Pulse

Chad Bouton, director of the Center for Bioelectronic Medicine and vice president of advanced engineering at the Feinstein Institute for Medical Research, which serves as the research arm of one of the largest health systems in the United States, has spent nearly two decades developing innovative medical technology and products that help diagnose and treat conditions including cancer, stroke, diabetes, and paralysis. Last year, in a groundbreaking effort, Bouton and his colleagues published their findings in Nature on neural-decoding methods that helped Ian Burkhart become the first paralyzed person with a brain implant to move again with his own thoughts.
Prior to joining Northwell Health, Bouton (pictured above) was a research leader at Battelle, the world’s largest nonprofit research and development (R&D) organization, and was involved in medical device R&D programs for 18 years. He developed cancer detection algorithms in the late 1990s to help surgeons pinpoint and remove tumors more effectively. Bouton has been named Inventor of the Year and Distinguished Inventor by Battelle and in 2011 was selected by the National Academy of Engineering to attend the Frontiers in Engineering Symposium.
Bouton has been featured in WIRED, Verge, and Medical Device and Diagnostic Industry for his expertise and continued work in bioelectronic technology; he has also been recognized by the U.S. Congress for his work in the medical device field. Recently, he spoke about the potential implications of groundbreaking bioelectronic medical research at one of this year’s most popular SxSW panels and also during an informative and compelling bioethics panel discussion at Hofstra University.
IEEE Pulse: Can you describe the progress that has been made with neural bypass technology and what you have learned?
Chad Bouton: This is a very exciting time because we are finally showing in debilitating conditions like paralysis that the technology—that is, bioelectronic technology—can actually make a difference. We are showing that it’s possible to treat these conditions that, quite frankly, currently don’t have a cure. Spinal paralysis is one area, especially for quadriplegics, where not only is there no cure, there’s also not a lot of technology available to help restore movement in the hand.
In fact, there was a study done a number of years ago—essentially a survey—where participants ranked hand function at the top of the list in terms of abilities that they would like to regain. With paraplegics it’s different because you have things like bowel control and other issues, but for quadriplegics, hand function is extremely important. This makes sense when you recognize there is a gap in terms of assistive technology.
A number of years ago, we started to focus on the hand and worked to create an electronic neural bypass, where we’re rerouting the signals from the brain and reconnecting those signals electronically back to the muscles. We’ve now determined that this bypass is possible with Ian Burkhart. Ian’s been able to regain functional hand movement—he’s picking up objects and even moving individual fingers and playing a game similar to Guitar Hero—which has been just phenomenal.

(a) and (b) Researchers with the Center for Bioelectronic Medicine’s Neural Bypass Lab stimulate different areas of the arm to identify which muscle groups control the various fine motor movements of the hand and arm. The information obtained aids in developing neural bypass technology, which may ultimately allow paralyzed patients to perform hand and arm movements autonomously via their own brain signals. (Photos courtesy of The Feinstein Institute for Medical Research.)
(a) and (b) Researchers with the Center for Bioelectronic Medicine’s Neural Bypass Lab stimulate different areas of the arm to identify which muscle groups control the various fine motor movements of the hand and arm. The information obtained aids in developing neural bypass technology, which may ultimately allow paralyzed patients to perform hand and arm movements autonomously via their own brain signals. (Photos courtesy of The Feinstein Institute for Medical Research.)

However, we really didn’t know what to expect when we began this process, and it has been exciting to see his progress. Originally, we weren’t sure if it would be possible to restore not only functional hand movement but individual finger movement, and that’s because we’ve continued learning through the years (see above). I’ve spent a lot of time in this area and have put a lot of effort into trying to understand how the brain works and how the brain’s neurons modulate. Especially in a case where someone has had a severe injury, there’s always a question of the brain remapping and whether the signals will be present for movement and whether they will modulate strongly enough. Can we decipher them? Can we decode them? These are all the big questions. Then, can we translate these signals—if we can decode them—into a language the muscles can understand? That’s what we’ve been working on and have made some really nice progress in this effort.
IEEE Pulse: The work you have done with restoring hand movement has far-reaching effects. What do you see as the next steps in this area?
Bouton: Sometimes it seems we are so concentrated on restoring movement for someone with paralysis that we neglect the other losses of function, such as sensation. There is proprioception, which is the sense of limb position; there is the sense of touch, which is also significant. Moving forward, this is a key area to investigate. There’s been some great preliminary work in other groups, but no one yet has restored movement and sensation simultaneously in a human participant. Also down the road, restoring lower-extremity movement or function will be extremely important. These are the kinds of things I think are essential questions that should be tackled in the future.
IEEE Pulse: I was captivated by what you said about sensation. What technology would be required to be able to activate those senses?
Bouton: The technology required would be, first, a way to pick up the sensory information—let’s say joint position—and that might be done with sensors, including different sensors on the arm. Then you would need a way of taking that information and encoding it—the opposite of decoding it—so that we could introduce that information to the brain through the sensory cortex. There are still a lot of questions around that process, but those are the kinds of technologies and new insights in terms of neuroscience that we would have to address or gain.
IEEE Pulse: Does that tie in to work on digital senses going on right now?
Bouton: Absolutely. We actually explored the idea of intercepting signals from the olfactory area along with neural signals. Our thought was that if you could learn to understand or decipher signals from the olfactory glands, for example, this would give you not only considerable insight into how that system works but a new way to create an electronic nose, if you will. We can learn so much as we tackle different senses. Of course, with hearing there have been many years of work trying to encode information for implants and restore hearing. Some of this work is limited by the number of electrodes that you can have, some of it is limited by our knowledge of how to encode and how knowledge is encoded in the brain, but as we’ve studied the different senses, we’re learning more and more, and that could open avenues like the electronic nose and biologically inspired types of sensors.
IEEE Pulse: Can you share your impressions of the ethical boundaries of work that’s being done to understand the brain and how it works and what you would like to see happen regarding discussions on ethical use of sensors and implants?
Bouton: Well, I think that, with any new biotechnology or medical technology, we always have to consider the ethics that surround that technology, and, any time we do an invasive procedure or have a technology that involves surgery, we need to keep safety and patient well-being at the forefront of our minds. Just as the FDA [U.S. Food and Drug Administration] is charged with balancing risk and benefit, we too must always think about the benefits to the patient. So if it’s someone who has a debilitating condition—for example, someone who has a spinal cord injury—we need to ask, “Okay, what are the risks of this technology and what are the benefits?” If we always keep that in mind and strive to keep these technologies safe, that’s key. But at the same time, if we can develop new technologies that offer benefits and treatments and options that have the potential to restore lost function in a condition that currently doesn’t have a cure or doesn’t have a lot of options available for restoring function, then I think that is something we need to keep working toward and we need to keep putting our energies into.
Now, you can consider ethical challenges in regard to other scenarios. For example, let’s say we develop brain implant technologies that could not only help treat a debilitating condition but that could perhaps augment our cognitive abilities. Well, there are certainly ethical questions around this possibility. Is that likely to happen someday? Is it going to cause a divide between the haves and the have nots, people who can afford this kind of technology versus people who can’t? Does it give those folks an unfair advantage? I’m not an ethicist, but I think those are important questions that have to be resolved in the near future.
One more thought on this is actually somewhat funny. Today, with calculators and smartphones, you go into a classroom and the teacher says, “Turn off your phones.” If we have brain implants, will the teacher ask you to turn off your implant? It makes things a bit more difficult and much more complicated when we are talking about brain implants and cognitive augmentation. There are a lot of questions, and it’s hard to know what is the right answer.
IEEE Pulse: Ethical challenges seem to be just one area of many diverse challenges in this field. Are there challenges specifically in your work that you grapple with, or is there something you’re trying to get over a threshold on in your specific research? Do you see a resolution?
Bouton: Yes, something you said sparked this thought of acceleration. We always have to look at safety, obviously, but if we could find ways to accelerate these studies and really move some of these ideas out of the lab and even out of clinical studies and bring them into the home and to patients, then that would be very valuable. In fact, I think that’s critical. The challenge is always that risk/benefit ratio, and regulatory bodies like the FDA are doing their jobs in always looking into the safety of the patients. Although we have to consider the efficacy of devices and how well they work, in the end, it’s also all of our responsibilities to try to develop new treatment options and develop new technologies that can address conditions that don’t have options available.
Anything we can do to perhaps streamline some of these processes and try to develop accelerated pathways is very important. I know there’s some work being done in the neurotechnology area, and if we can continue to look for ways to be a little more efficient but still yield safe studies and technologies for patients, that would be great. I think that one of the keys to that is communication. If we can keep communication lines open between scientists, engineers, and regulatory agencies as well as the different government agencies, that will help tremendously. I’ve seen that already starting to happen, again in the neurotechnology space and the bioelectronic medicine space, but I think we still have some work to do in that area.
IEEE Pulse: Do you think that machine-learning technology has the potential to help streamline these processes? What might these efficiencies look like?
Bouton: Do you know the phrase “garbage in, garbage out”? Well, with any kind of machine-learning approach, the quality of the output is only going to be as good as the quality of the input, and so one of the toughest things is to generate the right input. When we have these new technologies that are implanted in the brain, for example, or on nerves, we don’t have perfect numerical models or data that emulate or simulate some of these scenarios, so we have to do in vivo experiments and study these in humans to really collect the data that we need.
To take a design or an idea like a new brain implant or technology and put it through a machine-learning process, it’s really going to come down to how good are the inputs. It’s difficult to represent a new technology and how it will behave in tissue if you don’t have a good model, and we still are working on that. So, for now, we might be able to take data that’s been recorded in a large number or a given number of study participants, and, through a machine-learning approach, we might be able to find patterns common to certain people or even to certain diseases.
In addition, we’re working on an area we call real-time diagnostics, where we are using these same ideas of decoding signals in the brain. In different nerve pathways like the vagus nerve, we’re actually intercepting and deciphering signals from organs in the body that are traveling up to the brain and trying to pull out diagnostic information. So imagine taking out your cell phone, looking at it, and getting an instant reading on all sorts of biomarkers or levels in your body like inflammatory markers or glucose or cholesterol or anything you can think of in terms of what you would see in the usual blood tests. We’ve collected some data this year and are finding some very interesting things in these neural signals (see below). So maybe we can start to use machine-learning processes to look at that kind of data too, in order to recognize different types of diseases or diagnose diseases based on this information.

In a class 100 clean room, researchers in the Feinstein Institute’s Center for Bioelectronic Medicine’s Microfabrication Lab develop prototype bioelectronic medicine devices that can be used to record and simulate neural signals to monitor and treat disease. (Photo courtesy of The Feinstein Institute for Medical Research.)
In a class 100 clean room, researchers in the Feinstein Institute’s Center for Bioelectronic Medicine’s Microfabrication Lab develop prototype bioelectronic medicine devices that can be used to record and simulate neural signals to monitor and treat disease. (Photo courtesy of The Feinstein Institute for Medical Research.)

For this real-time diagnostics idea—sometimes we call it the electronic blood test—imagine having a chip on a nerve in your body, intercepting all these messages and basically being able to keep track of what’s going on. By the way, you have millions of receptors—chemoreceptors—in your body and throughout all your organs that pick up all sorts of interesting and useful information, and a lot of it is fed back up to your brain through different nerves, like the vagus nerve. That’s what we’re working on now, and we’re really excited about the possibilities.
IEEE Pulse: That’s an interesting way of changing perspective and looking at the information coming to the brain and not just what the brain is controlling. This underscores the idea of the brain as similar to higher management—a term you’ve used before—where it doesn’t necessarily know everything that’s going on at every level. That is, the day-to-day work is being done somewhere else, which makes sense when you think about the body trying to heal a specific area, for example.
Bouton: Yes, just think about it for a moment. There’s an expression we often use, that “we have a gut feeling” about something. Well, guess what? That is real. In fact, your gastrointestinal system is heavily innervated by the nervous system—it is one of the most complex networks besides the brain and the spinal cord. It’s almost unbelievable how much information is going to and from your gastrointestinal system, so if we have the “butterflies” or “that gut feeling,” those are all real signals being sent to your brain.
The body also has multiple local circuits, and that’s to your point—exactly how involved is the brain? Maybe the brain is just aware of certain things—you know when you’re not feeling well and so on—but there are millions of local processes and local networks that are working more independently. One example is in your motor system, where the spinal cord is coordinating multiple things such as rhythmic movement and walking. Even maintaining a grasp on an object is controlled by neurons in your spinal cord. There are 10 million neurons in the spinal cord, and there are certainly signals going up to the brain, so we’re still trying to figure out who—that is, which system or organ—is doing what. Essentially, we know that there’s a lot happening in the body and in the spinal cord, but the brain’s getting all the credit.
IEEE Pulse: That’s right, the brain’s getting all the credit. It’s quite fascinating to think about how much information might be available throughout the body’s electrical circuitry. How do you envision the role of bioelectronic medicine in the future?
Bouton: At the end of the day, the nervous system is a vast network that extends to every corner of our bodies and is involved in an incredible array of processes—both when we are healthy and also when we are battling disease. The idea of bioelectronic medicine is to tap into that vast network, “listen in,” and decode neural messages to extract diagnostic information and to electronically stimulate neural pathways—in a way, “speaking” the neural language.
This new approach leverages bioelectronic technology, rather than drugs, to modulate molecular processes and targets to fight disease naturally and even reroute signals in the body to treat debilitating injuries such as paralysis. We hope this will one day revolutionize how medicine is practiced and offer new treatment options for conditions where cures do not exist.

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