For all the medical advances in recent years, neurological and psychiatric disorders— Alzheimer’s Disease, Parkinson’s Disease, autism, and schizophrenia—remain largely a mystery. One reason is the incredibly complex structure of the brain. To encourage exploration of this unknown territory, the National Science Foundation (NSF) awarded Cornell University $9 million over five years to establish a neurotechnology hub, dedicated to developing new technologies for imaging the brain, then disseminating them to the wider neuroscience community.
The focus of the Cornell Neurotechnology (NeuroNex) Hub is optical imaging. Chris Xu, Applied and Engineering Physics, who is the lead principal investigator (PI) for the hub, says, “We’re pushing for imaging depth, speed, and volume. We want to image as much of the brain and the nervous system as we can in as short of a time as we can. That will enable us to attack neuroscience problems that are currently impossible.”
Co-PIs include Joseph R. Fetcho, Neurobiology and Behavior; Nilay Yapici, Neurobiology and Behavior; Chris Schaffer, Meinig School of Biomedical Engineering; and Mert R. Sabuncu, Electrical and Computer Engineering/Meinig School of Biomedical Engineering.
Cornell Neurotech—Reflecting Cornell’s Collaborative Spirit
The hub comes on the heels of the Cornell Neurotechnology Program, led by Fetcho and Xu. They formed the program in 2015 in partnership with their college deans—Gretchen Ritter, the Harold Tanner Dean of the College of Arts and Sciences, and Lance R. Collins, the Joseph Silbert Dean of the College of Engineering. A multimillion-dollar gift from the Mong Family Foundation provided early support. “The hub is the realization of efforts that have been on-going for the past two to three years to create and strengthen a program in neurotechnology at Cornell,” says Ritter. “This builds on one of the university’s greatest strengths, which is our ability to foster interdisciplinary, cutting-edge research.”
Cornell Neurotech originally grew out of collaborations between three faculty members: Xu, Schaffer, and Fetcho. The three had established a synergistic working relationship amongst themselves that led to the vision of an official Cornell Neurotechnology Program. They soon brought others from the Cornell community onboard with the idea, including Andrew H. Bass, formerly Senior Associate Vice Provost for Research. “The Neurotechnology Program is a grassroots faculty endeavor,” says Bass. “These people knew what they were able to do together. Being a neuroscientist myself, I recognized how special their collaborations were and what they could do, both for the Cornell community and others outside of Cornell. I was glad to advise them to organize their effort.”
Securing the NSF grant for the neurotechnology hub is an important step in establishing Cornell’s preeminence in this new area. “Doing something with respect to understanding the brain is especially important for Cornell,” says Fetcho. “Brain diseases are becoming huge societal problems. We don’t understand how the brain works, but yet it does pretty much everything that makes us human beings.”
Advanced Tools for Seeing How the Brain Really Works
Xu’s expertise in optical imaging takes center stage as he and his collaborators develop new tools that will enable them to map the brains of many different animals. “We will use the tools to address behavior in a variety of species and then extract the fundamental principles for how brains work,” explains Fetcho, who works with zebrafish. He notes that Yapici studies flies and Schaffer investigates mice, so the animal models represented by the PIs already span a wide range of animal phyla and sizes. At the same time, researchers at Cornell who are investigating neurobiological questions, using other species, will also be able to access the hub’s technology and add to the diversity of animal models.
The hub’s plan is carefully structured with a three-step approach. First, the engineers will develop new imaging tools to allow access to previously inaccessible brain regions. Then the neuroscientists and data experts will demonstrate the tools by using them to address fundamental questions about how nervous systems generate behaviors. Finally, the new tools will be disseminated to the wider neuroscience community through scientific workshops, lab demonstrations, and synergistic collaborations with technology companies and other research labs outside Cornell.
Deep Brain Imaging
The researchers will develop three specific brain imaging tools. The first is a multiphoton microscope that uses lasers and fluorescent tags at the cellular level to register brain activity. This is a two- and three-photon combined system Xu developed in his lab, building on the work of his PhD adviser, Watt W. Webb. Webb and his postdoctoral associate Winfred Denk—now director of the Max Planck Institute of Neurobiology in Martinsreid, Germany—created the breakthrough two-photon microscope at Cornell in 1990. “We’ve demonstrated that three-photon microscopy works well for deep brain imaging,” Xu says, “and now we want to build an infrastructure for it.”
“Brain diseases are becoming huge societal problems. We don’t understand how the brain works, but yet it does pretty much everything that makes us human beings.”
Xu has used the three-photon microscope on mouse models to see deep inside the living brain without damaging it. Now, the next step is to use the tool in other species. “People want to use it on fish, for example,” he says. “That’s a different problem. It’s good for us to work on this because we are really well versed in quantitative measurements of optical events. We can work those out, so the people in biology don’t have to worry about it. That’s part of the infrastructure we want to build, which is very similar to what Cornell did in the 1990s for two-photon microscopy. Our goal is to tell people exactly how this tool works, what exactly it’s good at, and how much better it works than other tools.” While perfecting the microscope, Xu will also continue to work closely with the laser, microscope, and software companies with which he already has a relationship. “We’ll show them how to make the best tool possible,” he says. “Then they’ll make the microscopes for the broader community of scientists.”
Seeing Different Areas Simultaneously
The second tool the hub will develop is a one-of-a-kind multiphoton microscope able to look at two different areas at the same time. Schaffer leads this project. Using mouse models, Schaffer investigates the mechanisms of unconscious walking on a smooth surface—controlled by central pattern generator circuits in the spinal cord—versus brain-directed conscious limb movement used to navigate through obstacles. “One of our goals is to figure out how the pattern generator circuits work,” Schaffer says. “But another goal is to understand how an animal switches between conscious and unconscious locomotion.”
To investigate the switching mechanism, Schaffer needs to simultaneously image neural activity patterns in both the brain and the spinal cord of the mouse. “We will develop this tool, leveraging our first technique of multiphoton imaging,” Xu says. “Using our technique, Chris Schaffer’s lab is currently the only one in the world that can image neural activity deep in the spinal cord of a live animal. We’re going to expand on that and image the brain at the same time.”
A Microscopy System That Adapts to Samples and Tasks
The third tool Xu and his collaborators hope to develop pushes the boundaries of possibility even further. It will be a completely new form of illumination system and microscope developed together that can adapt to the needs of the sample and the study. “It’s a novel conceptual change for imaging,” says Xu. “In some sense, the sample will be part of the microscope.” As soon as a specimen goes under the microscope, the tool will re-adapt to make sure it is configured in the best way for the size and makeup of the sample and the tasks at hand.
Xu plans to work out any problems with the imaging technology tools in his own lab before moving them into the hub’s lab where neuroscientists, based inside and outside the hub, can immediately use them. Known by the acronym LINC (Laboratory for Innovative Neurotechnology at Cornell), the lab will function as a true link between physics, engineering, and neuroscience. The university and all the PIs together will own and operate it, which is an important aspect that sets it apart. “When you come into my lab, you’re a guest in my house,” Xu explains. “But in the LINC, we don’t build a wall. No one owns it. When you come into the LINC, you come in as an equal.”
Studying How Hunger Affects the Brain
While emphasis in the hub is on the development of the tools, equally important is how neuroscientists like Yapici and Fetcho, who will be pursuing their own research questions, use them. Yapici wants to understand how hunger affects the brain, specifically in flies. She uses fruit flies as a genetic model because they have all the complex behaviors that mammals have, but their nervous systems are smaller in number of neurons. This allows the possibility of imaging the whole brain at one time.
Yapici plans to use the multiphoton microscope to image an entire fly brain while the insect is engaged in behavior connected to food deprivation. This has never been done before, because previous imaging systems didn’t have sufficient resolution and depth of imaging. Also, older methods required the removal of the protective cuticle that surrounds the fly’s body, including its brain. Once the cuticle is removed, a fly will only live a few hours. “We won’t have to remove the cuticle with the new multiphoton imaging methods developed in the hub,” Yapici says. “We can penetrate the intact cuticle completely without harming the animal. This will allow us to do chronic imaging of a live animal, where we image the brain at intervals, say six hours, twelve hours, and so on, to see how the brain changes activity as the fly gets hungry. This has never been achieved in flies or any other animal species, and I think it will be amazing to capture how hunger is encoded in an animal brain. Our goal is to study this in the fly brain first and identify basic principles of neural encoding of hunger states, before we search for similar mechanisms in vertebrates.”
Exploring Brain Motor Circuits
Fetcho, who works with zebrafish, studies the principles underlying the construction of brain motor circuits. Until now, his research has been with young zebrafish, who are transparent until about three weeks old. Fetcho has been able to watch as the young fish’s nervous system generates columns of nerve cells that connect in orderly ways. But as the fish gets older, it loses its transparency. That is just around the time the orderly columns of nerve cells begin to dissipate, as the cells move around and form new connections in the maturing brain. “There’s a simple pattern early in life,” Fetcho says. “The motor circuits are constructed via principles that we think are used by all vertebrates. But then the neurons migrate as the animal grows into adulthood, and they become re-sorted.”
The tools and approaches developed in the neurotechnology hub should allow Fetcho and his collaborators to observe this re-sorting process in live adult fish. That is an exciting prospect, Fetcho says, because adult zebrafish have more refined motor coordination. They also reach sexual maturity around three months of age, which results in a whole range of behaviors that are much more complicated than anything in which young fish engage.
All That Data, Analyzed and Made Useful
As the neurotechnology hub’s tools are perfected and the neuroscientists make their observations, huge amounts of data will be generated and will need to be analyzed and correlated. That’s where Sabuncu comes in. With expertise in biomedical data analysis, he moves to Cornell in fall 2017 from Massachusetts General Hospital and Harvard Medical School. “At Cornell I’ll be developing novel algorithm technology for making sense of and exploiting large-scale biomedical data,” says Sabuncu, who will be handling the hub’s data management plan. “The neurotechnology hub is exciting to me because it will let me look at data from different animal models and at different scales.”
Sabuncu envisions his lab’s approach will center on developing machine learning algorithms to understand patterns of association in the data. “We’ve always known that our ways of probing the way the brain works in animal models has been overly simplistic,” Sabuncu says. “The constraint has been the data you could acquire, but the neurotechnology hub should stimulate research that will allow us to gather more sophisticated, big data. When you are looking at larger scales, you’re looking at thousands, potentially tens of thousands, of neurons activating simultaneously in complex patterns. You cannot get away with simple statistical analysis. You need to think about large-scale patterns that relate to the complex behavioral phenotypes these animals display.”
Getting the Knowledge into the Hands of the Scientific Community
Another crucial part of the hub’s mission is to disseminate information about the tools and the research they facilitate. This includes research done by the hub’s PIs and by other neuroscientists at Cornell and outside the university. Part of Yapici’s role is to organize workshops to teach the technologies to the neuroscience community. A formal event each year will bring top national and international neuroscience researchers, students, and postdocs to Cornell. The tools will be available for participants to test on their own samples, so that they can experience a hands-on demonstration, but even more importantly, scientists can visit and learn how to apply the hub’s technology to their own work year-round. The hub will also collaborate with labs at the Massachusetts Institute of Technology, Princeton University, and the Howard Hughes Medical Institute Janelia Research Campus.
“The hub will facilitate an understanding of the normal function of the nervous system as well as provide insight into neurological diseases,” says Dean Collins of Engineering. “The groundbreaking data from these experiments will help unlock the mysteries of the brain and provide insights into how changes in the firing patterns and connections of the neurons can lead to the serious diseases that plague the brain."
Schaffer, who has devoted a large part of his research to neuroscience questions pertaining to Alzheimer’s, agrees. “We need to understand normal function to even begin to know the right questions to ask about disease state function,” he says. He points out that the hub’s technologies will also increase how far he will be able to see deep within the brain. With current tools, Schaffer is only able to see down to approximately 700 microns in mouse models. “That’s basically the cortex,” he explains. “But the first thing Alzheimer’s strikes is not cortical function but memory, and that’s in the hippocampus, which lies much deeper. The new imaging technology we will develop in the hub will enable us to routinely image at this depth.”
Alzheimer’s is just one of a host of neurological diseases waiting to be explored by the unprecedented collaborative opportunity the hub represents. “The hub is where engineering comes together with the basic sciences to do something spectacular,” Collins says, “and that will set it apart from other institutions. I think there will be many more opportunities coming down the road from this collaborative group of faculty. I’m thrilled by what they’ve been able to do in such short order.”