UW-Madison engineers brought together colleagues from across the neuroscience spectrum recently to spark a more comprehensive discussion about the vast challenges and opportunities ahead for brain research and new neurological therapies.
The first-ever UW-Madison Neuroimaging, Computational Neuroscience, and Neuroengineering Workshop took place April 27 through 30, 2015, on the UW-Madison campus and featured 15 invited speakers from fields including engineering, psychology, computer science, cognitive science, statistics, experimental physics, and brain imaging. Electrical and Computer Engineering Associate Professor and Wisconsin Institute for Discovery fellow Rebecca Willett and her co-organizers wanted to seize opportunities to build a stronger transdisciplinary neuroengineering community at UW-Madison.
The conference was supported by a grant from the College of Engineering Research Innovation Committee, which funds multidisciplinary research projects proposed by College of Engineering faculty. The conference was organized by Willett, Electrical and Computer Engineering Associate Professor Nam Sung Kim, Philip Dunham Reed Professor of Electrical and Computer Engineering Mikko Lipasti, Biomedical Engineering Professor and Chair Beth Meyerand, McFarland-Bascom Professor of Electrical and Computer Engineering Robert Nowak, Lynn H. Matthias Professor of Electrical and Computer Engineering Barry Van Veen, Biomedical Engineering Professor Justin Williams and Industrial and Systems Engineering and Computer Sciences Professor Stephen Wright.
“When cognitive scientists like University of California-Berkeley professor Jack Gallant get up and talk about how they’re using existing machine learning tools to better understand how the brain functions, they simultaneously identify the shortcomings of those tools and new opportunities for research,” Willett says. “Likewise, if someone in signal processing or machine learning is talking about new classes of algorithms, then brain researchers may identify new applications for those algorithms.” Willett noted similar cross-disciplinary interactions among computer engineers, neuroscientists, optimization experts, and neuroengineers, and psychologists.
The talks covered a variety of specific facets of neuroscience: UW-Milwaukee Electrical Engineering Associate Professor Ramin Pashaie kicked off the conference with a talk on optogenetics, a new method of genetically engineering brain cells that can be stimulated with light; Simons Foundation scientist Dmitri Chklovskii delved into his efforts to develop an algorithmic theory of neuronal function; IBM T.J. Watson Research Center Computational Biology Center researcher Irina Rish gave a talk on developing computational models for analyzing brain data from sources such as functional MRI, which shows how brain activity levels vary across space and time as we complete different tasks.
Beyond the talks, the conference focused on catalyzing a community focused on broad questions of brain science that spanned traditional academic disciplines, confronting myriad unknowns about how the brain actually works and the scientific, economic and cultural obstacles to more interdisciplinary, application-oriented research in neuroscience. Kip Ludwig, program director for neuroengineering at the National Institutes for Health and leader of President Barack Obama’s Brain Research through Advancing Neurotechnologies (BRAIN) initiative, used his own previous experience developing therapies for hypertension at the medical device company CVRx as a jumping-off point for a discussion of these challenges.
In his talk, Ludwig said CVRx’s struggles to develop accurate clinical trials for its technology highlight how little scientists and practitioners really know about brain function. Researchers can at times develop technologies that successfully stimulate neural activity to treat a patient but still not know exactly what it is they’re stimulating. And when research transitions from animal subjects to human ones, that only compounds the unknowns, because animals and humans have very different neurophysiology, and, as Ludwig pointed out—only half-jokingly—you cannot ask a pig if it’s depressed and expect an answer.
“That’s the problem if you don’t know the biology—even if you get it to work, you don’t know how to make it work better,” Ludwig said. “If you don’t understand the biology, it’s really hard to predict clinical results.”
The snags of clinical trials alone can create significant delays in getting regulatory approval and, for private-sector researchers, makes funding and making one’s money back quite the uphill battle. “The FDA isn’t the biggest hurdle anymore,” Ludwig said. “It’s getting reimbursement.”
The solution, Ludwig says, is for academia, industry and government to all develop a greater spirit of partnership, and for agencies like the NIH to continue working to create new pathways for neuroengineering research funding. He noted that the NIH has historically been very centered around funding research that produces drugs, but has been putting more and more weight on medical devices, and wants to create a “handoff point” where industry partners and venture capitalists can step in to provide funding for clinical trials.
“One of the reasons we don’t know the biology is we don’t work and play well with others,” Ludwig said. “We need to convince companies that they need to be sharing the data. We need to grow the pie, not fight for a small share of a small pie.”
Willett says that same spirit of communication and collaboration would help UW-Madison build a more cohesive research environment for neuroengineering, capitalizing on existing strengths in advanced computing, medical research and biomedical engineering.
“We have people in biomedical engineering like Justin Williams who are building devices, people like Rob Nowak, Barry Van Veen, and me in electrical and computer engineering, and Beth Meyerand in biomedical engineering who are building algorithms, and people in the medical school who are actually working with patients,” Willet says, referring to colleagues who helped organize the conference. “We’re all ultimately interested in the same scientific questions, but there’s not a huge amount of interaction. We thought this would be a nice opportunity for people to get to know each others’ work and learn from one another.”
It’s appropriate the engineering faculty took the lead in organizing the conference, because engineers have much to contribute to the neuroscience field, and much to learn about it. The difficulty of getting reliable, reproducible results in brain research, Willett says, cries out for engineers’ expertise in designing experiments. And, given that her own research is heavily focused on the theoretical and computational aspects of sifting through massive data sets, Willett sees enticing challenges in interpreting the plethora of data that neuroscience researchers gather from neural probes, EEG and fMRI.
“If you just blindly apply existing technology and techniques to brain data, you’ll get something, but engineers have the skill set to develop new methods that are really specialized for the kinds of data these researchers are looking at, and the technologies that allow you to test new hypotheses or collect data at different scales,” she says.
Willett isn’t sure yet if the conference will become an annual event, but it’s already having an impact on a diverse array of UW-Madison researchers. Even the process of planning the conference, Willet says, sparked conversations that yielded new research proposals and a clearer idea of some of the themes within neuroengineering that can bring focus to interdisciplinary projects here on campus.
“If we develop this community, it could have a substantial impact on campus science,” Willett says.