What should the field prioritize over the next 10 years?

“One [priority] is the ability to use neuroscience approaches to understand naturalistic behavior. We studied the simple behavior because we had to. Now, it’s possible to ask the questions we always wanted to. Since hundreds of years ago, we wondered how animals do what they do over their lifetime. We can observe long-term learning and developments with cameras. That’s happening more. I can’t imagine it slowing down.”
—Bing Wen Brunton, professor of biology, University of Washington

“The field must progress toward more precise recording of brain function and behavior in the natural ecological niches of different species while comprehensively capturing their diverse sensory experiences during exploration and interaction with their natural environments. Using the wealth of data generated from this effort, we should strive to develop computational models that can accurately mimic animal behavior while closely capturing the sensorimotor processes in their brains. This effort should span across species, aiming to uncover both shared principles and species-specific adaptations. The main technical challenges lie in recording technologies, especially in natural settings where animals exhibit a much wider range of behaviors. Moreover, although there has been great success in AI developing large models trained on gigantic datasets, we still need to translate that knowledge to neuroscience.”
—Shahab Bakhtiari, assistant professor of psychology, University of Montreal

“For the first time, humanity faces the possibility of encountering more intelligent complex systems that may threaten its survival. Neuroscience can lead the efforts for understanding how cognitive processes emerge in the brain and in artificial systems, guiding AI models toward the safest artificial cognition possible. But in order to get there, we need methods to create explanatory models of cognition emerging from neurons’ computation, surpassing the correlational methods and studies spread across the field.”
—Ignacio Castillejo, doctoral student, Autonomous University of Madrid

“I’d like to see intermediate models. It’s great to have the mouse, and monkeys are difficult; ferrets would be great. They have complex behaviors. Alternate models should be considered. We need to be clear. Behaviors are very subjective. We can say a mouse has schizophrenia or has learned something. But we don’t know that they really learn. It’s an interpretation. We should be mindful of that. I hope in the future, we will be mindful of what we need to use the mouse for or what to do in vitro for humans or advanced systems.”
—Benjamin Deneen, professor and Dr. Russell J. and Marian K. Blattner Chair, Baylor College of Medicine

“Linking neural circuit architecture and function to the mechanics of the body and its interaction with the world.”
—Bradley Dickerson, assistant professor of neuroscience, Princeton University

“Basic, non-translational neuroscience and, in particular, fundamental simplistic and reductionist models. Historically, this has been the field that offered the greatest return on investment, the highest success rate and still is the most likely to make progress. The biggest obstacle is conceptual and political and has to do with a translational and applied drive linked to funding sources. Technically, we are penalizing the field by setting unrealistic targets and ridiculously ambitious goals, and shifting priorities and resources toward unattainable targets. The field should return to being ambitiously realistic.”
—Giorgio Gilestro, reader in systems neurobiology, Imperial College London

“Multi-scale modeling approaches that make testable predictions across levels/methods.”
—Avram Holmes, associate professor of psychiatry, Rutgers University

“Principles of dynamic brain network interactions. Technical challenges include long-term dynamic recordings from across the brain while participants/animals engage in cognitive behaviors, and the analysis of such large and complex datasets. The conceptual challenges include having the framework to approach such experiments. Current frameworks are based on reductionist paradigms cobbled together to study large-scale networks, while falling woefully short of meeting such a challenge.”
—Ben Huang, assistant professor of neuroscience, Weill Cornell Medicine

“We need to secure the possibility to just do basic discovery research without a view of translating everything. I guess in neuroscience there’s more and more voices asking us to work on clinically relevant projects or projects that are relevant for humans broadly. And I think that’s a mistake. So, we need to be more vocal about that and make sure that there’s dedicated funding streams available to discover principles in nervous systems broadly, not just in mice, not just in humans, but in all sorts of model systems.”
—Johannes Kohl, group leader, Francis Crick Institute

“Enable bottom-up neuroscience. Structure to function. The main challenge is the belief that neuroscience is on the right path.”
—Konrad Körding, Penn Integrated Knowledge Professor, University of Pennsylvania

“I think we kind of lose [sight of the] fact that our brains function in the context of our bodies, in the context of our social interaction with one another, and if we extract from that to try and simplify it, then we may miss important features of how brain function evolves, but also how different kinds of clinical disorders either manifest or don’t manifest because of the way the social environment might support somebody.”
—Randy McIntosh, director, Institute for Neuroscience and Neurotechnology, Simon Fraser University

“We still don’t understand well enough at the circuit level how information is processed in the brain. At the cellular level, we have a century of work. At the behavior level, also a century. At the circuit level, we only just got optical readout a decade ago.”
—Drew Robson, research group leader, Max Planck Institute for Biological Cybernetics

“For basic neuroscience, I think we will come to understand the action of neuromodulators, the five important ones. The ones that are targets of psychiatric drugs. We don’t understand how they affect the operation of neurocircuits. But in the future, what will happen—we will work out how they alter neurocircuits in vivo, how they act and how we understand them.
—Michael Stryker, professor of physiology, University of California, San Francisco

“The most important part is trying to understand high-dimensional recordings of brain data without reducing them. There’s this balancing act between being able to interpret a dataset and describe it in simple terms but also paying heed to the complexity of the dynamics that are represented in the signal, and I think that’s what needs to be developed in terms of furthering our understanding of what we’re looking at.”
—Jan Wessel, Clement T. and Sylvia H. Hanson Family Chair and professor of psychological and brain sciences, University of Iowa

“We have made brilliant strides in understanding distinct molecules, neurons and brain regions. But this work is often siloed … The sheer number of publications on the brain—far too many for any one person to keep up with and digest—only exacerbate this issue. However, integrative, cross-disciplinary work is essential to understand how the brain works. Innovative methods that synthesize broad portions of the existing literature and apply it to new models, ultimately to test against new hypotheses, will be an important step in unifying extant work and identifying gaps in knowledge across subfields toward the future.”
—Keiland Cooper, graduate student, University of California, Irvine

“The technological boom within the functional brain imaging field is undeniable. Yet, amidst all the technological innovations and computational algorithms introduced, we are at a crossroads as a field. More information is produced than knowledge is marinated. While enthusiasm for technological advancement is crucial for progress in any complex field, a pause facilitates space for the thorough reflection and integration of findings. In other words, instead of just ‘doing,’ we must stop and intentionally revisit what has been done to ascertain the implications of recent results.”
—Maya Foster, doctoral student, Yale University

“Finding ways to integrate results that span the scales of brain organization (micro, meso and macro) into more comprehensive theories of brain function.”
—Timothy Lawn, research fellow in radiology, Massachusetts General Hospital

“Integrating theory with data-driven approaches to understanding brain function. Theory too strongly disconnected from data can become too abstract (although still often interesting and relevant).”
—Rich Pang, postdoctoral research associate, Princeton University

“The fields of psychology and neuroscience still require a greater level of integration. To this day, few neuroscientists work on high-level psychological phenomena, and not all psychologists receive training in neuroscience. We may be tempted at this time to focus on integration of artificial intelligence into our field, but let’s not forget over 100 years of legacy from psychology, upon which much of the general public may base their opinion on the human brain, mental health and illness.”
—Michael Pascale, doctoral student, Boston University

“In the case of basic science, but for those who frame their work in the context of the human condition, I think the field should emphasize working with the communities their research aims to understand (i.e., volunteering in an addiction clinic, serving meals in a homeless shelter, where rates of mental illness are high, or volunteering at a walk for multiple sclerosis, ALS or Alzheimer’s disease patients). Bench research can be far removed from the populations it aims to learn about, and I think it will also lead to new ideas about how to translate certain aspects of our research.”
—Samantha R. White, postdoctoral fellow, U.S. National Institute of Mental Health

“I think we have to be talking between fields. We need to get to that point where people start saying, ‘This is the paper that influenced the entire field,’ instead of, ‘This is the paper that influenced my subfield.’ But it is never going to be the whole thing all at once. We are going to be talking across boundaries. We often talk about [how] we have a parts list. That is what we did in the BRAIN Initiative. We built a parts list for the brain, and now we have got all of these parts in this automobile store, but we still have to put an engine together, right? And so we are not going to be building the engine all at once, but at least we can make a carburetor. Can we make a carburetor? This is where I think we need to be at.”
—Anne West, professor of neurobiology, Duke University School of Medicine

“Integration of ethology, evolution and disease.”
—Karl Farrow, professor of biology, KU Leuven

“I think the priorities are neurodegenerative diseases. And that’s largely driven by, of course, a justified need from society. There are huge problems because of Parkinson’s, Alzheimer’s, ALS and so on and so forth. So we need to understand how the brain works but also how diseases arise, how they can be recognized early on, how they can be treated, maybe even prevented or even cured.”
—Jorg Grandl, associate professor of neurobiology, Duke University

“Explain consciousness and cure Alzheimer’s. Understanding consciousness is hampered by the fact that we barely know what it is and don’t yet understand how to think about the relationship between subjective experience and the physical system. Curing Alzheimer’s is hampered by the fact that current models have so far led to dead ends in terms of practicable treatment. A new perspective is needed. However, neither of these things really is what the field ‘as a whole’ should prioritize—neuroscience is so diverse that I think the question doesn’t quite make sense.”
—Erin Wamsley, associate professor of psychology, Furman University

“Translation of basic research to the clinic.”
—David Johannes Griessel, associate professor of pediatrics and child health, University of the Free State

“Unfortunately, we must focus on educating non-scientists about the way science (including neuroscience) is done and what its value is, rather than focusing on new advances. Our failure to communicate our value up to now has led to a crisis that will take a huge collective effort to overcome.”
—Robyn Crook, associate professor of biology, San Francisco State University