Unlike biochemistry and psychology, brain science did not exist as a separate academic field until the middle of the 20th century. In recent decades, neuroscience has emerged as a star among the biological disciplines.
In 2014 a workshop organized by the National Academy of Medicine met to ponder the question of whether all bodes well for the scientists-to-be who are now getting their PhDs and laboring away at postdoctoral fellowships. Will the field be able to absorb this wealth of new talent—and is it preparing students with the quantitative skills needed to understand the workings of an organ with some 86 billion neurons and hundreds of trillions of connections among all of those cells?
Steven Hyman of the Broad Institute of Harvard and MIT, who helped with the planning of the workshop and was recently president of the Society for Neuroscience (SfN), welcomed the flood of doctoral students choosing neuroscience, but warned: “Insofar as talented young people are discouraged from academic careers by funding levels so low that they produce debilitating levels of competition or simply foreclose opportunities, the U.S. and the world are losing an incredibly precious resource.”
I got in touch with one member of the National Academy of Medicine panel, Huda Akil of the University of Michigan Medical School, the lead author on a paper in Neuron that summarized the workshop’s findings. Akil, also a former SfN president, is a noted researcher in the neurobiology of emotions.
[An edited transcript of the interview follows.]
There's a significant increase in the number of doctorates in neuroscience, but the number of people working as scientists in academia a decade after their postdoctoral fellowship is decreasing. Is that a problem for the field?
If we are losing people who are potentially incredible scientists, who have it in them to be able to make really great discoveries but who drift off—not for lack of talent or lack of interest but because they're getting discouraged by the atmosphere or by the odds of getting funding for their science—then that is a significant problem.
If we attract a lot of people who want to apply their knowledge, not to make discoveries but to illuminate other areas such as teaching, dealing with social issues or even creating games, then that is great. But what I hope does not happen is that we lose people who have the talent, the mind, the curiosity and the desire to be really great scientists but they give up for the wrong reasons.
Do you think that is happening?
There is no way of knowing what people's motivations are for moving in another direction. Sometimes it's for good reasons because they discover that they don't have the temperament. Research requires tolerance for failure. It requires risk taking. It requires enough confidence to take a lot of criticism and get turned down and still stick with a path and an idea and keep after it. So not everybody has the temperament, the personality to do this, and if they leave because of that, that is fine. Other people might leave for various family reasons and so on. But what I hope does not happen is that people leave because it is too anxiety-provoking, or they believe there aren’t enough positions, without actually trying to test that.
What do you mean by “anxiety-provoking”?
I think that sometimes the students come in full of excitement and they talk to a professor who is a pretty well known scientist and want to know whether they can get a research rotation in a particular lab, and that scientist says he or she isn’t taking students right now because a grant is up for renewal and the scientist has to support the people onboard now and won't be sure about new openings for another year. Then they go to the next person and they hear that that person just lost a grant. They think that a scientist might be doing really cool things and yet he or she can't be sure about supporting their students, and they start getting anxious about whether they will be able to succeed and withstand this kind of uncertainty.
One of the things your paper seemed to suggest is that the way jobs are structured in an academic research setting needs to change to open up new possibilities for people to stay in academia. The paper talks about what you call a new position—staff scientist.
The brain is really complicated and we have made progress but we have a very far road ahead of us. It's not going to be explained by genetics alone, by anatomy alone, by biochemistry alone. It's going to require all the tools of human thought and technology for us to shed light on it in a true and real way—and therefore the lone scientist working away in a corner is going to become a thing of the past. We really have to work in teams, which means that there is a role for different people doing different types of tasks on these teams. Not everybody has to be the boss. In my own operation I can’t do all the different studies that members of our team conduct. Some people are awesome at computation, at informatics; others at bench science, at technique development and the like. The argument in this paper is that there is room for lots of different kinds of people, lots of different kinds of minds playing many different roles in the context of larger scientific teams. And this should create opportunities for new stable positions for young neuroscientists.
Can you give me some examples?
For example, coordination and oversight of neuroscience research cores. As bioscience is getting more and more complex you need core centers not only for genotyping but handling the data, analyzing the data. People who have mastered these skills know something extremely valuable of vital use to neuroscience.
The paper made the point that there needs to be strengthening of the neuroscience curriculum in some areas such as data analytics and statistics.
You cannot really be a physicist without knowing math. You should also not call yourself a neuroscientist without having more of these skills. It didn't used to be necessary but it is becoming more necessary.
Do you think there's a lack of training at this point?
I think as the field has evolved, the need for using new technologies has grown. Our students are not getting enough training in them. Also, I think having these skills travels very well. Even if you leave neuroscience or academia, you will are going to be able to deploy them in a variety of different ways.
Overall, it seems like what you’re trying to address here is that supply is greater than the demand.
No, I would amend that. I would say that if money were no object, the supply is not greater than the demand. The actual demand for understanding the brain is huge. There is a lot of work to be done and the opportunities are also huge. The demand that is not matching supply is the number of academic positions, and there isn’t an infinite amount of money.
We never imagined this degree of interest for neuroscience and we imagined that we were always training more people like us. We really created these graduate programs to be training grounds for future academic neuroscientists, and I remember when I first began mentoring people, I would be disappointed when people went into Big Pharma. It was almost like I had failed in my training. I don’t feel that way anymore at all.
What has changed?
Over time we all had to revise our attitudes and realize that there are more paths to contribute to neuroscience, and we started incorporating industry and then biotech. I see this now as the next phase where the scope is even broader than that. It's not just academia. It's not just academia and industry. It's nonprofits. It's social policy. It’s science writing. It's man–machine interfaces. It’s big data or education or any area where knowledge of the brain is relevant. All of this is going to push the limits of our knowledge as professors because we don't know as much about how things work outside academia.
So what does this mean for students?
We want to make sure that if you have made the commitment to study neuroscience, you know that your investment in time, energy, money feels like it is worthwhile and that this knowledge and intelligence and curiosity are deployed in a way that is good for you, for your family and for society. If that is through academic neuroscience per se—fantastic. If not and you go and use it at Google and do neuroscience in a very different type of setting, that is fantastic, too.
Do you think these new approaches to producing a new generation of neuroscientists could also help in translating basic research into new treatments for brain diseases?
Brain disorders are intrinsically very complicated. If we need precision medicine to differentiate between two different kinds of lung cancer, you can imagine the differences between two different kinds of schizophrenia or autism. They really are very different but they just get tagged under one name. Computational tools are really going to be important for translation because we will need a lot of data to understand which variables are critical and which ones represent noise. We won’t be able to do this without working together in multidisciplinary teams. Training neuroscientists with many different skills, giving them many different opportunities and offering them a variety of substantive roles is absolutely critical, both for basic understanding of the brain and especially for translating that knowledge for better understanding and treatment of brain disorders.