“You might not know it yet, but you do want to be a neuroscientist, and this compelling book will show you why and how. A wonderful, entertaining, yet eminently practical guide to joining the quest to solve our deepest, richest scientific challenge—understanding the brain.”

—Mark D. Humphries, University of Nottingham

In today’s featured SFN post, Ashley Juavinett explores some trends that are emerging in the neuroscience field. These ideas and many more are explored in more depth in So You Want to Be a Neuroscientist?, which offers an honest look at the evolving field for prospective neuroscientists.

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Each year when we meet for the Society for Neuroscience (SfN) meeting, I feel all at once overwhelmed and exhilarated. SfN is a chance to reflect on how far we’ve come and also an unparalleled opportunity to peek at the future of our field.

If we look to recent history and what top leaders in the field are saying as a guide, there are a few trends we can reasonably expect to continue into the next five or ten years:

1. We’ll see more technological innovation. Neuroscientists love their technical toys because they provide windows of understanding into the brain’s complexity. Since the early days of electrophysiology, the number of simultaneously recorded neurons that we can image or record has grown exponentially. We’re also improving our means of noninvasively stimulating the human brain, as well as figuring out clever ways to manipulate genes, proteins, and nerve cells with potentially less disturbance to their endogenous systems.
2. We’ll need to wrangle larger, more complex datasets. Largely as a result of this steadily improving ability to record from chunks of the brain, the amount of data we have is quickly increasing in both size and complexity. One fun thought experiment: at current resolutions, one mouse brain alone could generate 500 petabytes of electron microscopy data and another 500 petabytes of imaging data. As others have pointed out, although the amount of data is growing, our ability to actually make sense of it is growing much more slowly.
3. We need more collaboration. With all of this novel technology and big data, we need engineers, experimentalists, and theorists to collaborate on large-scale, inherently interdisciplinary projects. This sort of collaboration, especially on the international scale, has been increasing in neuroscience over the past decade. There are many impressive examples of this, including the Allen Institute for Brain Science and the International Brain Laboratory. It’s likely that the next decade will see more teams that are breaking down expertise and country boundaries.

Of course, if 2020 taught us anything, it’s that the future is anything but perfectly predictable. Still, if you’re a trainee, there are a few things you can count on as being valuable skills in this brave new world: quantitative skills and coding, as well as the ability to collaborate with folks of different backgrounds. The next phase of neuroscience needs people who can wrangle as well as make sense of big data. Plus, neuroscience is diversifying in all sorts of ways—learn how to speak the language of different fields, and you’ll be a breezy traveler in our ever-changing landscape.

Cheers to another SfN and to all of the promising advances and perplexing insights that it will undoubtedly bring.

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