The Big Picture: Benefits of an Interdisciplinary Field

The department of Neuroscience at the University of Pittsburgh was established in 1983. This makes my dear old alma mater home to one of the oldest such departments in the nation.  They’re popping up all over the place nowadays (we’re up to 367 in the US), but make no mistake, Neuroscience as its own discipline is an infant in academic standards. So why is this? Was no one terribly interested in the brain before the 80s? Or is academic bureaucracy so toilsome that it took this long to get it recognized officially? The answer to the first is obviously no.  To the second, well yes probably, but that’s not the main reason.  What makes Neuroscience so difficult to institutionalize is exactly what makes it so powerful: its incredible interdisciplinariness.

Studying neuroscience requires integrating concepts from chemistry, genetics, psychology, evolutionary and molecular biology, pharmacology, and physiology. If you want to understand the methods you better have a grasp on medicine, statistics, and physics as well. And depending on your specific interests, you might also need acoustics, mechanics, linguistics, computer science, and/or mathematics. When people started doing neuroscience research, they came at it from one of these already-established fields.  Which is why, even still, rather than earning a BS in Neuroscience, many undergrads are forced to “take the neuroscience track” of their biology, psychology, or computer science major. Neuroscience is highly complex, and does not lend itself to easy administrating.

But, as I’ve said, it is this complexity and melding of fields at all levels that endows Neuroscience with such a strong explanatory power. Because, after all, the world is not as divided as our institutions of higher learning would make it seem. We have put up these walls to make our study of the universe simpler, and indeed they have. But it is necessary, at times, to make sure they haven’t become obstacles instead. And that is what Neuroscience is doing. Its willingness to dart across disciplinary lines and snatch up any potentially useful concept or technique ensures that our progress won’t be limited by past perspectives. And, quite honestly, when you’re attacking something as mysterious and complicated as the brain, you have to be willing to take help from wherever you can get it.

There are other, more personal benefits to working between disciplines as well. Attending a biochemistry-heavy lecture on transmitter synthesis in the morning, then spending the afternoon researching computational models of decision making is an exercise in mental dexterity.  Being able to jump between conceptual mindsets is a good skill to have. Furthermore, having a hand in many different fields means you are constantly exposed to new information and whole new concepts. Each time, you are practicing the process of understanding, getting better and faster at it. This exposure also helps you remember how to be a novice. That may seem like a bad trait for a seasoned scientist, but the fact is that some of the best insights can come from those who aren’t entrenched in the pre-existing dogma. As Suzuki says, “In the beginner’s mind there are many possibilities, but in the expert’s mind there are few.” Taking the novice perspective because you are forced to as an outsider can remind you that it is good practice to consider your own positions through that lens, and to question your assumptions occasionally. As Neil Thiese (a liver pathologist, complexity theorist, and fan of interdiscplinariness), stressed at a recent talk, you want to be able to see your data as it is presented to you –not as you expect it to be based on your existing beliefs. I believe practicing interdisciplinariness makes this easier. Finally, a field with a broad knowledge base can just lead to some pretty awesome ideas. My favorite example of the spoils of this in Neuroscience is groups like the Serre lab at Brown, that utilize computer vision to automate the tedious job of categorizing animal behavior. Thomas Serre develops computational models of visual information processing based on experimental data, and is applying those models to the design of lab equipment that can record rodent behavior and give quantitative descriptions of it to experimentalists. It’s a closed loop of neuroscience research!

Do you really want to know anything about Beowulf anymore anyhow?

Now for all my touting of the benefits of interdisciplinariness and having a broad and open mind, I do still appreciate the need for focus and walls. The process of educating a scientist is essentially a funnel that ends in a PhD thesis based on a very specific set of knowledge. This, by necessity and design, causes a detriment in most other areas of knowledge. There simply isn’t enough time to learn everything about everything, and to try to do so would result in knowing not very much about anything. The world is indeed complicated and we need to chunk it up into manageable bits if we want to be able to process it. I think the recent rise in interdisciplinary fields of all varieties simply reflects a need to partition things a little bit differently, and perhaps less rigidly. History has taught us that great insights come from people with broad interests: Da Vinci’s painting influenced his notions of light and color; Darwin was a naturlist, not just an ornithologist, entomologist, or botanist. Of course, not everyone can be a Darwin or a Da Vinci. The right balance is key. Specialization allows us to add to our knowledge base, one little pixel at a time. But someone needs to be looking at the big picture.