Tales from the Lab: Choosing What to Study Can Be Complex

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Over the next three months, the Dana Foundation blog is pleased to host a new blog series, “Tales from the Lab,” featuring two neuroscience graduate student guest bloggers: Tim Balmer from Georgia State University and Grace Lindsay from Columbia University. Tim’s contributions will focus on life as a graduate neuroscience student (pay attention for helpful tips!) and Grace will focus on neuroplasticity. This is Tim’s first blog in the series.

How do students select research projects? Very carefully. Every project starts with a question: How does a specific neural process work? But how do you choose which specific process, and what aspects of that process?

The goal of principal investigators (PIs) who direct neuroscience research labs is to answer questions that will increase our knowledge of the working brain. Graduate students and post-docs in the lab (the people who spend the most time in lab coats) generally work on one or two independent projects relating to the lab’s general research question: how a specific brain mechanism operates in health or disease.

Within the lab’s research area, there is often a great deal of flexibility in choosing an experimental target. Some PIs give their students projects with a clear directive; others expect their students to design their own projects. In either case, each experiment leads to many others, and the project may evolve in unplanned directions and into uncharted territory.

Over time (an average six years for a neuroscience Ph.D.), students increasingly become the custodians of their work, choosing which path to pursue first and even whether to continue. But that first choice can be hard.

To help narrow their choices, Uri Alon of the Weizmann Institute suggests visualizing a student’s potential research questions as a two-dimensional space with an axis of ease (how feasible is it) and an axis of interest (how much knowledge will be gained and how interesting it sounds to the student). The best projects fall into the quadrant of high ease and high interest. However, designing a project that will increase knowledge a great deal AND be relatively easy to complete is very difficult.

Generally, more-important questions are harder to answer. They may require the use of new technologies and months of troubleshooting. Or they may require technical expertise that takes practice. Every lab has a list of projects that they would love to do…but that may require generating a new mutant, training hundreds of animals, recruiting participants with an uncommon disorder, observing a rare species in the wild, or completing a potentially impossible reaction.

Many PIs suggest students work on a couple of projects simultaneously. If there isn’t a project that meets high interest and feasibility, choose two: One that is really interesting but a bit risky and another that is a sure thing. If the risky project produces significant results, it could make a nice story for a high profile publication. If the risky one fails, you’ll at least have something to publish from the other study.

Projects will fail; there is nothing worse than feeling like you’ve worked for years and have nothing to show for it. But the experience of choosing projects and seeing them evolve, positive or negative, helps us when we choose our next project, and our next.

Recommended reading: Alon, U. (2009). How to choose a good scientific problem. Molecular cell, 35(6), 726-728.

– Tim Balmer

Tim Balmer is a Neuroscience Ph.D. student at Georgia State University. He studies the role of experience in the development and plasticity of sensory systems.

One response

  1. But does not a “failed” project result in information not known before it was tried? Aren’t the surprises and the unknowns the stuff of scientific discovery? O brave new world! Continue on!

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