I’m pleased to introduce you to our new Digital Associate Editor (DAE), Melinh Lai (pictured below). If you read her post authored in a guest capacity, you are already familiar with her. 

In the interview with Melinh, I asked my now-standard DAE questions and was entertained by her thoughtful, clever, humorous responses and I suspect you will be too. Most of us will also relate to her feelings when reading often oversimplified and over-hyped scientific findings in the media. As part of the Digital Content team, she will mainly write up (in a hype-free manner) some of the latest research published in one of the Society’s seven journals. Watch out for her posts, and follow her on Twitter @melinhlai. She’ll be on the job market next year, so if you have a language researcher position open (especially one that involves comprehension and prediction), have a read through her impressive cv. 

Without further delay, meet Melinh (and her cat, Sandwich) …

What’s your area of research?

I primarily study language comprehension, with a particular focus on the predictions we make while we go about understanding language, and I mainly use event-related potentials (or ERPs) which you can also think of as “brainwaves”.

When we read text or listen to someone speak, we can often use a lot of different kinds of contextual cues—like preceding words or topics, the goals of a given conversation or piece of text, or what another person is looking at—to guess what kinds of words, concepts, or grammatical structures we’re likely to hear or read about next.

When our predictions are correct, we tend to process those correctly-predicted things more easily, which helps make the overall task of language comprehension (where you have to make quick work of connecting a very fast, and often very noisy, signal to complex representations of meaning) a lot easier. These processing patterns are reflected in the electrical signals coming from our brains, which we can record and study by placing sensors on top of a person’s head while they read text or listen to audio recordings.

I’m particularly interested in the mechanisms that create those predictions and how those mechanisms fit in with other processes, like potential effects on memory or how we choose to allocate attentional resources. But in general, I just love language and all the different ways we can use it, acquire it, and, of course, comprehend it so I also love reading about all the different kinds of ways to study other aspects of language—beyond just prediction and comprehension.

What’s the most exciting concept in cognitive science?

I bet you might predict (!) that I’d say something like “language of course!” but if you did, I’m going to mildly violate your prediction. I do think it is one of the most fascinating things to study, but it would also be kind of an incomplete answer to leave it at that.

Language comprehension relies on a lot of other processes, including memory, perception, attention, and decision-making, and—sorry if this sounds a little preachy—you can’t really understand how comprehension works without knowing how all those other things come together and interact with each other during the comprehension process.

This is all to say that I’m often most excited to learn about mechanisms of prediction and/or broader comprehension that incorporate findings from multiple research areas. Even if I end up disagreeing with at least some aspects of a given theory or mechanism, it’s always a really cool—dare I say even fun—challenge to try and fit all these puzzle pieces together to form a cohesive story about how our minds ultimately derive meaning from language.

What’s the most critical unsolved challenge or unanswered question for cognitive scientists?

I’m a little worried that my answer might sound like I’m misunderstanding one of the great endeavors of cognitive science—to answer the question of “How does the mind work?” But I do think an important challenge within cognitive science is the fact that we very rarely understand our participants’ motivations and decision-making processes as they perform our experimental tasks.

Most experimental paradigms offer very necessary levels of control over both environmental details and task manipulations; as we know from our introductory courses, this level of control is what allows us to make conclusions about causation. But for all the control we can exert in an experimental context, we still don’t really know what any particular participant is thinking during any particular experiment.

A college student who just wants to get an experiment over and done with is likely going to process information at least somewhat differently from someone who is eager to perform well (whatever that means to a person who is unlikely to know the underlying research goals when they first step into a lab). These very different motivations could lead to very different outcomes!

There are lots of ways that researchers can try to mitigate these potential effects, but at the end of the day, short of mind-reading, there’s really no way to be sure that the participants in our samples are thinking in the ways that we often assume from our theories. But maybe that’s also fine. After all, mind-reading would just take all the fun out of cognitive science research.

What drew you to science communication?

Tell me if I’m repeating myself, but: I really love language! In particular, I really like that any given topic can be discussed in many different ways to very different effects. So on a surface level, I just really enjoy the kind of “translation” work that goes into taking a very academic, often dense, kind of writing and finding appropriate words or phrases to make the underlying concepts more accessible to a wider audience while still preserving the original ideas. It can feel like a fun linguistic puzzle with a very satisfying ending, while also being a bit of a creative outlet (i.e., I get to occasionally crack jokes) where I get to engage with new and interesting research. What’s not to like about that?

On a more personal level, I think an often-unspoken aspect of academic life is how easy it is to feel like one’s research interests are very far removed from non-academics. Part of me is drawn to science communication for the selfish reason of just wanting to be able to share my enthusiasm for work that I find interesting without seeing another person’s eyes immediately glaze over with disinterest. On the flip side of this, whenever I read a clickbait headline starting with the phrase “According to science…!” my internal grouch can’t help but think that for every genuine scientific discovery, even those that seem small and inconsequential, there are a thousand ways that it can be misconstrued and spread into the general populace. From those two perspectives, science communication just feels like a natural way to both connect with other people and also mitigate some of those misconceptions about scientific research.

Is there anything else you want us to know about you?

Shameless self-promotion time (except that I do actually feel a little shy doing this)! In the next year, I’ll be graduating from the University of Illinois, where I’m currently a member of the Cognition and Brain Lab, directed by Dr. Kara Federmeier. I’m starting to keep an eye out for post-doctoral opportunities to keep researching comprehension and prediction, and I’d also love to teach introductory psychology and cognitive psychology courses!

Also, I’d like to continue the trend that Ben Wolfe started by sharing a picture of my own frequent collaborator, Sandwich. She’s provided me with invaluable advice, such as “Meow” and, when I need to hear it, “Hiss.” Members of the Society for Psychophysiological Research might also recognize her from the society’s news section.