‘There’s been a shift towards greater use of social media in both science communication and engagement, which brings more people into the conversation.’

Ellen Moore is a FutureNeuro PhD student in the Gillan Lab at Trinity College Dublin, where she investigates mental health and cognition using brain mapping and real-time, smartphone-based data collection.

Moore explains to SiliconRepublic.com that there is a disconnect between how mental health conditions are described and how they manifest biologically.

“Specifically, research relies heavily on diagnostic labels like ‘depression’ or ‘anxiety’, which are useful but don’t map neatly onto how the brain actually works,” she says. “In reality, mental health symptoms tend to overlap and exist across a spectrum, rather than fitting into neat boxes.

“Lived experience reflects this, as people’s difficulties rarely align perfectly with a single category.”

Her research focuses on a potential new model of mental illness that is grounded in biology and reflects how the brain functions, not just how symptoms are grouped together.

To explore this, Moore uses brain imaging – specifically, functional MRI – to look at patterns of activity in the brain at rest before comparing how different ways of defining mental health problems match up to the results.

“The key question is simple – which approach better explains what we see in the brain?”

Moore has a master’s degree in biomedical sciences from Radboud University in the Netherlands, where she specialised in medical neuroscience.

What inspired you to become a researcher?

As a kid, I questioned everything. I was curious about how things worked and why things were the way they were. I think it was a natural progression for this curiosity to lead me towards science and ultimately towards research.

My interest in mental health research was shaped by personal experience, and by seeing the limitations in how mental health conditions are understood and treated. This ultimately motivated me to pursue work that aims to bridge the gap between lived experience, research methods and clinical practice.

What are some of the biggest challenges or misconceptions you face as a researcher in your field?

One challenge in my area of research is the reliance on traditional diagnostic categories. While useful in clinical settings, they can limit how we study mental health from a research perspective, particularly when trying to map these categories onto brain-based measures. Moving toward more flexible, transdiagnostic approaches is promising, but it also introduces new methodological and conceptual challenges.

In terms of misconceptions, there is sometimes an expectation that brain imaging can provide clear-cut answers or definitive explanations for mental health conditions. In reality, the findings are often subtle, probabilistic and require careful interpretation. Part of the challenge is managing these expectations while still communicating the value of this work in advancing our understanding of mental health.

Do you think public engagement with science and data has changed in recent years?

I think there’s been a shift towards greater use of social media in both science communication and engagement, which brings more people into the conversation and has the potential to increase the scope and effect of research.

At the same time, this has also highlighted some challenges. Increased access to information doesn’t always mean increased understanding, and complex findings can be misinterpreted or oversimplified. In fields like mental health, where the science is already nuanced, this makes clear communication especially important.

Overall, I think there is a growing appetite for engaging with science but also a greater responsibility on researchers to communicate their work clearly, transparently and accessibly.

How do you encourage engagement with your own work?

As a first-year PhD student, my focus has primarily been on getting the research off the ground and on driving participant recruitment. Ultimately, however, the goal of any research is to clearly convey why the work matters, the approaches being used and the insights that emerge.

Encouraging engagement with my work means thinking about communication from the outset. Even at this stage, that involves discussing ideas within my lab, presenting preliminary plans, challenges and observations, and remaining open to feedback. Alongside this, I think it’s important to stay connected to the lived experiences that underpin mental health research. While my work is largely theoretical and not always directly translatable, grounding it in real-world context helps shape the questions I ask and keeps the broader purpose of the research in view.

Looking ahead, I see this developing further through more formal academic engagement such as conferences, posters and publications, while also considering how findings can be communicated more accessibly to wider audiences. Even when research is abstract, making it understandable and relevant is key to ensuring it resonates beyond academia.

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