A Trinity PhD student is investigating a new biologically based mental health model

‘There has been a shift towards greater use of social media for both scientific communication and engagement, bringing 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 that there is a disconnect between how mental health conditions are defined and how they manifest biologically.

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

“Living experience shows this, as people’s difficulties rarely fit into one category.”

His research focuses on a potential new model of mental illness that is biologically based and shows how the brain works, not just how symptoms are put together.

To test this, Moore uses brain imaging – particularly functional MRI – to look at patterns of activity in the brain at rest first before comparing how different methods of explaining mental health problems correspond to the brain.

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

Moore holds a master’s degree in biomedical science from Radboud University in the Netherlands, where he studied medical neuroscience.

What inspired you to become a researcher?

As a child, I doubted everything. I was curious about how things worked, and why things were the way they were. I think it was a natural progression that this curiosity led me to science, and eventually to research.

My interest in mental health research is shaped by personal experience, and by seeing the limitations of how mental health conditions are understood and treated. Ultimately this inspired me to pursue a career 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 research area is reliance on traditional diagnostic categories. Although useful in clinical settings, it can limit the way we study mental health from a research perspective, especially if we try to map these categories with brain-based measures. Moving towards dynamic, diagnostic methods is promising, but also presents new methodological and theoretical challenges.

Regarding misconceptions, there is sometimes an expectation that brain imaging can provide clear answers or specific explanations for mental health conditions. In fact, findings are often subtle, possible, and need to be interpreted carefully. Part of the challenge is managing these expectations, while still communicating the importance of this work in advancing our understanding of mental health.

Do you think the public’s interaction with science and data has changed in recent years?

I think there has been a shift towards greater use of social media for both scientific communication and engagement, which brings more people into the conversation and has the potential to expand the scope and impact of research.

At the same time, this has also highlighted some challenges. More access to information does not 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 even more important.

Overall, I think there is a growing desire to engage with science, but also a greater responsibility for researchers to communicate their work clearly, openly, and easily.

How do you encourage engagement in your personal work?

As a first-year PhD student, I’m mainly focused on getting the research off the ground and driving to recruit participants. Ultimately, however, the purpose of any research is to clearly state why the work is important, the methods used, and the insights that emerge.

Encouraging engagement with my work means thinking about communication from the start. Even at this stage, that includes discussing ideas within my lab, presenting initial plans, challenges, and observations, and staying open to feedback. Along with this, I think it’s important to stay connected to the lived experience that supports mental health research. Although my work is primarily theoretical and not always directly translatable, grounding it in a real-world context helps shape the questions I ask and keeps the broader research objective in mind.

Looking ahead, I see this growing further through formal academic engagement such as conferences, posters, and publications, while considering how those findings can be communicated to a wider audience. Even if research is abstract, making it understandable and relevant is key to ensuring it works beyond academia.

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