Dr Anna Sadnicka, Computational Movement Disorders Lab, University College London
As both a doctor and a researcher working with people who have movement disorders, I see every day how profoundly dystonia can affect someone’s life. Dystonia is a complex and heterogeneous group of conditions, and too often, that complexity goes unrecognised. Even when research is underway, it doesn’t always align closely enough with the real-world challenges patients face in the clinic. The path from research discovery to treatment can feel far too long.
At University College London, I lead the Computational Movement Disorders Lab. We bring together expertise from many disciplines — including physiotherapists, computational neuroscientists, psychologists, software engineers, and clinicians. We work side by side, combining our skills to answer core clinical questions, trying to close the gap between science and real-world change.
Measuring Movement in New Ways
One of our key priorities is to develop methods for measuring movement that are accurate, objective, and accessible. We are building tools that use widely available technology, such as multiple video cameras, alongside computer vision, a branch of artificial intelligence that extracts detailed movement data directly from video recordings. These systems are designed to be simple and cost-effective enough for use not only in specialist research facilities but also in routine clinics and rehabilitation settings.
Why this matters:
- It enables faster and more reliable diagnoses — essential when many people with dystonia still face months or even years before receiving the correct diagnosis.
- It allows precise tracking of subtle changes in movement over time, providing sensitive, objective indicators of whether a treatment is effective.
- It supports the development of dynamic biomarkers — markers that reflect not only the presence of dystonia but also how it changes over time.
This approach will directly support clinical decision-making while also advancing our understanding of the brain mechanisms that control movement.
Key Challenges
There remain significant challenges in dystonia research, for example:
- Dystonia is not a single disorder but a family of related conditions with varied presentations. We need to both identify common features across types and recognise when distinct models are needed for specific subtypes.
- The brain networks involved are complex. Historically, research focused on a single structure — the basal ganglia. We now know that dystonia involves broader, distributed brain networks, requiring models that reflect multiple interacting systems.
- Genetics is only part of the story. While some forms are linked to specific genes, many — especially focal dystonias — are shaped by a combination of genetic and environmental factors.
To address these challenges, we need to remain humble about what we know and push for cutting-edge science through close collaboration with neuroscientists working in related fields. By investigating dystonia from multiple perspectives, from molecular pathways to brain network dynamics to real-world movement, we can build more complete and accurate models of the condition. These tailored models will, in turn, support more effective, personalised treatments.
Looking Ahead
Our vision is to move beyond symptom management and towards a deeper understanding of the mechanisms underlying dystonia and to translate that knowledge into treatments that are more effective, targeted, and accessible. Patient-led organisations, such as Dystonia Europe, play a vital role in ensuring that the lived experience of dystonia continues to shape the direction of care and research.
By aligning clinical insight with rigorous science, and by working across disciplines, we can shorten the distance between research findings and their application in everyday practice. This is the path to faster diagnoses, more precise treatments, and better outcomes for people living with dystonia.
