Mats van Es
BSc, MSc, PhD
Postdoctoral Researcher in Cognitive Neuroscience
About me
I am a Postdoctoral Researcher working in the lab of Mark Woolrich, specializing in computational methods for Neuroimaging, specifically magneto- and electro-encephelography (M/EEG). I have a fundamental interest in understanding how neuronal synchronisation supports cognition, particularly by studying large-scale functional brain networks. For example, I have recently shown that functional brain networks activate in cycles of about 300-1000 milliseconds. This is the first concrete evidence that large-scale brain networks follow organised temporal rules, and may enable the brain to coordinate different cognitive functions effectively.
In addition, I aim to translate my neuroscientific findings into clinical applications. I work on identifying MEG-based biomarkers for brain disorders, such as Alzheimer's disease, and advocate for using dynamic network-based metrics to replace conventional "static" (i.e., time-averaged) metrics.
Before my time in Oxford, I obtained a BSc in Biophysics, and a MSc and Phd in Cognitive Neuroscience, at the Radboud University (Nijmegen, Netherlands). During my PhD at the Donders Institute I worked with Dr. Jan-Mathijs Schoffelen, studying how neuronal synchrony affects visual processing and attention. In addition, I had the privilege to learn from and work with the main developers of the FieldTrip toolbox, building my expertise in MEG methods and open-source software development. At Oxford, I continue M/EEG methods development, most notably in the open-source Python toolboxes osl-ephys and osl-dynamics.
Recent publications
Divergence of cortical neurophysiology across different neurodegenerative disorders compared to healthy ageing.
Journal article
Trubshaw M. et al, (2026), Prog Neurobiol, 257
Robust and replicable effects of ageing on resting state brain electrophysiology measured with MEG
Preprint
Quinn AJ. et al, (2025)
Robust and replicable effects of ageing on resting state brain electrophysiology measured with MEG
Preprint
Quinn AJ. et al, (2025)
Biomarkers
Journal article
Krugliak A. et al, (2025), Alzheimer S Dementia the Journal of the Alzheimer S Association, 21
