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
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Robust and replicable effects of ageing on resting state brain electrophysiology measured with MEG.
Preprint
Quinn AJ. et al, (2025)
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Distinct Alpha Networks Modulate Different Aspects of Perceptual Decision-Making
Preprint
Zhou J. et al, (2025)
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Effects of age on resting-state cortical networks
Preprint
Gohil C. et al, (2024)
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Dynamic network analysis of electrophysiological task data
Journal article
Gohil C. et al, (2024), Imaging Neuroscience, 2, 1 - 19
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Comparison between EEG and MEG of static and dynamic resting-state networks
Preprint
Cho S. et al, (2024)