Mats van Es
BSc, MSc, PhD
Postdoctoral Researcher in Machine Learning for Brain Imaging
I am a Postdoctoral Researcher working in the lab of Mark Woolrich, specializing in computational methods for NeuroImaging, specifically magnetoencephelography (MEG). I have a fundamental interest in understanding how synchronisation organises neural processing. Because I want to find general rules of neural processing, I don't limit myself to a specific cognitive domain, though I most of my research is focussed on resting state, (spatial) attention, vision, movement, and memory.
After a BSc in Biophysics and a MSc in Cognitive Neuroscience, I did a PhD at the Donders Institute (Radboud University, Netherlands) with Dr. Jan-Mathijs Schoffelen, studying how neural oscillations affect neural processing and behaviour. 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. I now continue my involvement in method development, researching better ways to use decoding for MEG analysis, as well as improving workflows to analyse electrophysiology data in general (most notably OSLpy https://github.com/OHBA-analysis/oslpy/tree/main/osl)
Interpretable many-class decoding for MEG.
Csaky R. et al, (2023), Neuroimage, 282
osl-dynamics: A toolbox for modelling fast dynamic brain activity
Gohil C. et al, (2023)
Large-scale cortical networks are organized in structured cycles
van Es MWJ. et al, (2023)
Interpretable full-epoch multiclass decoding for M/EEG
Csaky R. et al, (2023)
The relationship between frequency content and representational dynamics in the decoding of neurophysiological data.
Higgins C. et al, (2022), Neuroimage