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Michiel Cottaar

Postdoctoral Research Assistant

Studying the brain's cellular structure using MRI

Cellular structure

The main goal of my research is to develop techniques to study the cellular structure of the living human brain non-invasively. My main focus is on MRI, where a variety of modalities already exist that are sensitive to different aspects of the cellular structure, such as diffusion-weighted MRI, quantitative susceptibility mapping, relaxometry, and magnetisation transfer. I aim to combine these modalities to create MRI acquisitions that can identify any change in the cellular structure.

Most relevant contributions:

  • MCMRSimulator.jl: Monte Carlo simulator of MRI signal generation that includes all the ways that the tissue cellular structure affects the MRI signal evolution. There is a tutorial available, although the code is still under active development. 
  • DIffusion-Prepared Phase Imaging (DIPPI): A new MRI sequence combining the sensitivities of diffusion-weighted and susceptibility MRI to estimate the average myelin thickness surrounding axons (Cottaar, M. et al. (2021) ‘Quantifying myelin in crossing fibers using Diffusion‐prepared phase imaging: Theory and simulations’, Magnetic Resonance in Medicine, 86(5), p. mrm.28907. doi:10.1002/mrm.28907).
  • BENCH: A framework to identify any differences in the cellular structure between two groups, which works even if the MRI data acquired is insufficient to provide a complete picture of the cellular structure in either group (Rafipoor, H. ..., Cottaar, M. (2022) ‘Identifying microstructural changes in diffusion MRI; How to circumvent parameter degeneracy’, NeuroImage, 260, p. 119452. doi:10.1016/j.neuroimage.2022.119452).
  • WHIM: A tool to consistently identifying the same fibre populations across multiple subjects in a study, so that their microstructural properties can be compared (i.e., fixel-based analysis) (
    Rafipoor, H. et al. (2023) ‘Hierarchical Modelling of Crossing Fibres in the White Matter’. bioRxiv, p. 2023.05.24.542138. doi:10.1101/2023.05.24.542138.)

Neuroimaging pipelines

I have developed several tools to make it easier to write and share reusable neuroimaging pipelines:

  • File-tree: Describe the directory structure containing the input and output files of your pipeline in a simple text file, separated from the actual pipeline code (tutorial). The resulting files can be easily visualised in FSLeyes for quality control (docs). 
  • FSL-pipe: Builds a full-fledged, flexible pipeline out of a set of user-defined recipes that describe how individual intermediate/output files are created (docs).


Diffusion MRI tractography struggles to accurately predict where white matter tracts actually terminate on the cortical surface. We are working on models to include the information of the cortical shape from structural MRI to improve the accuracy of the tractography close to the cortex, which should lead to more accurate mappings of which the connections to and between cortical regions (Cottaar, M. et al. (2020) ‘Modelling white matter in gyral blades as a continuous vector field’, NeuroImage, 227, p. 117693. doi:10.1016/j.neuroimage.2020.117693.)


Recent publications

More publications