Michiel Cottaar
Postdoctoral Research Assistant
Studying the brain's cellular structure using MRI
Contact information
Research groups
Research interests
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 work on improving the FMRIB Software Library (FSL) tools for diffusion MRI analysis
In addition, 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).
TRACTOGRAPHY
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
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Linking microscopy to diffusion MRI with degenerate biophysical models: an application of the Bayesian EstimatioN of CHange (BENCH) framework
Preprint
Kor DZL. et al, (2024)
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An open resource combining multi-contrast MRI and microscopy in the macaque brain.
Journal article
Howard AFD. et al, (2023), Nat Commun, 14
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Universal Dynamic Fitting of Magnetic Resonance Spectroscopy
Preprint
Clarke WT. et al, (2023)
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Estimating axial diffusivity in the NODDI model.
Journal article
Howard AF. et al, (2022), Neuroimage, 262
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Identifying microstructural changes in diffusion MRI; How to circumvent parameter degeneracy.
Journal article
Rafipoor H. et al, (2022), Neuroimage, 260
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A macroscopic link between interhemispheric tract myelination and cortico-cortical interactions during action reprogramming.
Journal article
Lazari A. et al, (2022), Nat Commun, 13
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Hebbian activity-dependent plasticity in white matter.
Journal article
Lazari A. et al, (2022), Cell Rep, 39
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Hebbian activity-dependent plasticity in white matter
Preprint
Lazari A. et al, (2022)
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A macroscopic link between interhemispheric tract myelination and cortico-cortical interactions during action reprogramming
Preprint
Lazari A. et al, (2021)
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Reassessing associations between white matter and behaviour with multimodal microstructural imaging.
Journal article
Lazari A. et al, (2021), Cortex, 145, 187 - 200