Michiel Cottaar

The paper examines the relationship between white matter microstructure, measured by fractional anisotropy, and transition to psychosis in individuals at clinical high risk, finding directionally consistent but small associations.

The paper examines longitudinal white matter changes in early psychosis using diffusion tensor imaging and finds no significant group differences or associations with symptom progression, but links antipsychotic medication dose to lower fractional anisotropy.

This study uses Monte-Carlo simulations to show that permeability and magnetization transfer significantly affect diffusion MRI signal and parameter estimation in cylindrical substrates.

The paper introduces a multi-modal Monte Carlo MRI simulator that models tissue microstructure's impact on various MRI sequences and validates it against established techniques.

This paper develops a hybrid diffusion MRI-microscopy tractography method to improve 3D brain connectivity reconstruction by combining high-resolution microscopy with diffusion MRI data.

The paper applies the BENCH framework to link diffusion MRI signal changes to microstructural features in brain tissue using histology data.

This paper introduces a hierarchical framework for fitting crossing fibre models to diffusion MRI data, enabling consistent and comparable fibre-specific parameters across subjects.

The paper introduces a universal dynamic MRS toolbox that simultaneously fits dynamic spectra, reducing parameter uncertainty and replicating prior studies.

The paper introduces the BigMac dataset, combining multi-contrast MRI and microscopy data from a macaque brain, enabling multimodal analysis across scales and tissue states.

This paper estimates axial diffusivity in the NODDI model using high b-value data and shows the impact of noise assumptions on parameter estimates.

This paper introduces BENCH, a Bayesian framework to infer parameter changes in biophysical models despite parameter degeneracies, applied to diffusion MRI data.

This paper reassesses WM-behaviour relationships using multimodal microstructural imaging in 50 healthy individuals, finding partial support for FA-behaviour links and suggesting multimodal approaches may better capture WM-behaviour associations.

This paper introduces DIPPI, a new MRI technique that estimates the g-ratio per fibre population in crossing voxels, improving myelin quantification in complex white matter regions.

The paper links multimodal brain imaging markers in adolescents with physical activity and health measures using canonical correlation analysis.

The paper demonstrates that Hebbian plasticity occurs in human white matter, showing increased cortical excitability and myelin markers after co-stimulation of cortical areas.

This paper introduces an algorithm to reduce tractography biases in white matter by modeling fibre density and orientation as a divergence-free vector field, improving cross-modal agreement with functional connectomes.

This paper proposes using two-flip angle DW-SSFP data and a Gamma distribution model to correct for B1 inhomogeneity and improve diffusivity estimates in post-mortem human brains at 7T.

This paper proposes a joint model for diffusion MRI and microscopy data to improve microstructural analysis by combining complementary information from both modalities.

The paper identifies a connectional hub in the rostral anterior cingulate cortex (rACC) that integrates inputs from diverse frontal cortex regions in both macaques and humans.

This paper introduces the Additive Signal Change (ASC) method to improve the specificity of functional connectivity analysis by disambiguating signal changes underlying neural activity correlations.